Abstract
The rehabilitation process for the physically challenged people is a real challenge and concern where technology has not yet reached all sections of the society. This paper presents a novel and a low cost multi finger Robotic prosthetic hand based on the principle of Electromyography (EMG). A three channel EMG sensor is placed across the forearm to detect the voluntary actions of the superficial muscles in the forearm. The low frequency interference and noise in the signal was removed using sensor module that eliminates the need for high end processor and bringing down the cost. The unique nature of this prototype is that, it is adaptable to different people just by adjusting a potentiometer in the sensor module. The proposed prototype of the robotic prosthetic hand is a low cost, non-invasive, painless solution for prosthesis which is capable of performing some basic actions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jun-Furukawa, Tomoyuki Noda.: Estimating Joint Movements from Observed EMG signals with multiple electrodes under Sensor Failure Situations towards safe assistive robot control. IEEE International Conference on Robotics and Automation(ICRA), Washington State Convention Centre (2015).
T. R. Farrell and R. F. Weir.: The optimal controller delay for myoelectric prostheses. IEEE Trans. Neural Syst. Rehabil. Eng., vol. 15, no. 1, pp. 111–118 (2007).
D. Wang, K.M. Lee, J. Guo, and C. J. Jang.: Adaptive knee joint exoskeleton based on biological geometries. IEEE/ASME Trans. Mechatronics, vol. 19, no. 4, pp. 1268–1278 (2014).
P. Geethanjali and K.K. Ray.: A Low-Cost Real-Time Research Platform for EMG Pattern Recognition-Based Prosthetic Hand. IEEE/ASME Trans. Mechatronics, vol. 20, no. 4, pp. 1948–1955 (2015).
Carlo J. De Luca.: Surface Electromyography: Detection and Recording. DelSys Incorporated, (2002).
Pradeep Shenoy, Kai J. Miller, Beau Crawford, and Rajesh P. N. Rao.: Online Electromyographic Control of a Robotic Prosthesis. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 55, NO. 3, (2008).
L. Eriksson, F. Sebelius, and C. Balkenius: Neural control of a virtual prosthesis. presented at the ICANN, Skoevde, Sweden, (1998).
Andrea Merlo and Isabella Campanini.: Technical Aspects of Surface Electromyography for Clinicians. The Open Rehabilitation Journal, 3, 98–109 (2010).
C.Pylatiuk, M. Müller-Riederer, A. Kargov, S. Schulz, O. Schill, M. Reischl and G. Bretthauer.: Comparison of Surface EMG Monitoring Electrodes for Long-term Use in Rehabilitation Device Control. IEEE 11th International Conference on Rehabilitation Robotics, Kyoto International Conference Center, Japan (2009).
Ruchika, Shalini Dhingra.: An Explanatory Study of the Parameters to Be Measured from EMG Signal. International Journal of Engineering and Computer Science ISSN: 2319–7242 Volume 2 Issue 1, Page No. 207–213 (2014).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Koushik, B. et al. (2017). Signal Condition and Acquisition System for a Low Cost EMG Based Prosthetic Hand. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Computer Communication, Networking and Internet Security. Lecture Notes in Networks and Systems, vol 5. Springer, Singapore. https://doi.org/10.1007/978-981-10-3226-4_37
Download citation
DOI: https://doi.org/10.1007/978-981-10-3226-4_37
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3225-7
Online ISBN: 978-981-10-3226-4
eBook Packages: EngineeringEngineering (R0)