Abstract
Persons with upper-limb amputations face severe problems due to a reduction in their ability to perform the activities of daily living. The prosthesis controlled by electromyography (EMG) or other signals from sensors, switches, accelerometers, etc., can somewhat regain the lost capability of such individuals. However, there are several issues with these prostheses, such as expensive cost, limited functionality, unnatural control, slow operating speed, complexity, heavyweight, large size, etc. This paper proposes an affordable transradial prosthesis, controlled by the muscular contractions from user intention. A surface EMG sensor was explicitly fabricated for capturing the muscle contraction information from the residual forearm of subjects with amputation. An under actuated 3D printed hand was developed with a prosthetic socket assembly to attach the remaining upper-limb of such subjects. The hand integrates an intuitive closed-loop control system that receives reference input from the designed sensor and feedback input from a force sensor installed at the thumb tip. The performance of the EMG sensor was compared with that of a traditional sensor in detecting muscle contractions from the subjects. The designed sensor showed a good correlation (r > 0.93) and a better signal-to-noise ratio (SNR) feature to the conventional sensor. Further, a successful trial of the developed hand prosthesis was made on five different subjects with transradial amputation. The users wearing the hand prototype were able to perform faster and delicate grasping of various objects. The implemented control system allowed the prosthesis users to control the grasp force of hand fingers with their intention of muscular contractions.
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References
Slade P, Akhtar A, Nguyen M, Bretl T (2015) Tact: design and performance of an open-source, affordable, myoelectric prosthetic hand. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, Seattle, WA, USA, pp 6451–6456
World Report on Disability. 350
Sahu A, Sagar R, Sarkar S, Sagar S (2016) Psychological effects of amputation: A review of studies from India. Ind Psychiatry J 25:4–10. https://doi.org/10.4103/0972-6748.196041
Geethanjali P (2016) Myoelectric control of prosthetic hands: state-of-the-art review. Med Devices (Auckl) 9:247–255. https://doi.org/10.2147/MDER.S91102
Uellendahl J (2017) Myoelectric versus body-powered upper-limb prostheses: a clinical perspective. JPO 29:25. https://doi.org/10.1097/JPO.0000000000000151
Cordella F, Ciancio AL, Sacchetti R, Davalli A, Cutti AG, Guglielmelli E, Zollo L (2016) Literature review on needs of upper limb prosthesis users. Front Neurosci. https://doi.org/10.3389/fnins.2016.00209
Prakash A, Sahi AK, Sharma N, Sharma S (2020) Force myography controlled multifunctional hand prosthesis for upper-limb amputees. Biomed Signal Process Control 62:102122. https://doi.org/10.1016/j.bspc.2020.102122
Cheesborough JE, Smith LH, Kuiken TA, Dumanian GA (2015) Targeted muscle reinnervation and advanced prosthetic arms. Semin Plast Surg 29:62–72. https://doi.org/10.1055/s-0035-1544166
Fifer MS, Acharya S, Benz HL, Mollazadeh M, Crone NE, Thakor NV (2012) towards electrocorticographic control of a dexterous upper limb prosthesis. IEEE Pulse 3:38–42. https://doi.org/10.1109/MPUL.2011.2175636
AL-Quraishi MS, Elamvazuthi I, Daud SA, Parasuraman S, Borboni A (2018) EEG-based control for upper and lower limb exoskeletons and prostheses: a systematic review. Sensors (Basel). https://doi.org/10.3390/s18103342
Asghari Oskoei M, Hu H (2007) Myoelectric control systems: a survey. Biomed Signal Process Control 2:275–294. https://doi.org/10.1016/j.bspc.2007.07.009
Parker P, Englehart K, Hudgins B (2006) Myoelectric signal processing for control of powered limb prostheses. J Electromyogr Kinesiol 16:541–548. https://doi.org/10.1016/j.jelekin.2006.08.006
George JA, Davis TS, Brinton MR, Clark GA (2020) Intuitive neuromyoelectric control of a dexterous bionic arm using a modified Kalman filter. J Neurosci Methods 330:108462. https://doi.org/10.1016/j.jneumeth.2019.108462
Jiang N, Rehbaum H, Vujaklija I, Graimann B, Farina D (2014) Intuitive, online, simultaneous, and proportional myoelectric control over two degrees-of-freedom in upper limb amputees. IEEE Trans Neural Syst Rehabil Eng 22:501–510. https://doi.org/10.1109/TNSRE.2013.2278411
Milosevic B, Benatti S, Farella E (2017) Design challenges for wearable EMG applications. In: Design, Automation Test in Europe Conference Exhibition (DATE), pp 1432–1437
Liu J, Zhou P (2013) A novel myoelectric pattern recognition strategy for hand function restoration after incomplete cervical spinal cord injury. IEEE Trans Neural Syst Rehabil Eng 21:96–103. https://doi.org/10.1109/TNSRE.2012.2218832
Tavakoli M, Benussi C, Lourenco JL (2017) Single channel surface EMG control of advanced prosthetic hands. Expert Syst Appl 79:322–332. https://doi.org/10.1016/j.eswa.2017.03.012
Pancholi S, Joshi AM (2018) Portable EMG data acquisition module for upper limb prosthesis application. IEEE Sens J 18:3436–3443. https://doi.org/10.1109/JSEN.2018.2809458
Muzumdar A (2004) Powered upper limb prostheses. Springer, Berlin
Prakash A, Sharma S (2020) A low-cost system to control prehension force of a custom-made myoelectric hand prosthesis. Res Biomed Eng 36:237–247. https://doi.org/10.1007/s42600-020-00064-w
Cranny A, Cotton DPJ, Chappell PH, Beeby SP, White NM (2005) Thick-film force, slip and temperature sensors for a prosthetic hand. Meas Sci Technol 16:931–941. https://doi.org/10.1088/0957-0233/16/4/005
Engeberg ED, Meek SG (2013) adaptive sliding mode control for prosthetic hands to simultaneously prevent slip and minimize deformation of grasped objects. IEEE/ASME Trans Mechatron 18:376–385. https://doi.org/10.1109/TMECH.2011.2179061
Borisov II, Borisova OV, Krivosheev SV, Oleynik RV, Reznikov SS Prototyping of EMG-controlled prosthetic hand with sensory system. 5
Cipriani C, Controzzi M, Carrozza MC (2011) The SmartHand transradial prosthesis. J NeuroEng Rehabil 8:29. https://doi.org/10.1186/1743-0003-8-29
Furui A, Eto S, Nakagaki K, Shimada K, Nakamura G, Masuda A, Chin T, Tsuji T (2019) A myoelectric prosthetic hand with muscle synergy–based motion determination and impedance model–based biomimetic control. Sci Robot. https://doi.org/10.1126/scirobotics.aaw6339
Wang N, Lao K, Zhang X (2017) Design and myoelectric control of an anthropomorphic prosthetic hand. J Bionic Eng 14:47–59. https://doi.org/10.1016/S1672-6529(16)60377-3
Williams MR, Walter W (2015) Development of a prototype over-actuated biomimetic prosthetic hand. PLoS ONE 10:e0118817. https://doi.org/10.1371/journal.pone.0118817
bebionic hand. https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/bebionic-hand/. Accessed 21 Oct 2019
i-limb quantum | Touch Bionics. http://touchbionics.com/products/active-prostheses/i-limb-quantum. Accessed 12 Apr 2019
Michelangelo prosthetic hand. https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/michelangelo-prosthetic-hand/. Accessed 12 Apr 2019
VINCENTevolution 3. https://vincentsystems.de/en/prosthetics/vincent-evolution-3/. Accessed 12 Apr 2019
Atzori M, Müller H (2015) Control capabilities of myoelectric robotic prostheses by hand amputees: a scientific research and market overview. Front Syst Neurosci 9:162. https://doi.org/10.3389/fnsys.2015.00162
Li G, Schultz AE, Kuiken TA (2010) Quantifying pattern recognition—based myoelectric control of multifunctional transradial prostheses. IEEE Trans Neural Syst Rehabil Eng 18:185–192. https://doi.org/10.1109/TNSRE.2009.2039619
Daley H, Englehart K, Hargrove L, Kuruganti U (2012) High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control. J Electromyogr Kinesiol 22:478–484. https://doi.org/10.1016/j.jelekin.2011.12.012
Hamner SR, Narayan VG, Donaldson KM (2013) Designing for scale: development of the remotion knee for global emerging markets. Ann Biomed Eng 41:1851–1859. https://doi.org/10.1007/s10439-013-0792-8
Prakash A, Sharma S (2020) Development of an affordable myoelectric hand for transradial amputees: international journal of biomedical and clinical. Engineering 9:1–15. https://doi.org/10.4018/IJBCE.2020010101
Al-Timemy AH, Bugmann G, Escudero J, Outram N (2013) Classification of finger movements for the dexterous hand prosthesis control with surface electromyography. IEEE J Biomed Health Inform 17:608–618. https://doi.org/10.1109/JBHI.2013.2249590
Khushaba RN, Al-Timemy AH, Al-Ani A, Al-Jumaily A (2017) A framework of temporal-spatial descriptors-based feature extraction for improved myoelectric pattern recognition. IEEE Trans Neural Syst Rehabil Eng 25:1821–1831. https://doi.org/10.1109/TNSRE.2017.2687520
Chandrapal M (2012) Intelligent Assistive Knee Orthotic Device Utilizing Pneumatic Artificial Muscles
Chatfield LT, Fortune BC, McKenzie LR, Pretty CG (2018) Implementation of a particle filter to estimate torque from electromyography. IFAC-PapersOnLine 51:327–332. https://doi.org/10.1016/j.ifacol.2018.11.620
Chatfield LT, Fortune BC, McKenzie LR, Pretty CG (2019) Development of an assist-as-need controller for an upper-limb exoskeleton with voluntary torque estimate. american society of mechanical engineers digital collection
Sankai Y (2011) HAL: hybrid assistive limb based on cybernics. In: Kaneko M, Nakamura Y (eds) Robotics research. Springer, Berlin, Heidelberg, pp 25–34
Fortune BC, Pretty CG, Chatfield LT, McKenzie LR, Hayes MP (2019) Low-cost active electromyography. HardwareX 6:e00085. https://doi.org/10.1016/j.ohx.2019.e00085
Prakash A, Kumari B, Sharma S (2019) A low-cost, wearable sEMG sensor for upper limb prosthetic application. J Med Eng Technol 43:235–247. https://doi.org/10.1080/03091902.2019.1653391
De Luca CJ (1997) The use of surface electromyography in biomechanics. J Appl Biomech 13:135–163. https://doi.org/10.1123/jab.13.2.135
Gerdle B, Karlsson S, Day S, Djupsjöbacka M (1999) Acquisition, processing and analysis of the surface electromyogram. In: Windhorst U, Johansson H (eds) Modern techniques in neuroscience research. Springer, Berlin, pp 705–755
Sharma N, Prakash A, Sahi AK, Sharma N, Sharma S (2020) Multimodal sensor to measure the concurrent electrical and mechanical activity of muscles for controlling a hand prosthesis. Instrum Sci Technol. https://doi.org/10.1080/10739149.2020.1804932
Wang J, Tang L, Bronlund E (2013) Surface EMG signal amplification and filtering. Int J Comput Appl 82:15–22. https://doi.org/10.5120/14079-2073
Prakash A, Sharma S, Sharma N (2019) A compact-sized surface EMG sensor for myoelectric hand prosthesis. Biomed Eng Lett 9:467–479. https://doi.org/10.1007/s13534-019-00130-y
Farina D (2006) Interpretation of the surface electromyogram in dynamic contractions. Exerc Sport Sci Rev 34:121–127
Heywood S, Pua YH, McClelland J, Geigle P, Rahmann A, Bower K, Clark R (2018) Low-cost electromyography – Validation against a commercial system using both manual and automated activation timing thresholds. J Electromyogr Kinesiol 42:74–80. https://doi.org/10.1016/j.jelekin.2018.05.010
Tatarian K, Couceiro MS, Ribeiro EP, Faria DR (2018) Stepping-stones to Transhumanism: an EMG-controlled low-cost prosthetic hand for academia. In: 2018 International Conference on Intelligent Systems (IS). IEEE, Funchal-Madeira, Portugal, pp 807–812
Lobo-Prat J, Kooren PN, Stienen AH, Herder JL, Koopman BF, Veltink PH (2014) Non-invasive control interfaces forintention detection in active movement-assistive devices. J NeuroEng Rehabil 11:168. https://doi.org/10.1186/1743-0003-11-168
Agostini V, Knaflitz M (2012) An algorithm for the estimation of the signal-to-noise ratio in surface myoelectric signals generated during cyclic movements. IEEE Trans Biomed Eng 59:219–225. https://doi.org/10.1109/TBME.2011.2170687
Enabling The Future. In: Enabling The Future. https://enablingthefuture.org/. Accessed 20 Oct 2020
Melocchi A, Parietti F, Loreti G, Maroni A, Gazzaniga A, Zema L (2015) 3D printing by fused deposition modeling (FDM) of a swellable/erodible capsular device for oral pulsatile release of drugs. J Drug Deliv Sci Technol 30:360–367. https://doi.org/10.1016/j.jddst.2015.07.016
Pylatiuk C, Schulz S, Kargov A, Bretthauer G (2004) Two multiarticulated hydraulic hand prostheses. Artif Organs 28:980–986. https://doi.org/10.1111/j.1525-1594.2004.00014.x
Prakash A, Sharma N, Sharma S (2020) Novel force myography sensor to measure muscle contractions for controlling hand prostheses. Instrum Sci Technol 48:43–62. https://doi.org/10.1080/10739149.2019.1655441
Schoepp KR, Dawson MR, Schofield JS, Carey JP, Hebert JS (2018) Design and integration of an inexpensive wearable mechanotactile feedback system for myoelectric prostheses. IEEE J Transl Eng Health Med 6:1–11. https://doi.org/10.1109/JTEHM.2018.2866105
Fougner A, Stavdahl O, Kyberd PJ, Losier YG, Parker PA (2012) Control of upper limb prostheses: terminology and proportional myoelectric control-a review. IEEE Trans Neural Syst Rehabil Eng 20:663–677. https://doi.org/10.1109/TNSRE.2012.2196711
Lenzi T, De Rossi SMM, Vitiello N, Carrozza MC (2011) Proportional EMG control for upper-limb powered exoskeletons. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Boston, MA, pp 628–631
Sinderby C, Lindström L, Grassino AE (1995) Automatic assessment of electromyogram quality. J Appl Physiol 79:1803–1815. https://doi.org/10.1152/jappl.1995.79.5.1803
Jamal MZ, Kim K-S (2018) A finely machined toothed silver electrode surface for improved acquisition of EMG signals. In: 2018 IEEE Sensors Applications Symposium (SAS). IEEE, Seoul, pp 1–5
Sebastian F, Fu Q, Santello M, Polygerinos P (2017) Soft robotic haptic interface with variable stiffness for rehabilitation of neurologically impaired hand function. Front Robot AI. https://doi.org/10.3389/frobt.2017.00069
Zhu G, Duan X, Deng H (2013) Hybrid Force-Position Fuzzy Control for a Prosthetic Hand. In: Lee J, Lee MC, Liu H, Ryu J-H (eds) Intelligent Robotics and Applications. Springer, Berlin , pp 415–426
Geng W, Du Y, Jin W, Wei W, Hu Y, Li J (2016) Gesture recognition by instantaneous surface EMG images. Sci Rep 6:36571. https://doi.org/10.1038/srep36571
Myoelectric Speed hands. https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/myoelectric-devices-speedhands/. Accessed 12 Apr 2019
Chadwell A, Kenney L, Thies S, Galpin A, Head J (2016) The reality of myoelectric prostheses: understanding what makes these devices difficult for some users to control. Front Neurorobot. https://doi.org/10.3389/fnbot.2016.00007
Acknowledgements
The authors would like to thank the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India, for funding this project.
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Science and Engineering Research Board (SERB) [Grant No. CRG/2018/001612], Department of Science and Technology, Government of India.
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This article involves surface EMG data acquisition from various human subjects. Ethical approval was taken from the Ethical committee, Institute of medical sciences, BHU, Varanasi before performing this experiment. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Prakash, A., Sharma, S. A low-cost transradial prosthesis controlled by the intention of muscular contraction. Phys Eng Sci Med 44, 229–241 (2021). https://doi.org/10.1007/s13246-021-00972-w
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DOI: https://doi.org/10.1007/s13246-021-00972-w