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Real-time EMG based prosthetic hand controller realizing neuromuscular constraint

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Abstract

Development of prosthetic hands with human-like functionality and controllability is one of the major goals in the area of rehabilitation robotics. Current developments on prosthetic hands have earned higher functionality with multiple fingers and degrees of freedom. However, the issue of time required to perform a grasp type opens avenues for improvement in its controllability. This paper reports a real-time electromyogram (EMG) based embedded controller for prosthetic hands. The focus was on development of an efficient controller in terms of grasping accuracy and time required for grasping vis-á-vis human hand neuromuscular time constraint. The controller has been tested for a prosthetic hand to grasp four objects: cricket ball, coffee mug, screw-driver box and plastic container. EMG from biceps brachii muscles during maximum voluntary contraction versus resting state was classified. With an aim for low computational complexity in the controller such that the reported work can be translated into a low cost commercial product, a finite state algorithm was used to understand user’s grasping intention. Experiments have been accomplished in four sessions, each with 20 trials, by five subjects in both sitting and standing positions. It has been found that the prosthetic hand can perform grasping with an average accuracy of 96.2 ± 2.6%. The controller enables the prosthetic hand to perform grasping operation in 250.80 ± 1.1 ms, which is comparable to the time required by human hands i.e. 300 ms and thereby satisfied the neuromuscular constraint.

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Availability of data and material

The experimental EMG data samples are available on the website of Embedded Systems and Robotics Laboratory, Tezpur University (http://www.tezu.ernet.in/erl/sm.html).

Code availability

The codes are available on the website of Embedded Systems and Robotics Laboratory, Tezpur University (http://www.tezu.ernet.in/erl/sm.html).

Change history

  • 16 February 2022

    The original version is updated due to incorrect link provided in the section "Availability of data and material" and "Code availability".

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Acknowledgements

The support received under the ASEAN-India R&D Scheme, SERB-Department of Science and Technology (DST) for the project No. CRD/2018/000049 and NECBH, Department of Biotechnology (DBT) for the project No. NECBH/2019-20/144, Government of India are acknowledged. The authors also acknowledge the financial support received for the project entitled ”Development of A Cost-Effective EMG Controlled Prosthetic Hand for Multiple Grasp Patterns” under IHFC-IIT Delhi, DST, Government of India.

Funding

The research leading to these results received funding under ASEAN-India R&D Scheme, SERB-DST for the project No. CRD/2018/000049, NECBH, DBT for the project No. NECBH/2019-20/144 and project entitled ”Development of A Cost-Effective EMG Controlled Prosthetic Hand for Multiple Grasp Patterns” under IHFC-IIT Delhi, DST, Government of India.

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Authors and Affiliations

  1. Embedded Systems and Robotics Laboratory, Tezpur University, Tezpur, 784028, India

    Nayan M. Kakoty, Lakhyajit Gohain & Amlan Jyoti Kalita

  2. Intellectual Property Right Cell, Tezpur University, Tezpur, 784028, India

    Juri Borborua Saikia

  3. TIMeS Hospital, Tezpur, 784001, India

    Satyajit Borah

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  1. Nayan M. Kakoty
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  2. Lakhyajit Gohain
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  3. Juri Borborua Saikia
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  4. Amlan Jyoti Kalita
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Contributions

Experiments, analysis and drafting of the paper were performed by Lakhyajit Gohain and Nayan M. Kakoty. Satyjit Borah contributed in the the process of muscle site selection for EMG acquisition, EMG acquisition and in deriving physical significance on the acquired EMG. Juri Borborua Saikia helped in writing of the introduction section. Final review and editing of the manuscript was by Amlan Jyoti Kalita. All authors read and approved the final manuscript.

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Correspondence to Amlan Jyoti Kalita.

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The authors declared that they have no conflict of interest.

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The experiments were accomplished as per the permission of the institutional ethical committee.

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Written consent was obtained from each individual participants included in the study.

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The authors consent to publication of the work in International Journal of Intelligent Robotics and Applications. The authors affirm that human research participants provided informed consent for publication of the images in Figs. 2 ,8 and 9.

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Kakoty, N.M., Gohain, L., Saikia, J.B. et al. Real-time EMG based prosthetic hand controller realizing neuromuscular constraint. Int J Intell Robot Appl 6, 530–542 (2022). https://doi.org/10.1007/s41315-021-00221-z

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