Abstract
Purpose
In order to achieve stable and dexterous grasping of objects, prehension force control is quite a significant parameter for prosthetic hands. Commercially available hands such as bebionic, i-limb quantum and Michelangelo offer the precise grasping capability to perform activities of daily living (ADLs). However, the cost of such hands is too expensive for amputees residing in low-income countries.
Methods
This paper introduces a low-cost, simple and efficient system for controlling the prehension force of a self-designed myoelectric prosthetic hand. A hand prototype was developed employing 3D printing technology and an intrinsic actuation approach. The hand fingers were equipped with a pre-calibrated force sensor for the online estimation of the grasp force. A closed-loop proportional-derivative (PD) based position control system was designed considering actuator as plant, electromyography (EMG) as a reference and grasp force as a feedback signal.
Results
The results showed highly improved parameters, i.e. overshoot, offset and settling time of the proposed system than a simple open-loop system. These parameters guarantee faster closing of hand fingers and the production of accurate prehension force during finger-object interaction.
Conclusion
Further, the myoelectric hand with a developed control scheme was successfully tested on five different transradial amputees for performing precise and faster grasping of different shaped objects.
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References
Asghari Oskoei M, Hu H. Myoelectric control systems—a survey. Biomed Signal Process Control. 2007;2(4):275–94.
Bahrami Moqadam S, Elahi SM, Mo A, Zhang W. Hybrid control combined with a voluntary biosignal to control a prosthetic hand. Robotics Biomim. 2018;5(1):4.
Bebionic hand [Internet]. [cited 2019 Oct 21]. Available from: https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/bebionic-hand/
Belter JT, Segil JL, Dollar AM, Weir RF. Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review. J Rehabil Res Dev. 2013;50(5):599–618.
Bordignon V, Campestrini L. Data-driven PID control tuning for disturbance rejection in a hierarchical control architecture 2018;6.
Borisov II, Borisova OV, Krivosheev SV, Oleynik RV, Reznikov SS. Prototyping of EMG-controlled prosthetic hand with sensory system. IFAC-PapersOnLine. 2017;50(1):16027–16031.
Chappell PH, Elliott JA. Contact force sensor for artificial hands with a digital interface for a controller. Meas Sci Technol. 2003;14(8):1275–9.
Cranny A, Cotton DPJ, Chappell PH, Beeby SP, White NM. Thick-film force, slip and temperature sensors for a prosthetic hand. Meas Sci Technol. 2005;16(4):931–41.
Deimel R, Brock O. A novel type of compliant and underactuated robotic hand for dexterous grasping. Int J Robot Res. 2016;35(1–3):161–85.
e-NABLE Phoenix Hand v2 by EnableCommunityFoundation - Thingiverse [Internet]. [cited 2019 Jan 28]. Available from: https://www.thingiverse.com/thing:1453190
Engeberg ED, Meek SG. Adaptive sliding mode control for prosthetic hands to simultaneously prevent slip and minimize deformation of grasped objects. IEEE/ASME Trans Mech. 2013;18(1):376–85.
Engeberg ED, Meek SG, Minor MA. Hybrid force–velocity sliding mode control of a prosthetic hand. IEEE Trans Biomed Eng. 2008;55(5):1572–81.
Englehart K, Hudgins B. A robust, real-time control scheme for multifunction myoelectric control. IEEE Trans Biomed Eng. 2003;50(7):848–54.
Farrell TR, Weir RF. The optimal controller delay for myoelectric prostheses. IEEE Trans Neural Syst Rehabil Eng. 2007;15(1):111–8.
Fougner A, Stavdahl O, Kyberd PJ, Losier YG, Parker PA. Control of upper limb prostheses: terminology and proportional myoelectric control-a review. IEEE Trans Neural Syst Rehabil Eng. 2012;20(5):663–77.
Geethanjali P. Myoelectric control of prosthetic hands: state-of-the-art review. Med Devices (Auckl). 2016;9:247–55.
Ghazali R, Saad MZ, Hussien SYS, Jali MH, Zohedi FN, Izzuddin TA. Intelligent controller design for multifunctional prosthetics hand. Int J Mech Eng Robot Res. 2017;6(6):495–501.
Godfrey SB, Zhao KD, Theuer A, Catalano MG, Bianchi M, Breighner R, et al. The SoftHand Pro: functional evaluation of a novel, flexible, and robust myoelectric prosthesis. PLoS ONE. 2018;13(10):e0205653.
Herle S, Man S, Lazea G, Raica P. Myoelectric control strategies for a human upper limb prosthesis. J Control Eng Appl Inf. 2012;14(1):58–66.
Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, et al. European recommendations for surface electromyography. RRD. 1999;8(2):13–54.
Hudgins B, Parker P, Scott RN. A new strategy for multifunction myoelectric control. IEEE Trans Biomed Eng. 1993;40(1):82–94.
i-limb quantum [Internet]. [cited 2019 Apr 12]. Available from: http://touchbionics.com/products/active-prostheses/i-limb-quantum
Kargov A, Pylatiuk C, Martin J, Schulz S, Döderlein L. A comparison of the grip force distribution in natural hands and in prosthetic hands. Disabil Rehabil. 2004;26(12):705–11.
Lenzi T, De Rossi SMM, Vitiello N, Carrozza MC. Proportional EMG control for upper-limb powered exoskeletons. 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Boston, MA: IEEE; 2011. p. 628–31.
Li G, Schultz AE, Kuiken TA. Quantifying pattern recognition—based myoelectric control of multifunctional transradial prostheses. IEEE Trans Neural Syst Rehabil Eng. 2010;18(2):185–92.
Motion Control, Utah arm myoelectric prosthesis [Internet]. [cited 2019 Oct 21]. Available from: http://www.utaharm.com/ua3-plus-myoelectric-arm.php
Muzumdar A. Powered upper limb prostheses: control, implementation and clinical application; 11 tables. Springer Science & Business Media; 2004.
Myoelectric Speed hands [Internet]. [cited 2019 Apr 12]. Available from: https://www.ottobockus.com/prosthetics/upper-limb-prosthetics/solution-overview/myoelectric-devices-speedhands/
Parker P, Englehart K, Hudgins B. Myoelectric signal processing for control of powered limb prostheses. J Electromyogr Kinesiol. 2006;16(6):541–8.
Prakash A, Sharma S. Development of an affordable myoelectric hand for transradial amputees. Int J Biomed Clin Eng. 2020;9(1):1–15.
Prakash A, Kumari B, Sharma S. A low-cost, wearable sEMG sensor for upper limb prosthetic application. J Med Eng Technol. 2019a;15:1–13.
Prakash A, Sharma N, Sharma S. Novel force myography sensor to measure muscle contractions for controlling hand prostheses. Instrum Sci Technol. 2019b;21:1–20.
Prakash A, Sharma S, Sharma N. A compact-sized surface EMG sensor for myoelectric hand prosthesis. Biomed Eng Lett. 2019c;9(4):467–79.
Schoepp KR, Dawson MR, Schofield JS, Carey JP, Hebert JS. Design and integration of an inexpensive wearable mechanotactile feedback system for myoelectric prostheses. IEEE J Transl Eng Health Med. 2018;6:1–11.
Schwarz C. The slip hypothesis: tactile perception and its neuronal bases. Trends Neurosci. 2016;39(7):449–62.
Sebastian F, Fu Q, Santello M. Polygerinos P soft robotic haptic interface with variable stiffness for rehabilitation of neurologically impaired hand function. Frontiers in Robotics and AI. 2017;4:69.
Slade P, Akhtar A, Nguyen M, Bretl T. Tact: design and performance of an open-source, affordable, myoelectric prosthetic hand. 2015 IEEE International Conference on Robotics and Automation (ICRA). 2015. p. 6451–6.
Sono TSP, Menegaldo LL. Myoelectric hand prosthesis force control through servo motor current feedback. Artif Organs. 2009 Oct;33(10):871–6.
Ten Kate J, Smit G, Breedveld P. 3D-printed upper limb prostheses: a review. Disabil Rehabil Assist Technol. 2017;12(3):300–14.
Wada T, Ishikawa M, Kitayoshi R, Maruta I, Sugie T. Practical modeling and system identification of R/C servo motors. 2009 IEEE Control Applications, (CCA) Intelligent Control, (ISIC). 2009. p. 1378–83.
Wang N, Lao K, Zhang X. Design and myoelectric control of an anthropomorphic prosthetic hand. J Bionic Eng. 2017;14(1):47–59.
Zhu G, Duan X, Deng H. Hybrid force-position fuzzy control for a prosthetic hand. In International Conference on Intelligent Robotics and Applications 2013 Sep 25 (pp. 415-426). Springer, Berlin, Heidelberg.
Zollo L, Di Pino G, Ciancio AL, Ranieri F, Cordella F, Gentile C, et al. Restoring tactile sensations via neural interfaces for real-time force-and-slippage closed-loop control of bionic hands. Science robotics. 2019;4(27):eaau9924.
Acknowledgements
The authors would like to thank the Design Innovation Centre, Indian Institute of Technology (BHU) for funding this project.
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This research work was funded by Design Innovation Centre, Indian Institute of Technology (BHU).
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This article does not contain any studies with animals performed by any of the authors.
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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 system to control prehension force of a custom-made myoelectric hand prosthesis. Res. Biomed. Eng. 36, 237–247 (2020). https://doi.org/10.1007/s42600-020-00064-w
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DOI: https://doi.org/10.1007/s42600-020-00064-w