This paper is published in Volume 2, Issue 4, 2017
Area
Bio Engineering
Author
Saikaran Praveen, Siva M P, Vijay Chandrasekar C K, M Maria Dominic Savio
Org/Univ
SRM University, Tamil Nadu, India
Pub. Date
29 April, 2017
Paper ID
V2I4-1195
Publisher
Keywords
Myoelectric signals, Signal Processing, Muscle Powered, Human-Robot Interface, Hand Prosthesis, EMG-Based Control, Logical Programs.

Citationsacebook

IEEE
Saikaran Praveen, Siva M P, Vijay Chandrasekar C K, M Maria Dominic Savio. Bionic Arm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARnD.com.

APA
Saikaran Praveen, Siva M P, Vijay Chandrasekar C K, M Maria Dominic Savio (2017). Bionic Arm. International Journal of Advance Research, Ideas and Innovations in Technology, 2(4) www.IJARnD.com.

MLA
Saikaran Praveen, Siva M P, Vijay Chandrasekar C K, M Maria Dominic Savio. "Bionic Arm." International Journal of Advance Research, Ideas and Innovations in Technology 2.4 (2017). www.IJARnD.com.

Abstract

Functional prosthetics are the most sought after solutions to any physical trauma which leads to amputation of the limbs. In this technology, we aim to combine leading sensing techniques to use the user’s residual limb to power the prosthesis and advanced processing techniques to ensure optimum operation. The already present prosthesis either serve aesthetic purposes or are dependent on invasive surgery which complicates the integration of the system. The two main points to note in functional prosthetics is choosing the best sensing technique among the many present today and also arriving at the best possible way to process these signals to power the prosthetic i.e. the bionic arm. The main objective of this project is to design a low-cost Bionic Arm using myoelectric signal sensing and advanced signal processing. The main aim of this project is to provide an advanced model of the Bionic arm that can restore natural movement to all those who have undergone upper limb amputations, at an effective cost. The proposed model senses the muscle movement of the user and powers the artificial hand in real time, thus blurring the lines between physical ability and disability.