• Toshesh Meena
• Vidhi sharma
• Sushil Jhakar
• Sunil Kumar Sharma

This paper describes the development of a portable system using Raspberry Pi 3B+ system on chip platform for physiological signal acquisition and processing. For programming Python language is used because of availability of large number of open-source libraries and multi platform compatibility. This portable system along with processed results can be used for designing graphical interfaces for effective vital signal analysis and diseases diagnosis. Moreover, it shows a lot of scope for developing effective human machine interface. For application demonstration we use Python libraries for acquisition and processing of surface electromyography (SEMG) data. Obtained results are used to show a comparison between SEMG data for six different forearm exercises. Along with that we also demonstrate human machine interface development by controlling servos (representing actuators in prosthetic) using SEMG data.

Surface electromyography, Raspberry Pi 3B+, Myoware SEMG sensor, Python programming, Physiological signal.

"Raspberry PI based electromyography signal acquisition and processing system", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.69-75, April-2019, Available :http://www.jetir.org/papers/JETIR1904E09.pdf

"Raspberry PI based electromyography signal acquisition and processing system", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp69-75, April-2019, Available at : http://www.jetir.org/papers/JETIR1904E09.pdf