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Festin C, Ortmayr J, Maierhofer U, Tereshenko V, Blumer R, Schmoll M, Carrero-Rojas G, Luft M, Laengle G, Farina D, Bergmeister KD, Aszmann OC. Creation of a biological sensorimotor interface for bionic reconstruction. Nat Commun 2024; 15:5337. [PMID: 38914540 PMCID: PMC11196281 DOI: 10.1038/s41467-024-49580-8] [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: 08/07/2023] [Accepted: 06/12/2024] [Indexed: 06/26/2024] Open
Abstract
Neuromuscular control of bionic arms has constantly improved over the past years, however, restoration of sensation remains elusive. Previous approaches to reestablish sensory feedback include tactile, electrical, and peripheral nerve stimulation, however, they cannot recreate natural, intuitive sensations. Here, we establish an experimental biological sensorimotor interface and demonstrate its potential use in neuroprosthetics. We transfer a mixed nerve to a skeletal muscle combined with glabrous dermal skin transplantation, thus forming a bi-directional communication unit in a rat model. Morphological analyses indicate reinnervation of the skin, mechanoreceptors, NMJs, and muscle spindles. Furthermore, sequential retrograde labeling reveals specific sensory reinnervation at the level of the dorsal root ganglia. Electrophysiological recordings show reproducible afferent signals upon tactile stimulation and tendon manipulation. The results demonstrate the possibility of surgically creating an interface for both decoding efferent motor control, as well as encoding afferent tactile and proprioceptive feedback, and may indicate the way forward regarding clinical translation of biological communication pathways for neuroprosthetic applications.
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Affiliation(s)
- Christopher Festin
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
| | - Joachim Ortmayr
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Udo Maierhofer
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
| | - Vlad Tereshenko
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roland Blumer
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Martin Schmoll
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Génova Carrero-Rojas
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Matthias Luft
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Aesthetic and Reconstructive Surgery, University Hospital St. Poelten, Karl Landsteiner University of Health Sciences, Krems, Austria
| | - Gregor Laengle
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Konstantin D Bergmeister
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Aesthetic and Reconstructive Surgery, University Hospital St. Poelten, Karl Landsteiner University of Health Sciences, Krems, Austria
| | - 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.
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2
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Sparling T, Iyer L, Pasquina P, Petrus E. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery. J Neurosci 2024; 44:e1051232024. [PMID: 38171645 PMCID: PMC10851691 DOI: 10.1523/jneurosci.1051-23.2023] [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: 06/08/2023] [Revised: 08/28/2023] [Accepted: 09/29/2023] [Indexed: 01/05/2024] Open
Abstract
Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.
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Affiliation(s)
- Tawnee Sparling
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Laxmi Iyer
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817
| | - Paul Pasquina
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Emily Petrus
- Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, Maryland 20814
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3
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Mathewson KW, Parker ASR, Sherstan C, Edwards AL, Sutton RS, Pilarski PM. Communicative capital: a key resource for human-machine shared agency and collaborative capacity. Neural Comput Appl 2022; 35:16805-16819. [PMID: 37455836 PMCID: PMC10338399 DOI: 10.1007/s00521-022-07948-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 10/12/2022] [Indexed: 11/16/2022]
Abstract
In this work, we present a perspective on the role machine intelligence can play in supporting human abilities. In particular, we consider research in rehabilitation technologies such as prosthetic devices, as this domain requires tight coupling between human and machine. Taking an agent-based view of such devices, we propose that human-machine collaborations have a capacity to perform tasks which is a result of the combined agency of the human and the machine. We introduce communicative capital as a resource developed by a human and a machine working together in ongoing interactions. Development of this resource enables the partnership to eventually perform tasks at a capacity greater than either individual could achieve alone. We then examine the benefits and challenges of increasing the agency of prostheses by surveying literature which demonstrates that building communicative resources enables more complex, task-directed interactions. The viewpoint developed in this article extends current thinking on how best to support the functional use of increasingly complex prostheses, and establishes insight toward creating more fruitful interactions between humans and supportive, assistive, and augmentative technologies.
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Affiliation(s)
| | - Adam S. R. Parker
- University of Alberta, Edmonton, Canada
- Alberta Machine Intelligence Institute (Amii), Edmonton, Canada
| | | | | | - Richard S. Sutton
- DeepMind, Montreal, Canada
- University of Alberta, Edmonton, Canada
- Alberta Machine Intelligence Institute (Amii), Edmonton, Canada
- DeepMind, Edmonton, Canada
| | - Patrick M. Pilarski
- DeepMind, Montreal, Canada
- University of Alberta, Edmonton, Canada
- Alberta Machine Intelligence Institute (Amii), Edmonton, Canada
- DeepMind, Edmonton, Canada
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4
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Gonzalez M, Bismuth A, Lee C, Chestek CA, Gates DH. Artificial referred sensation in upper and lower limb prosthesis users: a systematic review. J Neural Eng 2022; 19:10.1088/1741-2552/ac8c38. [PMID: 36001115 PMCID: PMC9514130 DOI: 10.1088/1741-2552/ac8c38] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/23/2022] [Indexed: 11/12/2022]
Abstract
Objective.Electrical stimulation can induce sensation in the phantom limb of individuals with amputation. It is difficult to generalize existing findings as there are many approaches to delivering stimulation and to assessing the characteristics and benefits of sensation. Therefore, the goal of this systematic review was to explore the stimulation parameters that effectively elicited referred sensation, the qualities of elicited sensation, and how the utility of referred sensation was assessed.Approach.We searched PubMed, Web of Science, and Engineering Village through January of 2022 to identify relevant papers. We included papers which electrically induced referred sensation in individuals with limb loss and excluded papers that did not contain stimulation parameters or outcome measures pertaining to stimulation. We extracted information on participant demographics, stimulation approaches, and participant outcomes.Main results.After applying exclusion criteria, 49 papers were included covering nine stimulation methods. Amplitude was the most commonly adjusted parameter (n= 25), followed by frequency (n= 22), and pulse width (n= 15). Of the 63 reports of sensation quality, most reported feelings of pressure (n= 52), paresthesia (n= 48), or vibration (n= 40) while less than half (n= 29) reported a sense of position or movement. Most papers evaluated the functional benefits of sensation (n= 33) using force matching or object identification tasks, while fewer papers quantified subjective measures (n= 16) such as pain or embodiment. Only 15 studies (36%) observed percept intensity, quality, or location over multiple sessions.Significance.Most studies that measured functional performance demonstrated some benefit to providing participants with sensory feedback. However, few studies could experimentally manipulate sensation location or quality. Direct comparisons between studies were limited by variability in methodologies and outcome measures. As such, we offer recommendations to aid in more standardized reporting for future research.
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Affiliation(s)
- Michael Gonzalez
- Department of Robotics, University of Michigan, Ann Arbor, MI, United States of America
| | - Alex Bismuth
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Christina Lee
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Deanna H Gates
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States of America
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5
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Marasco PD, Hebert JS, Sensinger JW, Beckler DT, Thumser ZC, Shehata AW, Williams HE, Wilson KR. Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors. Sci Robot 2021; 6:eabf3368. [PMID: 34516746 DOI: 10.1126/scirobotics.abf3368] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Paul D Marasco
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard 151 W/APT, Cleveland, OH 44106, USA
| | - Jacqueline S Hebert
- Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta T6G 2E1, Canada.,Glenrose Rehabilitation Hospital, Alberta Health Services, 10230-111 Avenue, Edmonton, Alberta T5G 0B7, Canada
| | - Jonathon W Sensinger
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
| | - Dylan T Beckler
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Zachary C Thumser
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Research Service, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard, Research 151, Cleveland, OH 44106, USA
| | - Ahmed W Shehata
- Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta T6G 2E1, Canada
| | - Heather E Williams
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta T6G 2E1, Canada
| | - Kathleen R Wilson
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
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6
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Abstract
BACKGROUND Recent progress in biomechatronics and vascularized composite allotransplantation have occurred in the absence of congruent advancements in the surgical approaches generally utilized for limb amputation. Consideration of these advances, as well as of both novel and time-honored reconstructive surgical techniques, argues for a fundamental reframing of the way in which amputation procedures should be performed. METHODS We review sentinel developments in external prosthetic limb technology and limb transplantation, in addition to standard and emerging reconstructive surgical techniques relevant to limb modification, and then propose a new paradigm for limb amputation. RESULTS An approach to limb amputation based on the availability of native tissues is proposed, with the intent of maximizing limb function, limiting neuropathic pain, restoring limb perception/proprioception and mitigating limb atrophy. CONCLUSIONS We propose a reinvention of the manner in which limb amputations are performed, framed in the context of time-tested reconstructive techniques, as well as novel, state-of-the-art surgical procedures. Implementation of the proposed techniques in the acute setting has the potential to elevate advanced limb replacement strategies to a clinical solution that perhaps exceeds what is possible through traditional surgical approaches to limb salvage. We therefore argue that amputation, performed with the intent of optimizing the residuum for interaction with either a bionic or a transplanted limb, should be viewed not as a surgical failure, but as an alternative form of limb reconstruction.
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7
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A cutaneous mechanoneural interface for neuroprosthetic feedback. Nat Biomed Eng 2021; 6:731-740. [PMID: 33526908 DOI: 10.1038/s41551-020-00669-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 11/26/2020] [Indexed: 01/16/2023]
Abstract
Amputation destroys sensory end organs and does not provide an anatomical interface for cutaneous neuroprosthetic feedback. Here, we report the design and a biomechanical and electrophysiological evaluation of the cutaneous mechanoneural interface consisting of an afferent neural system that comprises a muscle actuator coupled to a natively pedicled skin flap in a cuff-like architecture. Muscle is actuated through electrical stimulation to induce strains or oscillatory vibrations on the skin flap that are proportional to a desired contact duration or contact pressure. In rat hindlimbs, the mechanoneural interface elicited native dermal mechanotransducers to generate at least four levels of graded contact and eight distinct vibratory afferents that were not significantly different from analogous mechanical stimulation of intact skin. The application of different patterns of electrical stimulation independently engaged slowly adapting and rapidly adapting mechanotransducers, and recreated an array of cutaneous sensations. The cutaneous mechanoneural interface can be integrated with current prosthetic technologies for tactile feedback.
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8
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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.
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Affiliation(s)
- Stefan Grushko
- Department of Robotics, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; (T.S.); (M.Č.)
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9
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Marasco PD, Hebert JS, Sensinger JW, Shell CE, Schofield JS, Thumser ZC, Nataraj R, Beckler DT, Dawson MR, Blustein DH, Gill S, Mensh BD, Granja-Vazquez R, Newcomb MD, Carey JP, Orzell BM. Illusory movement perception improves motor control for prosthetic hands. Sci Transl Med 2019. [PMID: 29540617 DOI: 10.1126/scitranslmed.aao6990] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
To effortlessly complete an intentional movement, the brain needs feedback from the body regarding the movement's progress. This largely nonconscious kinesthetic sense helps the brain to learn relationships between motor commands and outcomes to correct movement errors. Prosthetic systems for restoring function have predominantly focused on controlling motorized joint movement. Without the kinesthetic sense, however, these devices do not become intuitively controllable. We report a method for endowing human amputees with a kinesthetic perception of dexterous robotic hands. Vibrating the muscles used for prosthetic control via a neural-machine interface produced the illusory perception of complex grip movements. Within minutes, three amputees integrated this kinesthetic feedback and improved movement control. Combining intent, kinesthesia, and vision instilled participants with a sense of agency over the robotic movements. This feedback approach for closed-loop control opens a pathway to seamless integration of minds and machines.
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Affiliation(s)
- Paul D Marasco
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA. .,Advanced Platform Technology Center of Excellence, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard 151 W/APT, Cleveland, OH 44106, USA
| | - Jacqueline S Hebert
- Division of Physical Medicine and Rehabilitation, University of Alberta, Edmonton, Alberta T6G 2E1, Canada.,Glenrose Rehabilitation Hospital, Alberta Health Services, 10230-111 Avenue, Edmonton, Alberta T5G 0B7, Canada
| | - Jon W Sensinger
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
| | - Courtney E Shell
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Jonathon S Schofield
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Zachary C Thumser
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Research Service, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard, Research 151, Cleveland, OH 44106, USA
| | - Raviraj Nataraj
- Department of Biomedical Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, USA
| | - Dylan T Beckler
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Michael R Dawson
- Glenrose Rehabilitation Hospital, Alberta Health Services, 10230-111 Avenue, Edmonton, Alberta T5G 0B7, Canada
| | - Dan H Blustein
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
| | - Satinder Gill
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
| | - Brett D Mensh
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Rafael Granja-Vazquez
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Madeline D Newcomb
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Jason P Carey
- Department of Mechanical Engineering, University of Alberta, Donadeo Innovation Center for Engineering, Edmonton, Alberta T6G 2G8, Canada
| | - Beth M Orzell
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Prosthetics and Sensory Aids Service, Department of Physical Medicine and Rehabilitation, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard, Cleveland, OH 44106, USA
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10
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Parker ASR, Edwards AL, Pilarski PM. Exploring the Impact of Machine-Learned Predictions on Feedback from an Artificial Limb. IEEE Int Conf Rehabil Robot 2019; 2019:1239-1246. [PMID: 31374799 DOI: 10.1109/icorr.2019.8779424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Learning to get by without an arm or hand can be very challenging, and existing prostheses do not yet fill the needs of individuals with amputations. One promising solution is to improve the feedback from the device to the user. Towards this end, we present a simple machine learning interface to supplement the control of a robotic limb with feedback to the user about what the limb will be experiencing in the near future. A real-time prediction learner was implemented to predict impact-related electrical load experienced by a robot limb; the learning system's predictions were then communicated to the device's user to aid in their interactions with a workspace. We tested this system with five able-bodied subjects. Each subject manipulated the robot arm while receiving different forms of vibrotactile feedback regarding the arm's contact with its workspace. Our trials showed that using machine-learned predictions as a basis for feedback led to a statistically significant improvement in task performance when compared to purely reactive feedback from the device. Our study therefore contributes initial evidence that prediction learning and machine intelligence can benefit not just control, but also feedback from an artificial limb. We expect that a greater level of acceptance and ownership can be achieved if the prosthesis itself takes an active role in transmitting learned knowledge about its state and its situation of use.
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11
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Nizamis K, Stienen AHA, Kamper DG, Keller T, Plettenburg DH, Rouse EJ, Farina D, Koopman BFJM, Sartori M. Transferrable Expertise From Bionic Arms to Robotic Exoskeletons: Perspectives for Stroke and Duchenne Muscular Dystrophy. ACTA ACUST UNITED AC 2019. [DOI: 10.1109/tmrb.2019.2912453] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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12
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Tyler DJ. Neuroprostheses for Restoring Sensation. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00103-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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13
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Ghafoor U, Kim S, Hong KS. Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. Front Neurorobot 2017; 11:59. [PMID: 29163122 PMCID: PMC5671609 DOI: 10.3389/fnbot.2017.00059] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2017] [Accepted: 10/17/2017] [Indexed: 11/22/2022] Open
Abstract
For those individuals with upper-extremity amputation, a daily normal living activity is no longer possible or it requires additional effort and time. With the aim of restoring their sensory and motor functions, theoretical and technological investigations have been carried out in the field of neuroprosthetic systems. For transmission of sensory feedback, several interfacing modalities including indirect (non-invasive), direct-to-peripheral-nerve (invasive), and cortical stimulation have been applied. Peripheral nerve interfaces demonstrate an edge over the cortical interfaces due to the sensitivity in attaining cortical brain signals. The peripheral nerve interfaces are highly dependent on interface designs and are required to be biocompatible with the nerves to achieve prolonged stability and longevity. Another criterion is the selection of nerves that allows minimal invasiveness and damages as well as high selectivity for a large number of nerve fascicles. In this paper, we review the nerve-machine interface modalities noted above with more focus on peripheral nerve interfaces, which are responsible for provision of sensory feedback. The invasive interfaces for recording and stimulation of electro-neurographic signals include intra-fascicular, regenerative-type interfaces that provide multiple contact channels to a group of axons inside the nerve and the extra-neural-cuff-type interfaces that enable interaction with many axons around the periphery of the nerve. Section Current Prosthetic Technology summarizes the advancements made to date in the field of neuroprosthetics toward the achievement of a bidirectional nerve-machine interface with more focus on sensory feedback. In the Discussion section, the authors propose a hybrid interface technique for achieving better selectivity and long-term stability using the available nerve interfacing techniques.
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Affiliation(s)
- Usman Ghafoor
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
| | - Sohee Kim
- Department of Robotics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, South Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan, South Korea.,Department of Cogno-Mechatronics Engineering, Pusan National University, Busan, South Korea
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14
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Hebert JS, Chan KM, Dawson MR. Cutaneous sensory outcomes from three transhumeral targeted reinnervation cases. Prosthet Orthot Int 2016; 40:303-10. [PMID: 26932982 DOI: 10.1177/0309364616633919] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Accepted: 11/11/2015] [Indexed: 02/03/2023]
Abstract
BACKGROUND Although targeted muscle reinnervation has been shown to be effective in enhancing prosthetic control for upper limb amputees, restored hand sensations have been variable. An understanding of possible sensory feedback channels is crucial in working toward more effective closed-loop prosthetic control. OBJECTIVES To compare sensory outcomes of different targeted sensory reinnervation approaches. STUDY DESIGN Case series, cross-sectional, and retrospective. METHODS Three transhumeral amputees that had undergone different sensory reinnervation approaches were recruited. Skin pressure sensitivity thresholds and anatomic sensory mapping were performed using Semmes-Weinstein monofilaments. The clinical charts of the subjects were reviewed to compare the sensory maps performed during the earlier post-reinnervation period. RESULTS While the first two subjects achieved return of hand sensations on the stump skin in early follow-up, the maps showed attenuation over time. The last subject developed discrete sensations of all digits in the recipient cutaneous nerve territories away from the reinnervated muscles. CONCLUSIONS These findings confirm that it is feasible to restore hand sensation after transhumeral targeted reinnervation, but there is a significant intersubject variability. The intrafascicular approach may be particularly effective in restoring digit sensation and deserves further exploration, as do factors affecting stability of the hand maps over time. CLINICAL RELEVANCE In addition to enabling intuitive motor control of myoelectric prosthesis, targeted reinnervation can also result in sensory restoration of the hand. Documentation of sensory mapping present after reinnervation may assist with exploring future techniques for sensory enhancement, with the goal of working toward closed-loop prosthetic control.
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Affiliation(s)
- Jacqueline S Hebert
- University of Alberta, Edmonton, AB, Canada Glenrose Rehabilitation Hospital, Edmonton, AB, Canada
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Ciancio AL, Cordella F, Barone R, Romeo RA, Bellingegni AD, Sacchetti R, Davalli A, Di Pino G, Ranieri F, Di Lazzaro V, Guglielmelli E, Zollo L. Control of Prosthetic Hands via the Peripheral Nervous System. Front Neurosci 2016; 10:116. [PMID: 27092041 PMCID: PMC4824757 DOI: 10.3389/fnins.2016.00116] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Accepted: 03/08/2016] [Indexed: 11/13/2022] Open
Abstract
This paper intends to provide a critical review of the literature on the technological issues on control and sensorization of hand prostheses interfacing with the Peripheral Nervous System (i.e., PNS), and their experimental validation on amputees. The study opens with an in-depth analysis of control solutions and sensorization features of research and commercially available prosthetic hands. Pros and cons of adopted technologies, signal processing techniques and motion control solutions are investigated. Special emphasis is then dedicated to the recent studies on the restoration of tactile perception in amputees through neural interfaces. The paper finally proposes a number of suggestions for designing the prosthetic system able to re-establish a bidirectional communication with the PNS and foster the prosthesis natural control.
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Affiliation(s)
- Anna Lisa Ciancio
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | - Francesca Cordella
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | - Roberto Barone
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | - Rocco Antonio Romeo
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | - Alberto Dellacasa Bellingegni
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | | | | | - Giovanni Di Pino
- Institute of Neurology, Università Campus Bio-Medico di Roma Roma, Italy
| | - Federico Ranieri
- Institute of Neurology, Università Campus Bio-Medico di Roma Roma, Italy
| | | | - Eugenio Guglielmelli
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
| | - Loredana Zollo
- Unit of Biomedical Robotics and Biomicrosystems, Department of Engineering, Università Campus Bio-Medico di Roma Roma, Italy
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Abstract
PURPOSE OF REVIEW When an individual loses a limb, he/she loses touch with the world and with the people around him/her. Somatosensation is critical to the feeling of connection and control of one's own body. Decades of attempts to replace lost somatosensation by sensory substitutions have been ineffective outside of the laboratory. This review discusses important recent results demonstrating chronic somatosensory restoration through direct peripheral nerve stimulation. RECENT FINDINGS Stimulation of peripheral nerves results in somatosensory perception on the phantom limb. Sensations are localized to several independent and functionally relevant locations, such as the fingertips, thenar eminence, ulnar border and dorsal surface. Patterns in stimulation intensity change the perception experience by the user, opening new dimensions on neuromodulation. SUMMARY Neural interfaces with sophisticated stimulation paradigms create a user's perception of his/her hand to touch and manipulate objects. The pattern of intensity and frequency of stimulation is critical to the quality and intensity of perceived sensation. Restoring feeling has allowed the individuals to, 'feel [my] hand for the first time since the accident,' and 'feel [my] wife touch my hand'. Individuals using a prosthetic hand with sensation can pull cherries and grapes from the stem, open water bottles and move objects without destroying these objects - all while audio and visually deprived. After regaining sensation, phantom pain is eliminated in individuals that had frequent, sometimes debilitating, pain following limb loss. With over 5 subject-years of experience, this work is leading the evolution of a new era in prostheses. Somatosensory prosthetics as a standard procedure to augment and restore somatosensation are now within our reach.
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Affiliation(s)
- Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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