Flexion Detection Algorithm’s Applied to Classifying Joint Movements Based on Fiber Sensors

Abstract

Telepresence is a necessity in today’s world, and it is very important to develop it with great precision for assisted robot. Analyzed the movement during the flexion in joins is important to adapt them to robots. This paper presents the signal processing to synthetize the finger movements applied to service robot. Fiber optics sensor is used to detect the angle in the join, after that Recursive Least Square algorithm was carried out to reduce the noise in the signal. Furthermore, statistical feature extraction and machine learning algorithm was performed to classifying the thresholds angle in the join. Comparative analysis was developed to select the best algorithm to detect the angle in the join.