A Modular Adjustable Transhumeral Prosthetic Socket for Evaluating Myoelectric Control

Novel myoelectric control strategies may yield more robust, capable prostheses which improve quality of life for those affected by upper-limb loss; however, the development and translation of such strategies from an experimental setting towards daily use by persons with limb loss is a slow and costly process. Since prosthesis functionality is highly dependent on the physical interface between the user’s prosthetic socket and residual limb, assessment of such controllers under realistic (noisy) environmental conditions, integrated into prosthetic sockets, and with participants with amputation is essential for obtaining representative results. Unfortunately, this step is particularly difficult as participant- and control strategy-specific prosthetic sockets must be custom-designed and manufactured. There is thus a need for a system to reduce these burdens and facilitate this crucial phase of the development pipeline. This study aims to address this gap through the design and assessment of an inexpensive and easy-to-use 3D-printed Modular-Adjustable transhumeral Prosthetic Socket (MAPS). This 3D-printed, open-source socket was developed in consultation with prosthetists and compared with a participant-specific suction socket in a single-participant case-study. We conducted mechanical and functional assessments to ensure that the developed socket enabled similar performance compared to participant-specific sockets. Both socket systems yielded similar results in mechanical and functional assessments, as well as in self-reported user feedback. The MAPS system shows promise as a research tool which catalyzes the development and deployment of novel myoelectric control strategies by better-enabling comprehensive assessment involving participants with amputations.

[1]  Sibylle B. Thies,et al.  The reality of myoelectric prostheses : understanding what makes , 2018 .

[2]  Gregory A. Clark,et al.  A Modular Transradial Bypass Socket for Surface Myoelectric Prosthetic Control in Non-Amputees , 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[3]  Dario Farina,et al.  Translating Research on Myoelectric Control into Clinics—Are the Performance Assessment Methods Adequate? , 2017, Front. Neurorobot..

[4]  Jason P Carey,et al.  The effect of biomechanical variables on force sensitive resistor error: Implications for calibration and improved accuracy. , 2016, Journal of biomechanics.

[5]  C. Antfolk,et al.  Artificial Redirection of Sensation From Prosthetic Fingers to the Phantom Hand Map on Transradial Amputees: Vibrotactile Versus Mechanotactile Sensory Feedback , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[6]  Keehoon Kim,et al.  Haptic Feedback Enhances Grip Force Control of sEMG-Controlled Prosthetic Hands in Targeted Reinnervation Amputees , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[7]  Jason P Carey,et al.  Characterization of interfacial socket pressure in transhumeral prostheses: A case series , 2017, PloS one.

[8]  Christopher Lake,et al.  The Evolution of Upper Limb Prosthetic Socket Design , 2008 .

[9]  Christian Cipriani,et al.  Non-Invasive, Temporally Discrete Feedback of Object Contact and Release Improves Grasp Control of Closed-Loop Myoelectric Transradial Prostheses , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[10]  Albert H Vette,et al.  Cluster-based upper body marker models for three-dimensional kinematic analysis: Comparison with an anatomical model and reliability analysis. , 2018, Journal of biomechanics.

[11]  David Alan Boone,et al.  Socket Pressure and Discomfort in Upper-Limb Prostheses: A Preliminary Study , 2014 .

[12]  Ahmed W. Shehata,et al.  When Less Is More – Discrete Tactile Feedback Dominates Continuous Audio Biofeedback in the Integrated Percept While Controlling a Myoelectric Prosthetic Hand , 2019, Front. Neurosci..

[13]  Christian Cipriani,et al.  Improving internal model strength and performance of prosthetic hands using augmented feedback , 2018, Journal of NeuroEngineering and Rehabilitation.

[14]  Dario Farina,et al.  The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis , 2018, Journal of NeuroEngineering and Rehabilitation.

[15]  Ahmed W. Shehata,et al.  Mechanotactile Sensory Feedback Improves Embodiment of a Prosthetic Hand During Active Use , 2020, Frontiers in Neuroscience.

[16]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[17]  Jacqueline S Hebert,et al.  Fabrication and application of an adjustable myoelectric transhumeral prosthetic socket , 2019, Prosthetics and orthotics international.

[18]  Christian Antfolk,et al.  Sensory feedback in upper limb prosthetics , 2013, Expert review of medical devices.

[19]  Jacqueline S. Hebert,et al.  Case report of modified Box and Blocks test with motion capture to measure prosthetic function. , 2012, Journal of rehabilitation research and development.

[20]  Craig S. Chapman,et al.  Quantitative Eye Gaze and Movement Differences in Visuomotor Adaptations to Varying Task Demands Among Upper-Extremity Prosthesis Users , 2019, JAMA network open.

[21]  Kimberly Kontson,et al.  Targeted box and blocks test: Normative data and comparison to standard tests , 2017, PloS one.

[22]  Gursel Alici,et al.  A Review of Non-Invasive Sensory Feedback Methods for Transradial Prosthetic Hands , 2018, IEEE Access.

[23]  Maurizio Valle,et al.  A System for Electrotactile Feedback Using Electronic Skin and Flexible Matrix Electrodes: Experimental Evaluation , 2017, IEEE Transactions on Haptics.

[24]  A. Heinemann,et al.  Validation of the orthotics and prosthetics user survey upper extremity functional status module in people with unilateral upper limb amputation. , 2008, Journal of rehabilitation medicine.

[25]  Albert H Vette,et al.  Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol , 2019, PloS one.

[26]  Enzo Mastinu,et al.  An Alternative Myoelectric Pattern Recognition Approach for the Control of Hand Prostheses: A Case Study of Use in Daily Life by a Dysmelia Subject , 2018, IEEE Journal of Translational Engineering in Health and Medicine.

[27]  Nathan T. Kearns,et al.  Evaluation of Performance‐Based Outcome Measures for the Upper Limb: A Comprehensive Narrative Review , 2018, PM & R : the journal of injury, function, and rehabilitation.

[28]  Jacqueline S. Hebert,et al.  Applications of sensory feedback in motorized upper extremity prosthesis: a review , 2014, Expert review of medical devices.

[29]  Jason P. Carey,et al.  Design and Integration of an Inexpensive Wearable Mechanotactile Feedback System for Myoelectric Prostheses , 2018, IEEE Journal of Translational Engineering in Health and Medicine.

[30]  Rafael Granja-Vazquez,et al.  Illusory movement perception improves motor control for prosthetic hands , 2018, Science Translational Medicine.

[31]  Albert H Vette,et al.  Characterization of normative hand movements during two functional upper limb tasks , 2018, PloS one.