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Human Hand Anatomy-Based Prosthetic Hand. SENSORS 2020; 21:s21010137. [PMID: 33379252 PMCID: PMC7795667 DOI: 10.3390/s21010137] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/15/2020] [Accepted: 12/22/2020] [Indexed: 11/25/2022]
Abstract
The present paper describes the development of a prosthetic hand based on human hand anatomy. The hand phalanges are printed with 3D printing with Polylactic Acid material. One of the main contributions is the investigation on the prosthetic hand joins; the proposed design enables one to create personalized joins that provide the prosthetic hand a high level of movement by increasing the degrees of freedom of the fingers. Moreover, the driven wire tendons show a progressive grasping movement, being the friction of the tendons with the phalanges very low. Another important point is the use of force sensitive resistors (FSR) for simulating the hand touch pressure. These are used for the grasping stop simulating touch pressure of the fingers. Surface Electromyogram (EMG) sensors allow the user to control the prosthetic hand-grasping start. Their use may provide the prosthetic hand the possibility of the classification of the hand movements. The practical results included in the paper prove the importance of the soft joins for the object manipulation and to get adapted to the object surface. Finally, the force sensitive sensors allow the prosthesis to actuate more naturally by adding conditions and classifications to the Electromyogram sensor.
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Schmalfuss L, Hahne J, Farina D, Hewitt M, Kogut A, Doneit W, Reischl M, Rupp R, Liebetanz D. A hybrid auricular control system: direct, simultaneous, and proportional myoelectric control of two degrees of freedom in prosthetic hands. J Neural Eng 2018; 15:056028. [PMID: 30063469 DOI: 10.1088/1741-2552/aad727] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The conventional myoelectric control scheme of hand prostheses provides a high level of robustness during continuous use. Typically, the electrical activity of an agonist/antagonist muscle pair in the forearm is detected and used to control either opening/closing or rotation of the prosthetic hand. The translation of more sophisticated control approaches (e.g. regression-based classifiers) to clinical practice is limited mainly because of their lack of robustness in real-world conditions (e.g. due to different arm positions). We therefore explore a new hybrid approach, in which a second degree of freedom (DOF) controlled by the myoelectric activity of the posterior auricular muscles is added to the conventional forearm control. With this, an independent, simultaneous and proportional control of rotation and opening/closing of the hand is possible. APPROACH In this study, we compared the hybrid auricular control system (hACS) to the two most commonly used control techniques for two DOF. Ten able-bodied subjects and one person with transradial amputation performed two standardizes tests in three different arm positions. MAIN RESULTS Subjects controlled a hand prosthesis significantly more rapidly and more accurately using the hACS. Moreover, the robustness of the system was not influenced by different arm positions. SIGNIFICANCE The hACS therefore offers an alternative solution for simultaneous and proportional myoelectric control of two degrees of freedom that avoids several robustness issues related to machine learning based approaches.
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Affiliation(s)
- Leonie Schmalfuss
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany
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Liu Y, Norton JJS, Qazi R, Zou Z, Ammann KR, Liu H, Yan L, Tran PL, Jang KI, Lee JW, Zhang D, Kilian KA, Jung SH, Bretl T, Xiao J, Slepian MJ, Huang Y, Jeong JW, Rogers JA. Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human-machine interfaces. SCIENCE ADVANCES 2016; 2:e1601185. [PMID: 28138529 PMCID: PMC5262452 DOI: 10.1126/sciadv.1601185] [Citation(s) in RCA: 169] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Accepted: 10/20/2016] [Indexed: 05/17/2023]
Abstract
Physiological mechano-acoustic signals, often with frequencies and intensities that are beyond those associated with the audible range, provide information of great clinical utility. Stethoscopes and digital accelerometers in conventional packages can capture some relevant data, but neither is suitable for use in a continuous, wearable mode, and both have shortcomings associated with mechanical transduction of signals through the skin. We report a soft, conformal class of device configured specifically for mechano-acoustic recording from the skin, capable of being used on nearly any part of the body, in forms that maximize detectable signals and allow for multimodal operation, such as electrophysiological recording. Experimental and computational studies highlight the key roles of low effective modulus and low areal mass density for effective operation in this type of measurement mode on the skin. Demonstrations involving seismocardiography and heart murmur detection in a series of cardiac patients illustrate utility in advanced clinical diagnostics. Monitoring of pump thrombosis in ventricular assist devices provides an example in characterization of mechanical implants. Speech recognition and human-machine interfaces represent additional demonstrated applications. These and other possibilities suggest broad-ranging uses for soft, skin-integrated digital technologies that can capture human body acoustics.
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Affiliation(s)
- Yuhao Liu
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - James J. S. Norton
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Raza Qazi
- Department of Electrical, Computer and Energy Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Zhanan Zou
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Kaitlyn R. Ammann
- Department of Medicine, Sarver Heart Center, and Department of Biomedical Engineering Graduate Interdisciplinary Program, The University of Arizona, Tucson, AZ 85724, USA
| | - Hank Liu
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Lingqing Yan
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Phat L. Tran
- Department of Medicine, Sarver Heart Center, and Department of Biomedical Engineering Graduate Interdisciplinary Program, The University of Arizona, Tucson, AZ 85724, USA
| | - Kyung-In Jang
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jung Woo Lee
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Douglas Zhang
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Kristopher A. Kilian
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Sung Hee Jung
- Department of Internal Medicine, Eulji University College of Medicine, Daejeon, Korea
| | - Timothy Bretl
- Department of Aerospace Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Jianliang Xiao
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
- Materials Science and Engineering Program, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Marvin J. Slepian
- Department of Medicine, Sarver Heart Center, and Department of Biomedical Engineering Graduate Interdisciplinary Program, The University of Arizona, Tucson, AZ 85724, USA
| | - Yonggang Huang
- Department of Civil and Environmental Engineering and Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Jae-Woong Jeong
- Department of Electrical, Computer and Energy Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
- Materials Science and Engineering Program, University of Colorado Boulder, Boulder, CO 80309, USA
| | - John A. Rogers
- Department of Materials Science and Engineering and Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Johansen D, Cipriani C, Popovic DB, Struijk LNSA. Control of a Robotic Hand Using a Tongue Control System-A Prosthesis Application. IEEE Trans Biomed Eng 2016; 63:1368-76. [PMID: 26780786 DOI: 10.1109/tbme.2016.2517742] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the feasibility of using an inductive tongue control system (ITCS) for controlling robotic/prosthetic hands and arms. METHODS This study presents a novel dual modal control scheme for multigrasp robotic hands combining standard electromyogram (EMG) with the ITCS. The performance of the ITCS control scheme was evaluated in a comparative study. Ten healthy subjects used both the ITCS control scheme and a conventional EMG control scheme to complete grasping exercises with the IH1 Azzurra robotic hand implementing five grasps. Time to activate a desired function or grasp was used as the performance metric. RESULTS Statistically significant differences were found when comparing the performance of the two control schemes. On average, the ITCS control scheme was 1.15 s faster than the EMG control scheme, corresponding to a 35.4% reduction in the activation time. The largest difference was for grasp 5 with a mean AT reduction of 45.3% (2.38 s). CONCLUSION The findings indicate that using the ITCS control scheme could allow for faster activation of specific grasps or functions compared with a conventional EMG control scheme. SIGNIFICANCE For transhumeral and especially bilateral amputees, the ITCS control scheme could have a significant impact on the prosthesis control. In addition, the ITCS would provide bilateral amputees with the additional advantage of environmental and computer control for which the ITCS was originally developed.
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Johansen D, Sebelius F, Jensen S, Bentsen B, Popović DB, Andreasen Struijk LNS. A comparative study of virtual hand prosthesis control using an inductive tongue control system. Assist Technol 2015; 28:22-9. [PMID: 26479838 DOI: 10.1080/10400435.2015.1070303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
This study compares the time required to activate a grasp or function of a hand prosthesis when using an electromyogram (EMG) based control scheme and when using a control scheme combining EMG and control signals from an inductive tongue control system (ITCS). Using a cross-over study design, 10 able-bodied subjects used a computer model of a hand and completed simulated grasping exercises. The time required to activate grasps was recorded and analyzed for both control schemes. End session mean activation times (ATs; seconds) for the EMG control scheme grasps 1 -5 were 0.80, 1.51, 1.95, 2.93, and 3.42; for the ITCS control scheme grasps 1 ‒5 they were 1.19, 1.89, 1.75, 2.26, and 1.80. Mean AT for grasps 1 and 2 was statistically significant in favor of the EMG control scheme (p = 0.030; p = 0.004). For grasp 3 no statistical significance occurred, and for grasps 4 and 5 there was a statistical significance in favour of the ITCS control scheme (p = 0.048; p = 0.004). Based on the amount of training and the achieved level of performance, it is concluded that the proposed ITCS control scheme can be used as a means of enhancing prosthesis control.
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Affiliation(s)
- Daniel Johansen
- a Centre for Sensory-Motor Interaction, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
| | - Fredrik Sebelius
- b Department of Biomedical Engineering , Lund University , Lund , Sweden
| | - Stig Jensen
- c Arm Center, Sahva A/S, København Ø , Denmark
| | - Bo Bentsen
- a Centre for Sensory-Motor Interaction, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
| | - Dejan B Popović
- a Centre for Sensory-Motor Interaction, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark.,d School of Electrical Engineering , University of Belgrade , Belgrade , Serbia
| | - Lotte N S Andreasen Struijk
- a Centre for Sensory-Motor Interaction, Department of Health Science and Technology , Aalborg University , Aalborg , Denmark
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Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands. PLoS One 2015; 10:e0127528. [PMID: 26069961 PMCID: PMC4466571 DOI: 10.1371/journal.pone.0127528] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2014] [Accepted: 04/16/2015] [Indexed: 11/19/2022] Open
Abstract
Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system’s complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs.
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Farina D, Jiang N, Rehbaum H, Holobar A, Graimann B, Dietl H, Aszmann OC. The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges. IEEE Trans Neural Syst Rehabil Eng 2014; 22:797-809. [PMID: 24760934 DOI: 10.1109/tnsre.2014.2305111] [Citation(s) in RCA: 386] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.
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Wong YT, Hagan MA, Markowitz DA, Pesaran B. The tracking of reaches in three-dimensions. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2011; 2011:5440-5443. [PMID: 22255568 PMCID: PMC4183760 DOI: 10.1109/iembs.2011.6091388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Prosthetic devices to replace upper limb function have made great progress over the last decade. However, current control modalities for these prosthetics still have severe limitations in the degrees of freedom they offer patients. Brain machine interfaces offer the possibility to improve the functionality of prosthetics. Current research on brain machine interfaces is limited by our understanding of the neural representations for various movements. Few electrophysiology studies have examined the encoding of unconstrained multi-joint movements in neural signals. Here we present a system for the high-speed tracking of multiple joints in three dimensions while recording, optimizing and decoding neural signals.
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Affiliation(s)
- Yan T Wong
- Center for Neural Science, New York University, New York, NY 10003, USA
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Dosen S, Cipriani C, Kostić M, Controzzi M, Carrozza MC, Popović DB. Cognitive vision system for control of dexterous prosthetic hands: experimental evaluation. J Neuroeng Rehabil 2010; 7:42. [PMID: 20731834 PMCID: PMC2940869 DOI: 10.1186/1743-0003-7-42] [Citation(s) in RCA: 83] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2010] [Accepted: 08/23/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Dexterous prosthetic hands that were developed recently, such as SmartHand and i-LIMB, are highly sophisticated; they have individually controllable fingers and the thumb that is able to abduct/adduct. This flexibility allows implementation of many different grasping strategies, but also requires new control algorithms that can exploit the many degrees of freedom available. The current study presents and tests the operation of a new control method for dexterous prosthetic hands. METHODS The central component of the proposed method is an autonomous controller comprising a vision system with rule-based reasoning mounted on a dexterous hand (CyberHand). The controller, termed cognitive vision system (CVS), mimics biological control and generates commands for prehension. The CVS was integrated into a hierarchical control structure: 1) the user triggers the system and controls the orientation of the hand; 2) a high-level controller automatically selects the grasp type and size; and 3) an embedded hand controller implements the selected grasp using closed-loop position/force control. The operation of the control system was tested in 13 healthy subjects who used Cyberhand, attached to the forearm, to grasp and transport 18 objects placed at two different distances. RESULTS The system correctly estimated grasp type and size (nine commands in total) in about 84% of the trials. In an additional 6% of the trials, the grasp type and/or size were different from the optimal ones, but they were still good enough for the grasp to be successful. If the control task was simplified by decreasing the number of possible commands, the classification accuracy increased (e.g., 93% for guessing the grasp type only). CONCLUSIONS The original outcome of this research is a novel controller empowered by vision and reasoning and capable of high-level analysis (i.e., determining object properties) and autonomous decision making (i.e., selecting the grasp type and size). The automatic control eases the burden from the user and, as a result, the user can concentrate on what he/she does, not on how he/she should do it. The tests showed that the performance of the controller was satisfactory and that the users were able to operate the system with minimal prior training.
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Affiliation(s)
- Strahinja Dosen
- Department for Health Science and Technology, Center for Sensory-Motor Interaction, Aalborg University, 9220 Aalborg, Denmark.
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