1
|
Gherardini M, Ianniciello V, Masiero F, Paggetti F, D'Accolti D, La Frazia E, Mani O, Dalise S, Dejanovic K, Fragapane N, Maggiani L, Ipponi E, Controzzi M, Nicastro M, Chisari C, Andreani L, Cipriani C. Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets. Sci Robot 2024; 9:eadp3260. [PMID: 39259781 DOI: 10.1126/scirobotics.adp3260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 08/15/2024] [Indexed: 09/13/2024]
Abstract
The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.
Collapse
Affiliation(s)
- Marta Gherardini
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Valerio Ianniciello
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Federico Masiero
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Flavia Paggetti
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Daniele D'Accolti
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eliana La Frazia
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Olimpia Mani
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Stefania Dalise
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Katarina Dejanovic
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Noemi Fragapane
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Luca Maggiani
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Edoardo Ipponi
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Marco Controzzi
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Manuela Nicastro
- Orthopaedic and Burn Centre Anaesthesiology and Reanimation, University Hospital of Pisa, Pisa, Italy
| | - Carmelo Chisari
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Lorenzo Andreani
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Christian Cipriani
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| |
Collapse
|
2
|
Manero A, Rivera V, Fu Q, Schwartzman JD, Prock-Gibbs H, Shah N, Gandhi D, White E, Crawford KE, Coathup MJ. Emerging Medical Technologies and Their Use in Bionic Repair and Human Augmentation. Bioengineering (Basel) 2024; 11:695. [PMID: 39061777 PMCID: PMC11274085 DOI: 10.3390/bioengineering11070695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 07/04/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
As both the proportion of older people and the length of life increases globally, a rise in age-related degenerative diseases, disability, and prolonged dependency is projected. However, more sophisticated biomedical materials, as well as an improved understanding of human disease, is forecast to revolutionize the diagnosis and treatment of conditions ranging from osteoarthritis to Alzheimer's disease as well as impact disease prevention. Another, albeit quieter, revolution is also taking place within society: human augmentation. In this context, humans seek to improve themselves, metamorphosing through self-discipline or more recently, through use of emerging medical technologies, with the goal of transcending aging and mortality. In this review, and in the pursuit of improved medical care following aging, disease, disability, or injury, we first highlight cutting-edge and emerging materials-based neuroprosthetic technologies designed to restore limb or organ function. We highlight the potential for these technologies to be utilized to augment human performance beyond the range of natural performance. We discuss and explore the growing social movement of human augmentation and the idea that it is possible and desirable to use emerging technologies to push the boundaries of what it means to be a healthy human into the realm of superhuman performance and intelligence. This potential future capability is contrasted with limitations in the right-to-repair legislation, which may create challenges for patients. Now is the time for continued discussion of the ethical strategies for research, implementation, and long-term device sustainability or repair.
Collapse
Affiliation(s)
- Albert Manero
- Limbitless Solutions, University of Central Florida, 12703 Research Parkway, Suite 100, Orlando, FL 32826, USA (V.R.)
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
| | - Viviana Rivera
- Limbitless Solutions, University of Central Florida, 12703 Research Parkway, Suite 100, Orlando, FL 32826, USA (V.R.)
| | - Qiushi Fu
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA
| | - Jonathan D. Schwartzman
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Hannah Prock-Gibbs
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Neel Shah
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Deep Gandhi
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Evan White
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Kaitlyn E. Crawford
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- Department of Materials Science and Engineering, University of Central Florida, Orlando, FL 32816, USA
| | - Melanie J. Coathup
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| |
Collapse
|
3
|
Guo K, Lu J, Wu Y, Hu X, Yang H. The Latest Research Progress on Bionic Artificial Hands: A Systematic Review. MICROMACHINES 2024; 15:891. [PMID: 39064402 PMCID: PMC11278702 DOI: 10.3390/mi15070891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 07/01/2024] [Accepted: 07/03/2024] [Indexed: 07/28/2024]
Abstract
Bionic prosthetic hands hold the potential to replicate the functionality of human hands. The use of bionic limbs can assist amputees in performing everyday activities. This article systematically reviews the research progress on bionic prostheses, with a focus on control mechanisms, sensory feedback integration, and mechanical design innovations. It emphasizes the use of bioelectrical signals, such as electromyography (EMG), for prosthetic control and discusses the application of machine learning algorithms to enhance the accuracy of gesture recognition. Additionally, the paper explores advancements in sensory feedback technologies, including tactile, visual, and auditory modalities, which enhance user interaction by providing essential environmental feedback. The mechanical design of prosthetic hands is also examined, with particular attention to achieving a balance between dexterity, weight, and durability. Our contribution consists of compiling current research trends and identifying key areas for future development, including the enhancement of control system integration and improving the aesthetic and functional resemblance of prostheses to natural limbs. This work aims to inform and inspire ongoing research that seeks to refine the utility and accessibility of prosthetic hands for amputees, emphasizing user-centric innovations.
Collapse
Affiliation(s)
- Kai Guo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
| | - Jingxin Lu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China
| | - Yuwen Wu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Xuhui Hu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Hongbo Yang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China
| |
Collapse
|
4
|
Lambrecht JM, Cady SR, Peterson EJ, Dunning JL, Dinsmoor DA, Pape F, Graczyk EL, Tyler DJ. A distributed, high-channel-count, implanted bidirectional system for restoration of somatosensation and myoelectric control. J Neural Eng 2024; 21:036049. [PMID: 38861967 DOI: 10.1088/1741-2552/ad56c9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/11/2024] [Indexed: 06/13/2024]
Abstract
Objective. We intend to chronically restore somatosensation and provide high-fidelity myoelectric control for those with limb loss via a novel, distributed, high-channel-count, implanted system.Approach.We have developed the implanted Somatosensory Electrical Neurostimulation and Sensing (iSens®) system to support peripheral nerve stimulation through up to 64, 96, or 128 electrode contacts with myoelectric recording from 16, 8, or 0 bipolar sites, respectively. The rechargeable central device has Bluetooth® wireless telemetry to communicate to external devices and wired connections for up to four implanted satellite stimulation or recording devices. We characterized the stimulation, recording, battery runtime, and wireless performance and completed safety testing to support its use in human trials.Results.The stimulator operates as expected across a range of parameters and can schedule multiple asynchronous, interleaved pulse trains subject to total charge delivery limits. Recorded signals in saline show negligible stimulus artifact when 10 cm from a 1 mA stimulating source. The wireless telemetry range exceeds 1 m (direction and orientation dependent) in a saline torso phantom. The bandwidth supports 100 Hz bidirectional update rates of stimulation commands and data features or streaming select full bandwidth myoelectric signals. Preliminary first-in-human data validates the bench testing result.Significance.We developed, tested, and clinically implemented an advanced, modular, fully implanted peripheral stimulation and sensing system for somatosensory restoration and myoelectric control. The modularity in electrode type and number, including distributed sensing and stimulation, supports a wide variety of applications; iSens® is a flexible platform to bring peripheral neuromodulation applications to clinical reality. ClinicalTrials.gov ID NCT04430218.
Collapse
Affiliation(s)
- Joris M Lambrecht
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | - Sedona R Cady
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | | | - Jeremy L Dunning
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | | | - Forrest Pape
- Medtronic plc, Minneapolis, MN, United States of America
| | - Emily L Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| |
Collapse
|
5
|
Gstoettner C, Laengle G, Harnoncourt L, Sassu P, Aszmann OC. Targeted muscle reinnervation in bionic upper limb reconstruction: current status and future directions. J Hand Surg Eur Vol 2024; 49:783-791. [PMID: 38366374 DOI: 10.1177/17531934241227795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
Abstract
Selective nerve transfers are used in the setting of upper limb amputation to improve myoelectric prosthesis control. This surgical concept is referred to as targeted muscle reinnervation (TMR) and describes the rerouting of the major nerves of the arm onto the motor branches of the residual limb musculature. Aside from providing additional myosignals for prosthetic control, TMR can treat and prevent neuroma pain and possibly also phantom limb pain. This article reviews the history and current applications of TMR in upper limb amputation, with a focus on practical considerations. It further explores and identifies technological innovations to improve the man-machine interface in amputation care, particularly regarding implantable interfaces, such as muscle electrodes and osseointegration. Finally, future clinical directions and possible scientific avenues in this field are presented and critically discussed.
Collapse
Affiliation(s)
- Clemens Gstoettner
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University Vienna, Vienna, Austria
| | - Gregor Laengle
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University Vienna, Vienna, Austria
| | - Leopold Harnoncourt
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University Vienna, Vienna, Austria
| | - Paolo Sassu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Orthoplastic, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University Vienna, Vienna, Austria
| |
Collapse
|
6
|
Bhatia A, Hanna J, Stuart T, Kasper KA, Clausen DM, Gutruf P. Wireless Battery-free and Fully Implantable Organ Interfaces. Chem Rev 2024; 124:2205-2280. [PMID: 38382030 DOI: 10.1021/acs.chemrev.3c00425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.
Collapse
Affiliation(s)
- Aman Bhatia
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Jessica Hanna
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Tucker Stuart
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Kevin Albert Kasper
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - David Marshall Clausen
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Philipp Gutruf
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Department of Electrical and Computer Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Bio5 Institute, The University of Arizona, Tucson, Arizona 85721, United States
- Neuroscience Graduate Interdisciplinary Program (GIDP), The University of Arizona, Tucson, Arizona 85721, United States
| |
Collapse
|
7
|
Harnoncourt L, Gstoettner C, Laengle G, Boesendorfer A, Aszmann O. [Prosthetic Fitting Concepts after Major Amputation in the Upper Limb - an Overview of Current Possibilities]. HANDCHIR MIKROCHIR P 2024; 56:84-92. [PMID: 38417811 PMCID: PMC10954373 DOI: 10.1055/a-2260-9842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 01/31/2024] [Indexed: 03/01/2024] Open
Abstract
BACKGROUND The upper extremity and particularly the hands are crucial for patients in interacting with their environment, therefore amputations or severe damage with loss of hand function significantly impact their quality of life. In cases where biological reconstruction is not feasible or does not lead to sufficient success, bionic reconstruction plays a key role in patient care. Classical myoelectric prostheses are controlled using two signals derived from surface electrodes in the area of the stump muscles. Prosthesis control, especially in high amputations, is then limited and cumbersome. The surgical technique of Targeted Muscle Reinnervation (TMR) offers an innovative solution: The major arm nerves that have lost their target organs due to amputation are rerouted to muscles in the stump area. This enables the establishment of cognitive control signals that allow significantly improved prosthesis control. PATIENTS/MATERIALS AND METHODS A selective literature review on TMR and bionic reconstruction was conducted, incorporating relevant articles and discussing them considering the clinical experience of our research group. Additionally, a clinical case is presented. RESULTS Bionic reconstruction combined with Targeted Muscle Reinnervation enables intuitive prosthetic control with simultaneous movement of various prosthetic degrees of freedom and the treatment of neuroma and phantom limb pain. Long-term success requires a high level of patient compliance and intensive signal training during the prosthetic rehabilitation phase. Despite technological advances, challenges persist, especially in enhancing signal transmission and integrating natural sensory feedback into bionic prostheses. CONCLUSION TMR surgery represents a significant advancement in the bionic care of amputees. Employing selective nerve transfers for signal multiplication and amplification, opens up possibilities for improving myoelectric prosthesis function and thus enhancing patient care. Advances in the area of external prosthetic components, improvements in the skeletal connection due to osseointegration and more fluid signal transmission using wireless, fully implanted electrode systems will lead to significant progress in bionic reconstruction, both in terms of precision of movement and embodiment.
Collapse
Affiliation(s)
- Leopold Harnoncourt
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
| | - Clemens Gstoettner
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
| | - Gregor Laengle
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
| | - Anna Boesendorfer
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
| | - Oskar Aszmann
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
| |
Collapse
|
8
|
Quinn KN, Tian Y, Budde R, Irazoqui PP, Tuffaha S, Thakor NV. Neuromuscular implants: Interfacing with skeletal muscle for improved clinical translation of prosthetic limbs. Muscle Nerve 2024; 69:134-147. [PMID: 38126120 DOI: 10.1002/mus.28029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 11/27/2023] [Accepted: 12/10/2023] [Indexed: 12/23/2023]
Abstract
After an amputation, advanced prosthetic limbs can be used to interface with the nervous system and restore motor function. Despite numerous breakthroughs in the field, many of the recent research advancements have not been widely integrated into clinical practice. This review highlights recent innovations in neuromuscular implants-specifically those that interface with skeletal muscle-which could improve the clinical translation of prosthetic technologies. Skeletal muscle provides a physiologic gateway to harness and amplify signals from the nervous system. Recent surgical advancements in muscle reinnervation surgeries leverage the "bio-amplification" capabilities of muscle, enabling more intuitive control over a greater number of degrees of freedom in prosthetic limbs than previously achieved. We anticipate that state-of-the-art implantable neuromuscular interfaces that integrate well with skeletal muscle and novel surgical interventions will provide a long-term solution for controlling advanced prostheses. Flexible electrodes are expected to play a crucial role in reducing foreign body responses and improving the longevity of the interface. Additionally, innovations in device miniaturization and ongoing exploration of shape memory polymers could simplify surgical procedures for implanting such interfaces. Once implanted, wireless strategies for powering and transferring data from the interface can eliminate bulky external wires, reduce infection risk, and enhance day-to-day usability. By outlining the current limitations of neuromuscular interfaces along with potential future directions, this review aims to guide continued research efforts and future collaborations between engineers and specialists in the field of neuromuscular and musculoskeletal medicine.
Collapse
Affiliation(s)
- Kiara N Quinn
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Yucheng Tian
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Ryan Budde
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Pedro P Irazoqui
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Sami Tuffaha
- Department of Plastic and Reconstructive Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| |
Collapse
|
9
|
Taghlabi KM, Cruz-Garza JG, Hassan T, Potnis O, Bhenderu LS, Guerrero JR, Whitehead RE, Wu Y, Luan L, Xie C, Robinson JT, Faraji AH. Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review. J Neural Eng 2024; 21:011001. [PMID: 38237175 DOI: 10.1088/1741-2552/ad200f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 01/18/2024] [Indexed: 02/02/2024]
Abstract
Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.
Collapse
Affiliation(s)
- Khaled M Taghlabi
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Jesus G Cruz-Garza
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Taimur Hassan
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Ojas Potnis
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Engineering Medicine, Texas A&M University, Houston, TX 77030, United States of America
| | - Lokeshwar S Bhenderu
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Jaime R Guerrero
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Rachael E Whitehead
- Department of Academic Affairs, Houston Methodist Academic Institute, Houston, TX 77030, United States of America
| | - Yu Wu
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Lan Luan
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Chong Xie
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Jacob T Robinson
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Amir H Faraji
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| |
Collapse
|
10
|
Donati E, Valle G. Neuromorphic hardware for somatosensory neuroprostheses. Nat Commun 2024; 15:556. [PMID: 38228580 PMCID: PMC10791662 DOI: 10.1038/s41467-024-44723-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/03/2024] [Indexed: 01/18/2024] Open
Abstract
In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.
Collapse
Affiliation(s)
- Elisa Donati
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Giacomo Valle
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA.
| |
Collapse
|
11
|
Ortiz-Catalan M, Zbinden J, Millenaar J, D'Accolti D, Controzzi M, Clemente F, Cappello L, Earley EJ, Mastinu E, Kolankowska J, Munoz-Novoa M, Jönsson S, Cipriani C, Sassu P, Brånemark R. A highly integrated bionic hand with neural control and feedback for use in daily life. Sci Robot 2023; 8:eadf7360. [PMID: 37820004 DOI: 10.1126/scirobotics.adf7360] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 09/14/2023] [Indexed: 10/13/2023]
Abstract
Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.
Collapse
Affiliation(s)
- Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden
- Bionics Institute, Melbourne, Australia
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- University of Melbourne, Melbourne, Australia
| | - Jan Zbinden
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | | | - Daniele D'Accolti
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Marco Controzzi
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Leonardo Cappello
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eric J Earley
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Osseointegration Research Consortium, University of Colorado, Aurora, CO, USA
| | - Enzo Mastinu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Maria Munoz-Novoa
- Center for Bionics and Pain Research, Mölndal, Sweden
- Center for Advanced Reconstruction of Extremities, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Stewe Jönsson
- TeamOlmed, Department of Upper Limb Prosthetics, Kungsbacka, Sweden
| | - Christian Cipriani
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Paolo Sassu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Hand Surgery, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Orthopaedics, IRCCS, Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Rickard Brånemark
- Integrum AB, Mölndal, Sweden
- Department of Orthopaedics, Gothenburg University, Gothenburg, Sweden
- K. Lisa Yang Center for Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| |
Collapse
|
12
|
Xu W, Toyoda Y, Lin IC. Upper Extremity Prosthetics: Current Options and Future Innovations. J Hand Surg Am 2023; 48:1034-1044. [PMID: 37436340 DOI: 10.1016/j.jhsa.2023.05.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/04/2023] [Accepted: 05/28/2023] [Indexed: 07/13/2023]
Abstract
Major upper extremity amputations can have a considerable impact on patients' lives, altering their ability to independently perform activities of daily living and leading to changes in occupations and hobbies. Although upper extremity prosthetics have existed for millennia, recent advances have improved prosthetic motor control and sensory feedback, leading to increased overall satisfaction. The goal of this article was to describe the current options that exist for upper extremity prosthetics and explore the recent advances and future directions in prosthetic technology and surgical techniques.
Collapse
Affiliation(s)
- Wen Xu
- Division of Plastic Surgery, Department of Surgery, University of Pennsylvania Health System, Philadelphia, PA
| | - Yoshiko Toyoda
- Division of Plastic Surgery, Department of Surgery, University of Pennsylvania Health System, Philadelphia, PA
| | - Ines C Lin
- Division of Plastic Surgery, Department of Surgery, University of Pennsylvania Health System, Philadelphia, PA.
| |
Collapse
|
13
|
Patwardhan S, Gladhill KA, Joiner WM, Schofield JS, Lee BS, Sikdar S. Using principles of motor control to analyze performance of human machine interfaces. Sci Rep 2023; 13:13273. [PMID: 37582852 PMCID: PMC10427694 DOI: 10.1038/s41598-023-40446-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 08/10/2023] [Indexed: 08/17/2023] Open
Abstract
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.
Collapse
Affiliation(s)
| | - Keri Anne Gladhill
- Department of Psychology, George Mason University, Fairfax, VA, 22030, USA
| | - Wilsaan M Joiner
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA, 95616, USA
| | - Jonathon S Schofield
- Mechanical and Aerospace Engineering Department, University of California, Davis, Davis, CA, 95616, USA
| | - Ben Seiyon Lee
- Department of Statistics, George Mason University, Fairfax, VA, 22030, USA
| | - Siddhartha Sikdar
- Department of Bioengineering, George Mason University, Fairfax, VA, 22030, USA.
- Center for Adaptive Systems of Brain-Body Interactions, Fairfax, VA, 22030, USA.
| |
Collapse
|
14
|
Patwardhan S, Gladhill KA, Joiner WM, Schofield JS, Sikdar S. Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces. RESEARCH SQUARE 2023:rs.3.rs-2763325. [PMID: 37292730 PMCID: PMC10246101 DOI: 10.21203/rs.3.rs-2763325/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of a end effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.
Collapse
Affiliation(s)
| | - Keri Anne Gladhill
- Department of Psychology, George Mason University, Fairfax, VA, 22030, USA
| | - Wilsaan M. Joiner
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA, 95616, USA
| | - Jonathon S. Schofield
- Mechanical and Aerospace Engineering Department, University of California, Davis, Davis, CA, 95616, USA
| | - Siddhartha Sikdar
- Department of Bioengineering, George Mason University, Fairfax VA, 22030, USA
- Center for Adaptive Systems of Brain-Body Interactions, Fairfax VA, 22030, USA
| |
Collapse
|
15
|
Vu PP, Vaskov AK, Lee C, Jillala RR, Wallace DM, Davis AJ, Kung TA, Kemp SWP, Gates DH, Chestek CA, Cederna PS. Long-term upper-extremity prosthetic control using regenerative peripheral nerve interfaces and implanted EMG electrodes. J Neural Eng 2023; 20:026039. [PMID: 37023743 PMCID: PMC10126717 DOI: 10.1088/1741-2552/accb0c] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/23/2023] [Accepted: 04/06/2023] [Indexed: 04/08/2023]
Abstract
Objective.Extracting signals directly from the motor system poses challenges in obtaining both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To translate neural interfaces into the clinical space, these interfaces must provide consistent signals and prosthetic performance.Approach.Previously, we have demonstrated that the Regenerative Peripheral Nerve Interface (RPNI) is a biologically stable, bioamplifier of efferent motor action potentials. Here, we assessed the signal reliability from electrodes surgically implanted in RPNIs and residual innervated muscles in humans for long-term prosthetic control.Main results.RPNI signal quality, measured as signal-to-noise ratio, remained greater than 15 for up to 276 and 1054 d in participant 1 (P1), and participant 2 (P2), respectively. Electromyography from both RPNIs and residual muscles was used to decode finger and grasp movements. Though signal amplitude varied between sessions, P2 maintained real-time prosthetic performance above 94% accuracy for 604 d without recalibration. Additionally, P2 completed a real-world multi-sequence coffee task with 99% accuracy for 611 d without recalibration.Significance.This study demonstrates the potential of RPNIs and implanted EMG electrodes as a long-term interface for enhanced prosthetic control.
Collapse
Affiliation(s)
- Philip P Vu
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Section of Plastic Surgery, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Alex K Vaskov
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Section of Plastic Surgery, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Christina Lee
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Ritvik R Jillala
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Dylan M Wallace
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Alicia J Davis
- University of Michigan Hospital Orthotics & Prosthetics Center Ann Arbor, Ann Arbor, MI 48109, United States of America
| | - Theodore A Kung
- Section of Plastic Surgery, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Stephen W P Kemp
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Section of Plastic Surgery, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Deanna H Gates
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- School of Kinesiology, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Paul S Cederna
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Section of Plastic Surgery, University of Michigan, Ann Arbor, MI 48109, United States of America
| |
Collapse
|
16
|
Gehlhar R, Tucker M, Young AJ, Ames AD. A Review of Current State-of-the-Art Control Methods for Lower-Limb Powered Prostheses. ANNUAL REVIEWS IN CONTROL 2023; 55:142-164. [PMID: 37635763 PMCID: PMC10449377 DOI: 10.1016/j.arcontrol.2023.03.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge - the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user. In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: high-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.
Collapse
Affiliation(s)
- Rachel Gehlhar
- Department of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA
| | - Maegan Tucker
- Department of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA
| | - Aaron J Young
- Woodruff School of Mechanical Engineering, Georgia Institute of Technology, North Avenue, Atlanta, 30332, GA, USA
- Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, North Avenue, Atlanta, 30332, GA, USA
| | - Aaron D Ames
- Department of Mechanical and Civil Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA
- Department of Computing and Mathematical Sciences, California Institute of Technology, 1200 E. California Blvd., Pasadena, 91125, CA, USA
| |
Collapse
|
17
|
Farina D, Vujaklija I, Brånemark R, Bull AMJ, Dietl H, Graimann B, Hargrove LJ, Hoffmann KP, Huang HH, Ingvarsson T, Janusson HB, Kristjánsson K, Kuiken T, Micera S, Stieglitz T, Sturma A, Tyler D, Weir RFF, Aszmann OC. Toward higher-performance bionic limbs for wider clinical use. Nat Biomed Eng 2023; 7:473-485. [PMID: 34059810 DOI: 10.1038/s41551-021-00732-x] [Citation(s) in RCA: 94] [Impact Index Per Article: 94.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 04/01/2021] [Indexed: 12/19/2022]
Abstract
Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.
Collapse
Affiliation(s)
- Dario Farina
- Department of Bioengineering, Imperial College London, London, UK.
| | - Ivan Vujaklija
- Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
| | - Rickard Brånemark
- Center for Extreme Bionics, Biomechatronics Group, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anthony M J Bull
- Department of Bioengineering, Imperial College London, London, UK
| | - Hans Dietl
- Ottobock Products SE & Co. KGaA, Vienna, Austria
| | | | - Levi J Hargrove
- Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, USA
- Department of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
| | - Klaus-Peter Hoffmann
- Department of Medical Engineering & Neuroprosthetics, Fraunhofer-Institut für Biomedizinische Technik, Sulzbach, Germany
| | - He Helen Huang
- NCSU/UNC Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC, USA
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thorvaldur Ingvarsson
- Department of Research and Development, Össur Iceland, Reykjavík, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Hilmar Bragi Janusson
- School of Engineering and Natural Sciences, University of Iceland, Reykjavík, Iceland
| | | | - Todd Kuiken
- Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, USA
- Department of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
| | - Silvestro Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pontedera, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pontedera, Italy
- Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, BrainLinks-BrainTools Center and Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
| | - Agnes Sturma
- Department of Bioengineering, Imperial College London, London, UK
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic and Reconstructive Surgery, Medical University of Vienna, Vienna, Austria
| | - Dustin Tyler
- Case School of Engineering, Case Western Reserve University, Cleveland, OH, USA
- Louis Stokes Veterans Affairs Medical Centre, Cleveland, OH, USA
| | - Richard F Ff Weir
- Biomechatronics Development Laboratory, Bioengineering Department, University of Colorado Denver and VA Eastern Colorado Healthcare System, Aurora, CO, USA
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic and Reconstructive Surgery, Medical University of Vienna, Vienna, Austria
| |
Collapse
|
18
|
Pogarasteanu ME, Moga M, Barbilian A, Avram G, Dascalu M, Franti E, Gheorghiu N, Moldovan C, Rusu E, Adam R, Orban C. The Role of Fascial Tissue Layer in Electric Signal Transmission from the Forearm Musculature to the Cutaneous Layer as a Possibility for Increased Signal Strength in Myoelectric Forearm Exoprosthesis Development. Bioengineering (Basel) 2023; 10:bioengineering10030319. [PMID: 36978710 PMCID: PMC10044912 DOI: 10.3390/bioengineering10030319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/13/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Myoelectric exoprostheses serve to aid in the everyday activities of patients with forearm or hand amputations. While electrical signals are known key factors controlling exoprosthesis, little is known about how we can improve their transmission strength from the forearm muscles as to obtain better sEMG. The purpose of this study is to evaluate the role of the forearm fascial layer in transmitting myoelectrical current. We examined the sEMG signals in three individual muscles, each from six healthy forearms (Group 1) and six amputation stumps (Group 2), along with their complete biometric characteristics. Following the tests, one patient underwent a circumferential osteoneuromuscular stump revision surgery (CONM) that also involved partial removal of fascia and subcutaneous fat in the amputation stump, with re-testing after complete healing. In group 1, we obtained a stronger sEMG signal than in Group 2. In the CONM case, after surgery, the patient’s data suggest that the removal of fascia, alongside the fibrotic and subcutaneous fat tissue, generates a stronger sEMG signal. Therefore, a reduction in the fascial layer, especially if accompanied by a reduction of the subcutaneous fat layer may prove significant for improving the strength of sEMG signals used in the control of modern exoprosthetics.
Collapse
Affiliation(s)
- Mark-Edward Pogarasteanu
- Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 8 Eroii Sanitari Boulevard, 050474 Bucharest, Romania
- Department of Orthopaedics and Trauma Surgery, “Dr. Carol Davila” Central Military Emergency University Hospital, 010242 Bucharest, Romania
| | - Marius Moga
- Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 8 Eroii Sanitari Boulevard, 050474 Bucharest, Romania
- Department of Orthopaedics and Trauma Surgery, “Dr. Carol Davila” Central Military Emergency University Hospital, 010242 Bucharest, Romania
| | - Adrian Barbilian
- Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 8 Eroii Sanitari Boulevard, 050474 Bucharest, Romania
- Department of Orthopaedics and Trauma Surgery, “Dr. Carol Davila” Central Military Emergency University Hospital, 010242 Bucharest, Romania
| | - George Avram
- Department of Orthopaedics and Trauma Surgery, “Dr. Carol Davila” Central Military Emergency University Hospital, 010242 Bucharest, Romania
| | - Monica Dascalu
- Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania
- Center for New Electronic Architecture, Romanian Academy Center for Artificial Intelligence, 13 September Blulevard, 050711 Bucharest, Romania
| | - Eduard Franti
- Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania
- Center for New Electronic Architecture, Romanian Academy Center for Artificial Intelligence, 13 September Blulevard, 050711 Bucharest, Romania
- Microsystems in Biomedical and Environmental Applications Laboratory, National Institute for Research and Development in Microtechnology, 126A Erou Iancu Nicolae Street, 077190 Bucharest, Romania
| | - Nicolae Gheorghiu
- Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 8 Eroii Sanitari Boulevard, 050474 Bucharest, Romania
- Department of Orthopedics and Traumatology, Elias Emergency University Hospital, 011461 Bucharest, Romania
| | - Cosmin Moldovan
- Department of Medical-Clinical Disciplines, Faculty of Medicine, “Titu Maiorescu” University of Bucharest, 031593 Bucharest, Romania
- Department of General Surgery, Witting Clinical Hospital, 010243 Bucharest, Romania
- Correspondence: (C.M.); (R.A.); Tel.: +40-7-2350-4207 (C.M.); +40-7-4003-8744 (R.A.)
| | - Elena Rusu
- Department of Preclinic Disciplines, Faculty of Medicine, “Titu Maiorescu” University of Bucharest, 031593 Bucharest, Romania
| | - Razvan Adam
- Department of Orthopedics and Traumatology, Elias Emergency University Hospital, 011461 Bucharest, Romania
- Department of First Aid and Disaster Medicine, Faculty of Medicine, “Titu Maiorescu” University of Bucharest, 040051 Bucharest, Romania
- Correspondence: (C.M.); (R.A.); Tel.: +40-7-2350-4207 (C.M.); +40-7-4003-8744 (R.A.)
| | - Carmen Orban
- Department of Anesthesia and Intensive Care, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania
| |
Collapse
|
19
|
Zheng Z, Wu Z, Zhao R, Ni Y, Jing X, Gao S. A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications. BIOSENSORS 2022; 12:bios12070516. [PMID: 35884319 PMCID: PMC9313012 DOI: 10.3390/bios12070516] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/06/2022] [Accepted: 07/09/2022] [Indexed: 11/23/2022]
Abstract
Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.
Collapse
Affiliation(s)
| | | | | | | | | | - Shuo Gao
- Correspondence: ; Tel.: +86-18600737330
| |
Collapse
|
20
|
Gherardini M, Sturma A, Boesendorfer A, Ianniciello V, Mannini A, Aszmann OC, Cipriani C. Feasibility Study on Disentangling Muscle Movements in TMR Patients Through a Myokinetic Control Interface for the Control of Artificial Hands. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3181748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Marta Gherardini
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera, PI, Italy
| | - Agnes Sturma
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Anna Boesendorfer
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | | | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Firenze, Italy
| | - Oskar C. Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | | |
Collapse
|
21
|
Patwardhan S, Schofield J, Joiner WM, Sikdar S. Sonomyography shows feasibility as a tool to quantify joint movement at the muscle level. IEEE Int Conf Rehabil Robot 2022; 2022:1-5. [PMID: 36176162 PMCID: PMC9806856 DOI: 10.1109/icorr55369.2022.9896582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Several methods have been used to quantify human movement at different levels, from coordinated multi joint movements to those taking place at the single muscle level. These methods are developed either in order to allow us to interact with computers and machines, or to use such technologies for aiding rehabilitation among those with mobility impairments or movement disorders. Human machine interfaces typically rely on some existing human movement ability and measure it using motion tracking or inertial measurement units, while the rehabilitation applications may require us to measure human motor intent. Surface or implanted electrodes, electromyography, electroencephalography, and brain computer interfaces are beneficial in this regard, but have their own shortcomings. We have previously shown feasibility of using ultrasound imaging (Sonomyography) to infer human motor intent and allow users to control external biomechatronic devices such as prosthetics. Here, we asked users to freely move their hand in three different movement patterns, measuring their actual joint angles and passively computing their Sonomyographic output signal. We found a high correlation between these two signals, demonstrating that the Sonomyography signal is not only user-controlled and stable, but it is closely linked with the user's actual movement level. These results could help design wearable rehabilitation or human computer interaction devices based on Sonomyography to decode human motor intent.
Collapse
Affiliation(s)
| | - Jonathon Schofield
- Mechanical and Aerospace Engineering Department, University of California, Davis, USA
| | - Wilsaan M. Joiner
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, CA, USA
| | - Siddhartha Sikdar
- Department of Bioengineering, George Mason University, Fairfax VA, USA,Center for Adaptive Systems of Brain-Body Interactions, Fairfax, VA
| |
Collapse
|
22
|
Becerra-Fajardo L, Krob MO, Minguillon J, Rodrigues C, Welsch C, Tudela-Pi M, Comerma A, Oliveira Barroso F, Schneider A, Ivorra A. Floating EMG sensors and stimulators wirelessly powered and operated by volume conduction for networked neuroprosthetics. J Neuroeng Rehabil 2022; 19:57. [PMID: 35672857 PMCID: PMC9171952 DOI: 10.1186/s12984-022-01033-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/19/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Implantable neuroprostheses consisting of a central electronic unit wired to electrodes benefit thousands of patients worldwide. However, they present limitations that restrict their use. Those limitations, which are more adverse in motor neuroprostheses, mostly arise from their bulkiness and the need to perform complex surgical implantation procedures. Alternatively, it has been proposed the development of distributed networks of intramuscular wireless microsensors and microstimulators that communicate with external systems for analyzing neuromuscular activity and performing stimulation or controlling external devices. This paradigm requires the development of miniaturized implants that can be wirelessly powered and operated by an external system. To accomplish this, we propose a wireless power transfer (WPT) and communications approach based on volume conduction of innocuous high frequency (HF) current bursts. The currents are applied through external textile electrodes and are collected by the wireless devices through two electrodes for powering and bidirectional digital communications. As these devices do not require bulky components for obtaining power, they may have a flexible threadlike conformation, facilitating deep implantation by injection. METHODS We report the design and evaluation of advanced prototypes based on the above approach. The system consists of an external unit, floating semi-implantable devices for sensing and stimulation, and a bidirectional communications protocol. The devices are intended for their future use in acute human trials to demonstrate the distributed paradigm. The technology is assayed in vitro using an agar phantom, and in vivo in hindlimbs of anesthetized rabbits. RESULTS The semi-implantable devices were able to power and bidirectionally communicate with the external unit. Using 13 commands modulated in innocuous 3 MHz HF current bursts, the external unit configured the sensing and stimulation parameters, and controlled their execution. Raw EMG was successfully acquired by the wireless devices at 1 ksps. CONCLUSIONS The demonstrated approach overcomes key limitations of existing neuroprostheses, paving the way to the development of distributed flexible threadlike sensors and stimulators. To the best of our knowledge, these devices are the first based on WPT by volume conduction that can work as EMG sensors and as electrical stimulators in a network of wireless devices.
Collapse
Affiliation(s)
- Laura Becerra-Fajardo
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain.
| | - Marc Oliver Krob
- Fraunhofer Institute for Biomedical Engineering IBMT, 66280, Sulzbach, Germany
| | - Jesus Minguillon
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain
- Research Centre for Information and Communications Technologies, University of Granada, 18014, Granada, Spain
- Department of Signal Theory, Telematics and Communications, University of Granada, 18014, Granada, Spain
| | - Camila Rodrigues
- Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002, Madrid, Spain
- Electronics, Automation and Communications Department, ICAI School of Engineering, Comillas Pontifical University, 28015, Madrid, Spain
| | - Christine Welsch
- Fraunhofer Institute for Biomedical Engineering IBMT, 66280, Sulzbach, Germany
| | - Marc Tudela-Pi
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain
| | - Albert Comerma
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain
| | - Filipe Oliveira Barroso
- Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002, Madrid, Spain
| | - Andreas Schneider
- Fraunhofer Institute for Biomedical Engineering IBMT, 66280, Sulzbach, Germany
| | - Antoni Ivorra
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08018, Barcelona, Spain
- Serra Húnter Fellow Programme, Universitat Pompeu Fabra, 08018, Barcelona, Spain
| |
Collapse
|
23
|
Gstoettner C, Festin C, Prahm C, Bergmeister KD, Salminger S, Sturma A, Hofer C, Russold MF, Howard CL, McDonnall D, Farina D, Aszmann OC. Feasibility of a Wireless Implantable Multi-electrode System for High-bandwidth Prosthetic Interfacing: Animal and Cadaver Study. Clin Orthop Relat Res 2022; 480:1191-1204. [PMID: 35202032 PMCID: PMC9263498 DOI: 10.1097/corr.0000000000002135] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 01/19/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Currently used prosthetic solutions in upper extremity amputation have limited functionality, owing to low information transfer rates of neuromuscular interfacing. Although surgical innovations have expanded the functional potential of the residual limb, available interfaces are inefficacious in translating this potential into improved prosthetic control. There is currently no implantable solution for functional interfacing in extremity amputation which offers long-term stability, high information transfer rates, and is applicable for all levels of limb loss. In this study, we presented a novel neuromuscular implant, the the Myoelectric Implantable Recording Array (MIRA). To our knowledge, it is the first fully implantable system for prosthetic interfacing with a large channel count, comprising 32 intramuscular electrodes. QUESTIONS/PURPOSES The purpose of this study was to evaluate the MIRA in terms of biocompatibility, functionality, and feasibility of implantation to lay the foundations for clinical application. This was achieved through small- and large-animal studies as well as test surgeries in a human cadaver. METHODS We evaluated the biocompatibility of the system's intramuscular electromyography (EMG) leads in a rabbit model. Ten leads as well as 10 pieces of a biologically inert control material were implanted into the paravertebral muscles of four animals. After a 3-month implantation, tissue samples were taken and histopathological assessment performed. The probes were scored according to a protocol for the assessment of the foreign body response, with primary endpoints being inflammation score, tissue response score, and capsule thickness in µm. In a second study, chronic functionality of the full system was evaluated in large animals. The MIRA was implanted into the shoulder region of six dogs and three sheep, with intramuscular leads distributed across agonist and antagonist muscles of shoulder flexion. During the observation period, regular EMG measurements were performed. The implants were removed after 5 to 6 months except for one animal, which retained the implant for prolonged observation. Primary endpoints of the large-animal study were mechanical stability, telemetric capability, and EMG signal quality. A final study involved the development of test surgeries in a fresh human cadaver, with the goal to determine feasibility to implant relevant target muscles for prosthetic control at all levels of major upper limb amputation. RESULTS Evaluation of the foreign body reaction revealed favorable biocompatibility and a low-grade tissue response in the rabbit study. No differences regarding inflammation score (EMG 4.60 ± 0.97 [95% CI 4.00 to 5.20] versus control 4.20 ± 1.48 [95% CI 3.29 to 5.11]; p = 0.51), tissue response score (EMG 4.00 ± 0.82 [95% CI 3.49 to 4.51] versus control 4.00 ± 0.94 [95% CI 3.42 to 4.58]; p > 0.99), or thickness of capsule (EMG 19.00 ± 8.76 µm [95% CI 13.57 to 24.43] versus control 29.00 ± 23.31 µm [95% CI 14.55 to 43.45]; p = 0.29) were found compared with the inert control article (high-density polyethylene) after 3 months of intramuscular implantation. Throughout long-term implantation of the MIRA in large animals, telemetric communication remained unrestricted in all specimens. Further, the implants retained the ability to record and transmit intramuscular EMG data in all animals except for two sheep where the implants became dislocated shortly after implantation. Electrode impedances remained stable and below 5 kΩ. Regarding EMG signal quality, there was little crosstalk between muscles and overall average signal-to-noise ratio was 22.2 ± 6.2 dB. During the test surgeries, we found that it was possible to implant the MIRA at all major amputation levels of the upper limb in a human cadaver (the transradial, transhumeral, and glenohumeral levels). For each level, it was possible to place the central unit in a biomechanically stable environment to provide unhindered telemetry, while reaching the relevant target muscles for prosthetic control. At only the glenohumeral level, it was not possible to reach the teres major and latissimus dorsi muscles, which would require longer lead lengths. CONCLUSION As assessed in a combination of animal model and cadaver research, the MIRA shows promise for clinical research in patients with limb amputation, where it may be employed for all levels of major upper limb amputation to provide long-term stable intramuscular EMG transmission. CLINICAL RELEVANCE In our study, the MIRA provided high-bandwidth prosthetic interfacing through intramuscular electrode sites. Its high number of individual EMG channels may be combined with signal decoding algorithms for accessing spinal motor neuron activity after targeted muscle reinnervation, thus providing numerous degrees of freedom. Together with recent innovations in amputation surgery, the MIRA might enable improved control approaches for upper limb amputees, particularly for patients with above-elbow amputation where the mismatch between available control signals and necessary degrees of freedom for prosthetic control is highest.
Collapse
Affiliation(s)
- Clemens Gstoettner
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Christopher Festin
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Cosima Prahm
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- BG Trauma Clinic, Eberhard Karls University, Department for Plastic and Reconstructive Surgery, Tübingen, Germany
| | - Konstantin D. Bergmeister
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Karl Landsteiner University of Health Sciences, Krems, Austria
- Department of Plastic, Aesthetic and Reconstructive Surgery, University Hospital St. Poelten, St. Poelten, Austria
| | - Stefan Salminger
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Agnes Sturma
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Bioengineering, Imperial College London, London, UK
| | - Christian Hofer
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Otto Bock Healthcare Products GmbH, Vienna, Austria
| | | | | | | | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK
| | - Oskar C. Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| |
Collapse
|
24
|
Luu DK, Nguyen AT, Jiang M, Drealan MW, Xu J, Wu T, Tam WK, Zhao W, Lim BZH, Overstreet CK, Zhao Q, Cheng J, Keefer EW, Yang Z. Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface. IEEE Trans Biomed Eng 2022; 69:3051-3063. [PMID: 35302937 DOI: 10.1109/tbme.2022.3160618] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines. METHODS Here we present a neuroprosthetic system to demonstrate that principle by employing an artificial intelligence (AI) agent to translate the amputees movement intent through a peripheral nerve interface. The AI agent is designed based on the recurrent neural network (RNN) and could simultaneously decode six degree-of-freedom (DOF) from multichannel nerve data in real-time. The decoder's performance is characterized in motor decoding experiments with three human amputees. RESULTS First, we show the AI agent enables amputees to intuitively control a prosthetic hand with individual finger and wrist movements up to 97-98% accuracy. Second, we demonstrate the AI agent's real-time performance by measuring the reaction time and information throughput in a hand gesture matching task. Third, we investigate the AI agent's long-term uses and show the decoder's robust predictive performance over a 16-month implant duration. Conclusion & significance: Our study demonstrates the potential of AI-enabled nerve technology, underling the next generation of dexterous and intuitive prosthetic hands.
Collapse
|
25
|
Mablekos-Alexiou A, Kontogiannopoulos S, Bertos GA, Papadopoulos E. A biomechatronics-based EPP topology for upper-limb prosthesis control: Modeling & benchtop prototype. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
|
26
|
Pasluosta C, Kiele P, Čvančara P, Micera S, Aszmann OC, Stieglitz T. Bidirectional bionic limbs: a perspective bridging technology and physiology. J Neural Eng 2022; 19. [PMID: 35132954 DOI: 10.1088/1741-2552/ac4bff] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 01/17/2022] [Indexed: 11/11/2022]
Abstract
Precise control of bionic limbs relies on robust decoding of motor commands from nerves or muscles signals and sensory feedback from artificial limbs to the nervous system by interfacing the afferent nerve pathways. Implantable devices for bidirectional communication with bionic limbs have been developed in parallel with research on physiological alterations caused by an amputation. In this perspective article, we question whether increasing our effort on bridging these technologies with a deeper understanding of amputation pathophysiology and human motor control may help to overcome pressing stalls in the next generation of bionic limbs.
Collapse
Affiliation(s)
- C Pasluosta
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
| | - P Kiele
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
| | - P Čvančara
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.,BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - S Micera
- School of Engineering, École Polytechnique Fédérale de Lausanne, Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, Lausanne, Switzerland.,The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - O C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna; Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of Vienna, Vienna, Austria
| | - T Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.,Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.,BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| |
Collapse
|
27
|
Bumbaširević M, Matić S, Palibrk T, Glišović Jovanović I, Mitković M, Lesić A. Mangled extremity- Modern concepts in treatment. Injury 2021; 52:3555-3560. [PMID: 33766434 DOI: 10.1016/j.injury.2021.03.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/09/2021] [Indexed: 02/02/2023]
Abstract
A mangled extremity is the most devastating limb injury and presents a challenge for the orthopedic surgeon. There are two main treatment options, reconstruction or amputation, but sometimes indications for either are not clear. There are many pro and contra arguments for both options. To make the decision easier numerous score systems have been introduced, but the final decision is based on the judgment and experience of the treating surgeon. Early extremity reconstruction appears to give better results than delayed or late reconstruction and should be the treatment of choice where possible. The goal in reconstruction of a lower extremity is to restore and maintain balance and ambulation, while restoration of an upper extremity's numerous functions is more demanding. In this paper the authors describe and suggest treatment approaches in patients with a severely mangled extremity, including assessment and treatment of all injured tissues, using defined protocols, with special attention to bone stabilization, revascularization, soft-tissue coverage and nerve reconstruction. These have a great impact on the outcome and function of the injured extremity. Rehabilitation and return to the preinjury level is slow and sometimes uncertain.
Collapse
Affiliation(s)
- M Bumbaširević
- School of Medicine, University of Belgrade; Clinic for orthopedic surgery and traumatology, Clinical Centre of Serbia; Serbian Academy of Sciences and Arts, Belgrade
| | - S Matić
- School of Medicine, University of Belgrade; Clinic for orthopedic surgery and traumatology, Clinical Centre of Serbia
| | - T Palibrk
- School of Medicine, University of Belgrade; Clinic for orthopedic surgery and traumatology, Clinical Centre of Serbia
| | | | - M Mitković
- Clinic for orthopedic surgery and traumatology, Clinical Centre Nis
| | - A Lesić
- School of Medicine, University of Belgrade; Clinic for orthopedic surgery and traumatology, Clinical Centre of Serbia
| |
Collapse
|
28
|
Gherardini M, Mannini A, Cipriani C. Optimal Spatial Sensor Design for Magnetic Tracking in a Myokinetic Control Interface. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 211:106407. [PMID: 34537492 DOI: 10.1016/j.cmpb.2021.106407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 09/03/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVES Magnetic tracking involves the use of magnetic sensors to localize one or more magnetic objectives, in those applications in which a free line-of-sight between them and the operator is hampered. We applied this concept to prosthetic hands, which could be controlled by tracking permanent magnets implanted in the forearm muscles of amputees (the myokinetic control interface). Concerning the system design, the definition of a sensor distribution which maximizes the information, while minimizing the computational cost of localization, is still an open problem. We present a simple yet effective strategy to define an optimal sensor set for tracking multiple magnets, which we called the Peaks method. METHODS We simulated a proximal amputation using a 3D CAD model of a human forearm, and the implantation of 11 magnets in the residual muscles. The Peaks method was applied to select a subset of sensors from an initial grid of 480 elements. The approach involves setting an appropriate threshold to select those sensors associated with the peaks in the magnetic flux density and its gradient distributions. Selected sensors were used to track the magnets during muscle contraction. For validating our strategy, an alternative method based on state-of-the-art solutions was implemented. We finally proposed a calibration phase to customize the sensor distribution on the specific patient's anatomy. RESULTS 80 sensors were selected with the Peaks method, and 101 with the alternative one. A localization accuracy below 0.22 mm and 1.86° for position and orientation, respectively, was always achieved. Unlike alternative methods from the literature, neither iterative or analytical solution, nor a-priori knowledge on the magnet positions or trajectories were required, and yet the outcomes achieved with the two strategies proved statistically comparable. The calibration phase proved useful to adapt the sensors to the patient's stump and to increase the signal-to-noise ratio against intrinsic noise. CONCLUSIONS We demonstrated an efficient and general solution for solving the design optimization problem (i.e. identifying an optimal sensor set) and reducing the computational cost of localization. The optimal sensor distribution mirrors the field shape traced by the magnets on the sensing surface, being an intuitive and fast way of achieving the same results of more complex and application-specific methods. Several applications in the (bio)medical field involving magnetic tracking will benefit from the outcomes of this work.
Collapse
Affiliation(s)
- Marta Gherardini
- The Biorobotics Institute Scuola Superiore Sant'Anna, 56127 Pisa, Italy; Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
| | - Andrea Mannini
- The Biorobotics Institute Scuola Superiore Sant'Anna, 56127 Pisa, Italy; Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy; IRCCS Fondazione Don Carlo Gnocchi, Firenze, Italy
| | - Christian Cipriani
- The Biorobotics Institute Scuola Superiore Sant'Anna, 56127 Pisa, Italy; Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| |
Collapse
|
29
|
Segil JL, Lukyanenko P, Lambrecht J, Weir RFF, Tyler D. Comparison of Myoelectric Control Schemes for Simultaneous Hand and Wrist Movement using Chronically Implanted Electromyography: A Case Series . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:6224-6230. [PMID: 34892537 PMCID: PMC10964936 DOI: 10.1109/embc46164.2021.9630845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE A current biomedical engineering challenge is the development of a system that allows fluid control of multi-functional prosthetic devices through a human-machine interface. Here we probe this challenge by studying two subjects with trans-radial limb loss as they control a virtual hand and wrist system using 6 or 8 chronically implanted intramuscular electromyographic (iEMG) signals. The subjects successfully controlled a 4, 5, and 6 Degrees of Freedom (DoF's) virtual hand and wrist systems to perform a target matching task. APPROACH Two control systems were evaluated where one tied EMG features directly to movement directions (Direct Control) and the other method determines user intent in the context of prior training data (Linear Interpolation). MAIN RESULTS Subjects successfully matched most targets with both controllers but differences were seen as the complexity of the virtual limb system increased. The Direct Control method encountered difficulty due to crosstalk at higher DoF's. The Linear Interpolation method reduced crosstalk effects and outperformed Direct Control at higher DoF's. This work also studied the use of the Postural Control Algorithm to control the hand postures simultaneously with wrist degrees of freedom. SIGNIFICANCE This work presents preliminary evidence that the PC algorithm can be used in conjunction with wrist control, that Direct Control with iEMG signals allows stable 4-DoF control, and that EMG pre-processing using the Linear Interpolation method can improve performance at 5 and 6-DoF's.
Collapse
|
30
|
Yu T, Akhmadeev K, Carpentier EL, Aoustin Y, Farina D. Highly accurate real-time decomposition of single channel intramuscular EMG. IEEE Trans Biomed Eng 2021; 69:746-757. [PMID: 34388089 DOI: 10.1109/tbme.2021.3104621] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Real-time intramuscular electromyography (iEMG) decomposition, as an identification procedure of individual motor neuron (MN) discharge timings from a streaming iEMG recording, has the potential to be used in human-machine interfacing. However, for these applications, the decomposition accuracy and speed of current approaches need to be improved. METHODS In our previous work, a real-time decomposition algorithm based on a Hidden Markov Model of EMG, using GPU-implemented Bayesian filter to estimate the spike trains of motor units (MU) and their action potentials (MUAPs), was proposed. In this paper, a substantially extended version of this algorithm that boosts the accuracy while maintaining real-time implementation, is introduced. Specifically, multiple heuristics that aim at resolving the problems leading to performance degradation, are applied to the original model. In addition, the recursive maximum likelihood (RML) estimator previously used to estimate the statistical parameters of the spike trains, is replaced by a linear regression (LR) estimator, which is computationally more efficient, in order to ensure real-time decomposition with the new heuristics. RESULTS The algorithm was validated using twenty-one experimental iEMG signals acquired from the tibialis anterior muscle of five subjects by fine wire electrodes. All signals were decomposed in real time. The decomposition accuracy depended on the level of muscle activation and was >90% when less than 10 MUs were identified, substantially exceeding previous real-time results. CONCLUSION Single channel iEMG signals can be very accurately decomposed in real time with the proposed algorithm. SIGNIFICANCE The proposed highly accurate algorithm for single-channel iEMG decomposition has the potential of providing neural information on motor tasks for human interfacing.
Collapse
|
31
|
Montero J, Clemente F, Cipriani C. Feasibility of generating 90 Hz vibrations in remote implanted magnets. Sci Rep 2021; 11:15456. [PMID: 34326398 PMCID: PMC8322332 DOI: 10.1038/s41598-021-94240-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Accepted: 06/29/2021] [Indexed: 11/17/2022] Open
Abstract
Limb amputation not only reduces the motor abilities of an individual, but also destroys afferent channels that convey essential sensory information to the brain. Significant efforts have been made in the area of upper limb prosthetics to restore sensory feedback, through the stimulation of residual sensory elements. Most of the past research focused on the replacement of tactile functions. On the other hand, the difficulties in eliciting proprioceptive sensations using either haptic or (neural) electrical stimulation, has limited researchers to rely on sensory substitution. Here we propose the myokinetic stimulation interface, that aims at restoring natural proprioceptive sensations by exploiting the so-called tendon illusion, elicited through the vibration of magnets implanted inside residual muscles. We present a prototype which exploits 12 electromagnetic coils to vibrate up to four magnets implanted in a forearm mockup. The results demonstrated that it is possible to generate highly directional and frequency-selective vibrations. The system proved capable of activating a single magnet, out of many. Hence, this interface constitutes a promising approach to restore naturally perceived proprioception after an amputation. Indeed, by implanting several magnets in independent muscles, it would be possible to restore proprioceptive sensations perceived as coming from single digits.
Collapse
Affiliation(s)
- Jordan Montero
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
| | - Francesco Clemente
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
| | - Christian Cipriani
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy.
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy.
| |
Collapse
|
32
|
Fleming A, Stafford N, Huang S, Hu X, Ferris DP, Huang H(H. Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions. J Neural Eng 2021; 18:10.1088/1741-2552/ac1176. [PMID: 34229307 PMCID: PMC8694273 DOI: 10.1088/1741-2552/ac1176] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/06/2021] [Indexed: 11/16/2022]
Abstract
Objective.Advanced robotic lower limb prostheses are mainly controlled autonomously. Although the existing control can assist cyclic movements during locomotion of amputee users, the function of these modern devices is still limited due to the lack of neuromuscular control (i.e. control based on human efferent neural signals from the central nervous system to peripheral muscles for movement production). Neuromuscular control signals can be recorded from muscles, called electromyographic (EMG) or myoelectric signals. In fact, using EMG signals for robotic lower limb prostheses control has been an emerging research topic in the field for the past decade to address novel prosthesis functionality and adaptability to different environments and task contexts. The objective of this paper is to review robotic lower limb Prosthesis control via EMG signals recorded from residual muscles in individuals with lower limb amputations.Approach.We performed a literature review on surgical techniques for enhanced EMG interfaces, EMG sensors, decoding algorithms, and control paradigms for robotic lower limb prostheses.Main results.This review highlights the promise of EMG control for enabling new functionalities in robotic lower limb prostheses, as well as the existing challenges, knowledge gaps, and opportunities on this research topic from human motor control and clinical practice perspectives.Significance.This review may guide the future collaborations among researchers in neuromechanics, neural engineering, assistive technologies, and amputee clinics in order to build and translate true bionic lower limbs to individuals with lower limb amputations for improved motor function.
Collapse
Affiliation(s)
- Aaron Fleming
- Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, United States of America
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America
- Equal contribution as the first author
| | - Nicole Stafford
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, United States of America
- Equal contribution as the first author
| | - Stephanie Huang
- Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, United States of America
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America
| | - Xiaogang Hu
- Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, United States of America
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, United States of America
| | - He (Helen) Huang
- Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, United States of America
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States of America
| |
Collapse
|
33
|
Karczewski AM, Dingle AM, Poore SO. The Need to Work Arm in Arm: Calling for Collaboration in Delivering Neuroprosthetic Limb Replacements. Front Neurorobot 2021; 15:711028. [PMID: 34366820 PMCID: PMC8334559 DOI: 10.3389/fnbot.2021.711028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 06/22/2021] [Indexed: 11/21/2022] Open
Abstract
Over the last few decades there has been a push to enhance the use of advanced prosthetics within the fields of biomedical engineering, neuroscience, and surgery. Through the development of peripheral neural interfaces and invasive electrodes, an individual's own nervous system can be used to control a prosthesis. With novel improvements in neural recording and signal decoding, this intimate communication has paved the way for bidirectional and intuitive control of prostheses. While various collaborations between engineers and surgeons have led to considerable success with motor control and pain management, it has been significantly more challenging to restore sensation. Many of the existing peripheral neural interfaces have demonstrated success in one of these modalities; however, none are currently able to fully restore limb function. Though this is in part due to the complexity of the human somatosensory system and stability of bioelectronics, the fragmentary and as-yet uncoordinated nature of the neuroprosthetic industry further complicates this advancement. In this review, we provide a comprehensive overview of the current field of neuroprosthetics and explore potential strategies to address its unique challenges. These include exploration of electrodes, surgical techniques, control methods, and prosthetic technology. Additionally, we propose a new approach to optimizing prosthetic limb function and facilitating clinical application by capitalizing on available resources. It is incumbent upon academia and industry to encourage collaboration and utilization of different peripheral neural interfaces in combination with each other to create versatile limbs that not only improve function but quality of life. Despite the rapidly evolving technology, if the field continues to work in divided "silos," we will delay achieving the critical, valuable outcome: creating a prosthetic limb that is right for the patient and positively affects their life.
Collapse
Affiliation(s)
| | - Aaron M. Dingle
- Division of Plastic Surgery, Department of Surgery, University of Wisconsin–Madison, Madison, WI, United States
| | | |
Collapse
|
34
|
Sanchez M, Ruız A, Cruz-Ortiz D, Salgado I, Ballesteros M, Chairez I. Discrete event-driven control of an active orthosis regulated by electromyographic signals for Canis lupus familiaris. INTEL SERV ROBOT 2021. [DOI: 10.1007/s11370-021-00371-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
35
|
Hoellwarth JS, Tetsworth K, Rozbruch SR, Handal MB, Coughlan A, Al Muderis M. Osseointegration for Amputees: Current Implants, Techniques, and Future Directions. JBJS Rev 2021; 8:e0043. [PMID: 32224634 PMCID: PMC7161721 DOI: 10.2106/jbjs.rvw.19.00043] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Osseointegrated prostheses provide a rehabilitation option for amputees offering greater mobility, better satisfaction, and higher use than traditional socket prostheses. There are several different osseointegrated implant designs, surgical techniques, and rehabilitation protocols with their own strengths and limitations. The 2 most prominent risks, infection and periprosthetic fracture, do not seem unacceptably frequent or insurmountable. Proximal amputations or situations leading to reduced mobility are exceptionally infrequent. Osseointegrated implants can be attached to advanced sensory and motor prostheses.
Collapse
Affiliation(s)
- Jason Shih Hoellwarth
- Department of Orthopaedic Surgery, Macquarie University Hospital, Sydney, New South Wales, Australia
| | - Kevin Tetsworth
- Department of Orthopaedics, The Royal Brisbane Hospital, Brisbane, Victoria, Australia
| | - S Robert Rozbruch
- Limb Lengthening and Complex Reconstruction Service, Hospital for Special Surgery, New York, NY
| | - M Brianne Handal
- Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania
| | - Adam Coughlan
- Department of Orthopaedics, The Royal Brisbane Hospital, Brisbane, Victoria, Australia
| | - Munjed Al Muderis
- Department of Orthopaedic Surgery, Macquarie University Hospital, Sydney, New South Wales, Australia
| |
Collapse
|
36
|
Lukyanenko P, Dewald HA, Lambrecht J, Kirsch RF, Tyler DJ, Williams MR. Stable, simultaneous and proportional 4-DoF prosthetic hand control via synergy-inspired linear interpolation: a case series. J Neuroeng Rehabil 2021; 18:50. [PMID: 33736656 PMCID: PMC7977328 DOI: 10.1186/s12984-021-00833-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 02/02/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Current commercial prosthetic hand controllers limit patients' ability to fully engage high Degree-of-Freedom (DoF) prosthetic hands. Available feedforward controllers rely on large training data sets for controller setup and a need for recalibration upon prosthesis donning. Recently, an intuitive, proportional, simultaneous, regression-based 3-DoF controller remained stable for several months without retraining by combining chronically implanted electromyography (ciEMG) electrodes with a K-Nearest-Neighbor (KNN) mapping technique. The training dataset requirements for simultaneous KNN controllers increase exponentially with DoF, limiting the realistic development of KNN controllers in more than three DoF. We hypothesize that a controller combining linear interpolation, the muscle synergy framework, and a sufficient number of ciEMG channels (at least two per DoF), can allow stable, high-DoF control. METHODS Two trans-radial amputee subjects, S6 and S8, were implanted with percutaneously interfaced bipolar intramuscular electrodes. At the time of the study, S6 and S8 had 6 and 8 bipolar EMG electrodes, respectively. A Virtual Reality (VR) system guided users through single and paired training movements in one 3-DoF and four different 4-DoF cases. A linear model of user activity was built by partitioning EMG feature space into regions bounded by vectors of steady state movement EMG patterns. The controller evaluated online EMG signals by linearly interpolating the movement class labels for surrounding trained EMG movements. This yields a simultaneous, continuous, intuitive, and proportional controller. Controllers were evaluated in 3-DoF and 4-DoF through a target-matching task in which subjects controlled a virtual hand to match 80 targets spanning the available movement space. Match Percentage, Time-To-Target, and Path Efficiency were evaluated over a 10-month period based on subject availability. RESULTS AND CONCLUSIONS In 3-DoF, S6 and S8 matched most targets and demonstrated stable control after 8 and 10 months, respectively. In 4-DoF, both subjects initially found two of four 4-DoF controllers usable, matching most targets. S8 4-DoF controllers were stable, and showed improving trends over 7-9 months without retraining or at-home practice. S6 4-DoF controllers were unstable after 7 months without retraining. These results indicate that the performance of the controller proposed in this study may remain stable, or even improve, provided initial viability and a sufficient number of EMG channels. Overall, this study demonstrates a controller capable of stable, simultaneous, proportional, intuitive, and continuous control in 3-DoF for up to ten months and in 4-DoF for up to nine months without retraining or at-home use with minimal training times.
Collapse
Affiliation(s)
- Platon Lukyanenko
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA.,APT Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd., Mail Stop 151 W/APT, Cleveland, OH, 44106-1702, USA
| | - Hendrik Adriaan Dewald
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA.,Cleveland FES Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Boulevard, B-E210, Cleveland, OH, 44106-1702, USA
| | - Joris Lambrecht
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA.,Cleveland FES Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Boulevard, B-E210, Cleveland, OH, 44106-1702, USA
| | - Robert F Kirsch
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA.,Cleveland FES Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Boulevard, B-E210, Cleveland, OH, 44106-1702, USA
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA. .,Cleveland FES Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Boulevard, B-E210, Cleveland, OH, 44106-1702, USA. .,APT Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Blvd., Mail Stop 151 W/APT, Cleveland, OH, 44106-1702, USA.
| | - Matthew R Williams
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-1712, USA.,Cleveland FES Center, Louis Stokes Cleveland Veterans Affairs Medical Center, 10701 East Boulevard, B-E210, Cleveland, OH, 44106-1702, USA
| |
Collapse
|
37
|
Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges. SENSORS 2021; 21:s21062084. [PMID: 33809721 PMCID: PMC8002299 DOI: 10.3390/s21062084] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/05/2021] [Accepted: 03/11/2021] [Indexed: 11/17/2022]
Abstract
Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.
Collapse
|
38
|
Abstract
Upper limb amputations, ranging from transhumeral to partial hand, can be devastating for patients, their families, and society. Modern paradigm shifts have focused on reconstructive options after upper extremity limb loss, rather than considering the amputation an ablative procedure. Surgical advancements such as targeted muscle reinnervation and regenerative peripheral nerve interface, in combination with technological development of modern prosthetics, have expanded options for patients after amputation. In the near future, advances such as osseointegration, implantable myoelectric sensors, and implantable nerve cuffs may become more widely used and may expand the options for prosthetic integration, myoelectric signal detection, and restoration of sensation. This review summarizes the current advancements in surgical techniques and prosthetics for upper limb amputees. Cite this article: Bone Joint J 2021;103-B(3):430-439.
Collapse
Affiliation(s)
- Michael Geary
- Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute, Charlotte, North Carolina, USA
| | - Raymond Glenn Gaston
- Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute, Charlotte, North Carolina, USA.,Reconstructive Center for Lost Limbs, OrthoCarolina Hand Center, Charlotte, North Carolina, USA
| | - Bryan Loeffler
- Department of Orthopaedic Surgery, Atrium Health Musculoskeletal Institute, Charlotte, North Carolina, USA.,Reconstructive Center for Lost Limbs, OrthoCarolina Hand Center, Charlotte, North Carolina, USA
| |
Collapse
|
39
|
Milici S, Gherardini M, Clemente F, Masiero F, Sassu P, Cipriani C. The Myokinetic Control Interface: How Many Magnets Can be Implanted in an Amputated Forearm? Evidence From a Simulated Environment. IEEE Trans Neural Syst Rehabil Eng 2020; 28:2451-2458. [PMID: 32956064 DOI: 10.1109/tnsre.2020.3024960] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
We recently introduced the concept of a new human-machine interface (the myokinetic control interface) to control hand prostheses. The interface tracks muscle contractions via permanent magnets implanted in the muscles and magnetic field sensors hosted in the prosthetic socket. Previously we showed the feasibility of localizing several magnets in non-realistic workspaces. Here, aided by a 3D CAD model of the forearm, we computed the localization accuracy simulated for three different below-elbow amputation levels, following general guidelines identified in early work. To this aim we first identified the number of magnets that could fit and be tracked in a proximal (T1), middle (T2) and distal (T3) representative amputation, starting from 18, 20 and 23 eligible muscles, respectively. Then we ran a localization algorithm to estimate the poses of the magnets based on the sensor readings. A sensor selection strategy (from an initial grid of 840 sensors) was also implemented to optimize the computational cost of the localization process. Results showed that the localizer was able to accurately track up to 11 (T1), 13 (T2) and 19 (T3) magnetic markers (MMs) with an array of 154, 205 and 260 sensors, respectively. Localization errors lower than 7% the trajectory travelled by the magnets during muscle contraction were always achieved. This work not only answers the question: "how many magnets could be implanted in a forearm and successfully tracked with a the myokinetic control approach?", but also provides interesting insights for a wide range of bioengineering applications exploiting magnetic tracking.
Collapse
|
40
|
Nazeer H, Naseer N, Khan RA, Noori FM, Qureshi NK, Khan US, Khan MJ. Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis. J Neural Eng 2020; 17:056025. [DOI: 10.1088/1741-2552/abb417] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
|
41
|
Brinton MR, Barcikowski E, Davis T, Paskett M, George JA, Clark GA. Portable Take-Home System Enables Proportional Control and High-Resolution Data Logging With a Multi-Degree-of-Freedom Bionic Arm. Front Robot AI 2020; 7:559034. [PMID: 33501323 PMCID: PMC7805650 DOI: 10.3389/frobt.2020.559034] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 08/21/2020] [Indexed: 11/16/2022] Open
Abstract
This paper describes a portable, prosthetic control system and the first at-home use of a multi-degree-of-freedom, proportionally controlled bionic arm. The system uses a modified Kalman filter to provide 6 degree-of-freedom, real-time, proportional control. We describe (a) how the system trains motor control algorithms for use with an advanced bionic arm, and (b) the system's ability to record an unprecedented and comprehensive dataset of EMG, hand positions and force sensor values. Intact participants and a transradial amputee used the system to perform activities-of-daily-living, including bi-manual tasks, in the lab and at home. This technology enables at-home dexterous bionic arm use, and provides a high-temporal resolution description of daily use—essential information to determine clinical relevance and improve future research for advanced bionic arms.
Collapse
Affiliation(s)
- Mark R Brinton
- Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
| | | | - Tyler Davis
- Neurosurgery, University of Utah, Salt Lake City, UT, United States
| | - Michael Paskett
- Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
| | - Jacob A George
- Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
| | - Gregory A Clark
- Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
| |
Collapse
|
42
|
Grushko S, Spurný T, Černý M. Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback. SENSORS (BASEL, SWITZERLAND) 2020; 20:E4883. [PMID: 32872291 PMCID: PMC7506660 DOI: 10.3390/s20174883] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 08/24/2020] [Accepted: 08/25/2020] [Indexed: 02/07/2023]
Abstract
The loss of a hand can significantly affect one's work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands.
Collapse
Affiliation(s)
- Stefan Grushko
- Department of Robotics, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; (T.S.); (M.Č.)
| | | | | |
Collapse
|
43
|
Ke A, Huang J, Chen L, Gao Z, He J. An Ultra-Sensitive Modular Hybrid EMG-FMG Sensor with Floating Electrodes. SENSORS 2020; 20:s20174775. [PMID: 32846982 PMCID: PMC7506715 DOI: 10.3390/s20174775] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/16/2020] [Accepted: 08/19/2020] [Indexed: 11/16/2022]
Abstract
To improve the reliability and safety of myoelectric prosthetic control, many researchers tend to use multi-modal signals. The combination of electromyography (EMG) and forcemyography (FMG) has been proved to be a practical choice. However, an integrative and compact design of this hybrid sensor is lacking. This paper presents a novel modular EMG–FMG sensor; the sensing module has a novel design that consists of floating electrodes, which act as the sensing probe of both the EMG and FMG. This design improves the integration of the sensor. The whole system contains one data acquisition unit and eight identical sensor modules. Experiments were conducted to evaluate the performance of the sensor system. The results show that the EMG and FMG signals have good consistency under standard conditions; the FMG signal shows a better and more robust performance than the EMG. The average accuracy is 99.07% while using both the EMG and FMG signals for recognition of six hand gestures under standard conditions. Even with two layers of gauze isolated between the sensor and the skin, the average accuracy reaches 90.9% while using only the EMG signal; if we use both the EMG and FMG signals for classification, the average accuracy is 99.42%.
Collapse
Affiliation(s)
- Ang Ke
- Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; (A.K.); (Z.G.)
| | - Jian Huang
- Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; (A.K.); (Z.G.)
- Correspondence: ; Tel.: +86-136-2720-6071
| | - Luyao Chen
- School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China;
| | - Zhaolong Gao
- Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China; (A.K.); (Z.G.)
| | - Jiping He
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China;
| |
Collapse
|
44
|
Ng KA, Rusly A, Gammad GGL, Le N, Liu SC, Leong KW, Zhang M, Ho JS, Yoo J, Yen SC. A 3-Mbps, 802.11g-Based EMG Recording System With Fully Implantable 5-Electrode EMG Acquisition Device. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:889-902. [PMID: 32746357 DOI: 10.1109/tbcas.2020.3009088] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
We have developed a 5-electrode recording system that combines an implantable electromyography (EMG) device package with transcutaneous inductive power transmission, near-infrared (NIR) transcutaneous data telemetry and 3 Mbps Wi-Fi data acquisition for chronic EMG recording in vivo. This system comprises a hermetically-sealed single-chip, 5-electrode Implantable EMG Acquisition Device (IEAD), a custom external powering and Implant Telemetry Module (ITM), and a custom Wi-Fi-based Raspberry Pi-based Data Acquisition (RaspDAQ) and relay device. The external unit (ITM and RaspDAQ) is powered entirely by a single battery to achieve the objective of untethered EMG recording, for the convenience of clinicians and animal researchers. The IEAD acquires intramuscular EMG signals at 17.85 ksps/electrode while being powered transcutaneously by the ITM using 22 MHz near-field inductive coupling. The acquired EMG data is transmitted transcutaneously via NIR telemetry to the ITM, which in turn, transfers the data to the RaspDAQ for relaying to a laptop computer for display and storage. We have also validated the complete system by acquiring EMG signals from rodents for up to two months. Following the explantation of the devices, we have also conducted failure and histological analysis on the devices and the surrounding tissue, respectively.
Collapse
|
45
|
Mastinu E, Engels LF, Clemente F, Dione M, Sassu P, Aszmann O, Brånemark R, Håkansson B, Controzzi M, Wessberg J, Cipriani C, Ortiz-Catalan M. Neural feedback strategies to improve grasping coordination in neuromusculoskeletal prostheses. Sci Rep 2020; 10:11793. [PMID: 32678121 PMCID: PMC7367346 DOI: 10.1038/s41598-020-67985-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 06/11/2020] [Indexed: 11/09/2022] Open
Abstract
Conventional prosthetic arms suffer from poor controllability and lack of sensory feedback. Owing to the absence of tactile sensory information, prosthetic users must rely on incidental visual and auditory cues. In this study, we investigated the effect of providing tactile perception on motor coordination during routine grasping and grasping under uncertainty. Three transhumeral amputees were implanted with an osseointegrated percutaneous implant system for direct skeletal attachment and bidirectional communication with implanted neuromuscular electrodes. This neuromusculoskeletal prosthesis is a novel concept of artificial limb replacement that allows to extract control signals from electrodes implanted on viable muscle tissue, and to stimulate severed afferent nerve fibers to provide somatosensory feedback. Subjects received tactile feedback using three biologically inspired stimulation paradigms while performing a pick and lift test. The grasped object was instrumented to record grasping and lifting forces and its weight was either constant or unexpectedly changed in between trials. The results were also compared to the no-feedback control condition. Our findings confirm, in line with the neuroscientific literature, that somatosensory feedback is necessary for motor coordination during grasping. Our results also indicate that feedback is more relevant under uncertainty, and its effectiveness can be influenced by the selected neuromodulation paradigm and arguably also the prior experience of the prosthesis user.
Collapse
Affiliation(s)
- Enzo Mastinu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Leonard F Engels
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Francesco Clemente
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Prensilia SRL, Pontedera, Italy
| | - Mariama Dione
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Paolo Sassu
- Department of Hand Surgery, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Oskar Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Division of Plastic and Reconstructive Surgery, Medical University of Vienna, Vienna, Austria
| | - Rickard Brånemark
- Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Center for Extreme Bionics, Biomechatronics Group, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bo Håkansson
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Marco Controzzi
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Johan Wessberg
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Christian Cipriani
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden.
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
- Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Operational Area 3, Sahlgrenska University Hospital, Mölndal, Sweden.
| |
Collapse
|
46
|
Waris A, Zia ur Rehman M, Niazi IK, Jochumsen M, Englehart K, Jensen W, Haavik H, Kamavuako EN. A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN. SENSORS (BASEL, SWITZERLAND) 2020; 20:E3385. [PMID: 32549396 PMCID: PMC7349229 DOI: 10.3390/s20123385] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 06/12/2020] [Accepted: 06/12/2020] [Indexed: 12/05/2022]
Abstract
Recent developments in implantable technology, such as high-density recordings, wireless transmission of signals to a prosthetic hand, may pave the way for intramuscular electromyography (iEMG)-based myoelectric control in the future. This study aimed to investigate the real-time control performance of iEMG over time. A novel protocol was developed to quantify the robustness of the real-time performance parameters. Intramuscular wires were used to record EMG signals, which were kept inside the muscles for five consecutive days. Tests were performed on multiple days using Fitts' law. Throughput, completion rate, path efficiency and overshoot were evaluated as performance metrics using three train/test strategies. Each train/test scheme was categorized on the basis of data quantity and the time difference between training and testing data. An artificial neural network (ANN) classifier was trained and tested on (i) data from the same day (WDT), (ii) data collected from the previous day and tested on present-day (BDT) and (iii) trained on all previous days including the present day and tested on present-day (CDT). It was found that the completion rate (91.6 ± 3.6%) of CDT was significantly better (p < 0.01) than BDT (74.02 ± 5.8%) and WDT (88.16 ± 3.6%). For BDT, on average, the first session of each day was significantly better (p < 0.01) than the second and third sessions for completion rate (77.9 ± 14.0%) and path efficiency (88.9 ± 16.9%). Subjects demonstrated the ability to achieve targets successfully with wire electrodes. Results also suggest that time variations in the iEMG signal can be catered by concatenating the data over several days. This scheme can be helpful in attaining stable and robust performance.
Collapse
Affiliation(s)
- Asim Waris
- Department of Biomedical Engineering and Sciences, School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan;
| | - Muhammad Zia ur Rehman
- Faculty of Engineering and Applied Sciences, Riphah International University, Islamabad 46000, Pakistan;
| | - Imran Khan Niazi
- Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark; (M.J.); (W.J.)
- Center of Chiropractic Research, New Zealand College of Chiropractic, Auckland 1060, New Zealand;
- Faculty of Health and Environmental Sciences, Health and Rehabilitation Research Institute, AUT University, Auckland 0627, New Zealand
| | - Mads Jochumsen
- Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark; (M.J.); (W.J.)
| | - Kevin Englehart
- Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada;
| | - Winnie Jensen
- Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark; (M.J.); (W.J.)
| | - Heidi Haavik
- Center of Chiropractic Research, New Zealand College of Chiropractic, Auckland 1060, New Zealand;
| | - Ernest Nlandu Kamavuako
- Centre for Robotics Research, Department of Informatics, King’s College London, London WC2R 2LS, UK;
| |
Collapse
|
47
|
Vu PP, Chestek CA, Nason SR, Kung TA, Kemp SW, Cederna PS. The future of upper extremity rehabilitation robotics: research and practice. Muscle Nerve 2020; 61:708-718. [PMID: 32413247 PMCID: PMC7868083 DOI: 10.1002/mus.26860] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 03/03/2020] [Accepted: 03/03/2020] [Indexed: 01/14/2023]
Abstract
The loss of upper limb motor function can have a devastating effect on people's lives. To restore upper limb control and functionality, researchers and clinicians have developed interfaces to interact directly with the human body's motor system. In this invited review, we aim to provide details on the peripheral nerve interfaces and brain-machine interfaces that have been developed in the past 30 years for upper extremity control, and we highlight the challenges that still remain to transition the technology into the clinical market. The findings show that peripheral nerve interfaces and brain-machine interfaces have many similar characteristics that enable them to be concurrently developed. Decoding neural information from both interfaces may lead to novel physiological models that may one day fully restore upper limb motor function for a growing patient population.
Collapse
Affiliation(s)
- Philip P. Vu
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, University of Michigan, Ann Arbor, Michigan
| | - Cynthia A. Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Robotics Institute, University of Michigan, Ann Arbor, Michigan
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan
| | - Samuel R. Nason
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Theodore A. Kung
- Section of Plastic Surgery, University of Michigan, Ann Arbor, Michigan
| | - Stephen W.P. Kemp
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, University of Michigan, Ann Arbor, Michigan
| | - Paul S. Cederna
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, University of Michigan, Ann Arbor, Michigan
| |
Collapse
|
48
|
Cracchiolo M, Valle G, Petrini F, Strauss I, Granata G, Stieglitz T, Rossini PM, Raspopovic S, Mazzoni A, Micera S. Decoding of grasping tasks from intraneural recordings in trans-radial amputee. J Neural Eng 2020; 17:026034. [PMID: 32207409 DOI: 10.1088/1741-2552/ab8277] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE A major challenge in neuroprosthetics is the restoration of sensory-motor hand functions in upper-limb amputees. Neuroprostheses based on the direct re-connection of the peripheral nerves may be an interesting approach for re-establishing the natural and effective bidirectional control of hand prostheses. Recent results have shown that transverse intrafascicular multi-channel electrodes (TIMEs) can restore natural and sophisticated sensory feedback. However, the potential of using TIME-recorded motor intraneural signals to decode grasping tasks has not as yet been explored. APPROACH In this study, we show that several hand-movement intentions can be decoded from intraneural signals recorded using four TIMEs implanted in the median and ulnar nerves of an upper limb amputee. Experimental sessions were performed over a week, from day 16 to day 23 after the surgical operation. Intraneural activity was recorded during several hand motor tasks imagined by the subject and processed offline. MAIN RESULTS We obtained a very high decoding accuracy considering 11 class states (up to 83%). These results confirm that neural signals recorded by multi-channel intraneural electrodes can be used to decode several movement intentions with high accuracy. Moreover, we were able to use same TIME channels for decoding over one week within the first month, even if the stability has to be confirmed during long-term experiments. SIGNIFICANCE Therefore, TIMEs could be used in the future to achieve a complete bidirectional approach exploiting neural pathways, to make a more natural and intuitive new generation of hand prostheses that have a closer resemblance to a healthy hand.
Collapse
Affiliation(s)
- Marina Cracchiolo
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | | | | | | | | | | | | | | | | |
Collapse
|
49
|
Yildiz KA, Shin AY, Kaufman KR. Interfaces with the peripheral nervous system for the control of a neuroprosthetic limb: a review. J Neuroeng Rehabil 2020; 17:43. [PMID: 32151268 PMCID: PMC7063740 DOI: 10.1186/s12984-020-00667-5] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 02/17/2020] [Indexed: 12/22/2022] Open
Abstract
The field of prosthetics has been evolving and advancing over the past decade, as patients with missing extremities are expecting to control their prostheses in as normal a way as possible. Scientists have attempted to satisfy this expectation by designing a connection between the nervous system of the patient and the prosthetic limb, creating the field of neuroprosthetics. In this paper, we broadly review the techniques used to bridge the patient's peripheral nervous system to a prosthetic limb. First, we describe the electrical methods including myoelectric systems, surgical innovations and the role of nerve electrodes. We then describe non-electrical methods used alone or in combination with electrical methods. Design concerns from an engineering point of view are explored, and novel improvements to obtain a more stable interface are described. Finally, a critique of the methods with respect to their long-term impacts is provided. In this review, nerve electrodes are found to be one of the most promising interfaces in the future for intuitive user control. Clinical trials with larger patient populations, and for longer periods of time for certain interfaces, will help to evaluate the clinical application of nerve electrodes.
Collapse
Affiliation(s)
- Kadir A Yildiz
- Motion Analysis Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Alexander Y Shin
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Kenton R Kaufman
- Motion Analysis Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
- Motion Analysis Laboratory, W. Hall Wendel, Jr., Musculoskeletal Research, 200 First Street SW, Rochester, MN, 55905, USA.
| |
Collapse
|
50
|
Raspopovic S, Cimolato A, Panarese A, Vallone F, Del Valle J, Micera S, Navarro X. Neural signal recording and processing in somatic neuroprosthetic applications. A review. J Neurosci Methods 2020; 337:108653. [PMID: 32114143 DOI: 10.1016/j.jneumeth.2020.108653] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 11/30/2019] [Accepted: 02/26/2020] [Indexed: 12/11/2022]
Abstract
Neurointerfaces have acquired major relevance as both rehabilitative and therapeutic tools for patients with spinal cord injury, limb amputations and other neural disorders. Bidirectional neural interfaces are a key component for the functional control of neuroprosthetic devices. The two main neuroprosthetic applications of interfaces with the peripheral nervous system (PNS) are: the refined control of artificial prostheses with sensory neural feedback, and functional electrical stimulation (FES) systems attempting to generate motor or visceral responses in paralyzed organs. The results obtained in experimental and clinical studies with both, extraneural and intraneural electrodes are very promising in terms of the achieved functionality for the neural stimulation mode. However, the results of neural recordings with peripheral nerve interfaces are more limited. In this paper we review the different existing approaches for PNS signals recording, denoising, processing and classification, enabling their use for bidirectional interfaces. PNS recordings can provide three types of signals: i) population activity signals recorded by using extraneural electrodes placed on the outer surface of the nerve, which carry information about cumulative nerve activity; ii) spike activity signals recorded with intraneural electrodes placed inside the nerve, which carry information about the electrical activity of a set of individual nerve fibers; and iii) hybrid signals, which contain both spiking and cumulative signals. Finally, we also point out some of the main limitations, which are hampering clinical translation of neural decoding, and indicate possible solutions for improvement.
Collapse
Affiliation(s)
- Stanisa Raspopovic
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zürich, Switzerland
| | - Andrea Cimolato
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zürich, Switzerland; NEARLab - Neuroengineering and Medical Robotics Laboratory, DEIB Department of Electronics, Information and Bioengineering, Politecnico Di Milano, 20133, Milano, Italy; IIT Central Research Labs Genova, Istituto Italiano Tecnologia, 16163, Genova, Italy
| | | | - Fabio Vallone
- The BioRobotics Institute, Scuola Superiore Sant'Anna, I-56127, Pisa, Italy
| | - Jaume Del Valle
- Institute of Neurosciences and Department of Cell Biology, Physiology and Immunology, Universitat Autònoma De Barcelona, CIBERNED, 08193, Bellaterra, Spain
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, I-56127, Pisa, Italy; Translational Neural Engineering Laboratory, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale De Lausanne, Lausanne, CH-1015, Switzerland.
| | - Xavier Navarro
- Institute of Neurosciences and Department of Cell Biology, Physiology and Immunology, Universitat Autònoma De Barcelona, CIBERNED, 08193, Bellaterra, Spain; Institut Guttmann De Neurorehabilitació, Badalona, Spain.
| |
Collapse
|