Development of an Affordable Myoelectric Hand for Transradial Amputees

Upper limb amputations seriously affect a patient’s life by restricting their ability in performing various tasks. Prosthetic hands are considered the primary method toreinstatethelostcapabilitiesofsuchamputees.However,thepresentlyavailable prosthetic devices are unable to fulfill the requirements of users due to their excessivelyhighcost,limitedfunctionality,heavyweight,unnaturaloperation,and complexity.Thisarticlepresentsanaffordableandsimplecontrol-basedmyoelectric hand for transradial amputees. The hand setup mainly consists of a self-designed surfaceelectromyography(sEMG)sensor,amicrocontrollerunitandafive-fingered, intrinsicallyactuated3Dprintedhandfordexterousoperations.Thedevelopedhand wasimplementedwithproportionalcontrolschemeandwassuccessfullytestedonfive amputees(withmissinglowerforearms)forperforminggraspingactivitiesofdifferent objects.Further,theclosingtimeandgripforceatthefingertipswerealsodetermined forthehandtocompareitsperformancewiththecommerciallyavailablehands. KEywoRDS 3D Printing, Closing Time, Grip Force, Myoelectric Prosthesis, Proportional Control, Surface Electromyography, Transradial Amputation

[1]  S Conforto,et al.  Extraction of the envelope from surface EMG signals. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[2]  A. Patla Some characteristics of EMG patterns during locomotion: implications for the locomotor control process. , 1985, Journal of motor behavior.

[3]  B Hudgins,et al.  Myoelectric signal processing for control of powered limb prostheses. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[4]  C. Chandramouli,et al.  Report on disability , 2015 .

[5]  D. Farina,et al.  Spatial Correlation of High Density EMG Signals Provides Features Robust to Electrode Number and Shift in Pattern Recognition for Myocontrol , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[6]  Pornchai Phukpattaranont,et al.  Feature reduction and selection for EMG signal classification , 2012, Expert Syst. Appl..

[7]  Max Ortiz-Catalan,et al.  On the viability of implantable electrodes for the natural control of artificial limbs: Review and discussion , 2012, Biomedical engineering online.

[8]  Kevin B. Englehart,et al.  A wavelet-based continuous classification scheme for multifunction myoelectric control , 2001, IEEE Transactions on Biomedical Engineering.

[9]  Christian Cipriani,et al.  The SmartHand transradial prosthesis , 2011, Journal of NeuroEngineering and Rehabilitation.

[10]  Sheroz Khan,et al.  High Quality Acquisition of Surface Electromyography – Conditioning Circuit Design , 2013 .

[11]  Nianfeng Wang,et al.  Design and Myoelectric Control of an Anthropomorphic Prosthetic Hand , 2017 .

[12]  V. Venkatachalam,et al.  A simple envelope detector , 1988 .

[13]  Mats Djupsjöbacka,et al.  Acquisition, Processing and Analysis of the Surface Electromyogram , 1999 .

[14]  Levi J. Hargrove,et al.  A training strategy to reduce classification degradation due to electrode displacements in pattern recognition based myoelectric control , 2008, Biomed. Signal Process. Control..

[15]  Timothy Bretl,et al.  Tact: Design and performance of an open-source, affordable, myoelectric prosthetic hand , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Nicola Vitiello,et al.  Proportional EMG control for upper-limb powered exoskeletons , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[17]  Jian Huang,et al.  A real-time EMG pattern recognition method for virtual myoelectric hand control , 2014, Neurocomputing.

[18]  A. Kargov,et al.  A comparison of the grip force distribution in natural hands and in prosthetic hands , 2004, Disability and rehabilitation.

[19]  O. Stavdahl,et al.  Control of Upper Limb Prostheses: Terminology and Proportional Myoelectric Control—A Review , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  Ivan I. Borisov,et al.  Prototyping of EMG-Controlled Prosthetic Hand with Sensory System , 2017 .

[21]  V. Medved,et al.  Locomotion diagnostics: Some neuromuscular and robotic aspects , 1991, IEEE Engineering in Medicine and Biology Magazine.

[22]  Marie-Françoise Lucas,et al.  Multi-channel surface EMG classification using support vector machines and signal-based wavelet optimization , 2008, Biomed. Signal Process. Control..

[23]  Wayne Walter,et al.  Development of a Prototype Over-Actuated Biomimetic Prosthetic Hand , 2015, PloS one.

[24]  Huosheng Hu,et al.  Myoelectric control systems - A survey , 2007, Biomed. Signal Process. Control..

[25]  Samuel R. Hamner,et al.  Designing for Scale: Development of the ReMotion Knee for Global Emerging Markets , 2013, Annals of Biomedical Engineering.