Learn More
The aim of this novel work is to recognize 12 health care linked gestures from young individuals of 20-40 years of age group. Due to constant sitting in a specific posture for deskbound jobs, functioning of joints and muscles of persons are deteriorated. The scope of this work is to recognize the early stage symptoms of those physical disorders and notify(More)
Deformability and texture are two unique object characteristics which are essential for appropriate surface recognition by tactile exploration. Tactile sensation is required to be incorporated in artificial arms for rehabilitative and other human–computer interface applications to achieve efficient and human-like manoeuvring. To accomplish the same, surface(More)
This work is a preliminary study towards developing an alternative communication channel for conveying shape information to aid in recognition of items when tactile perception is hindered. Tactile data, acquired during object exploration by sensor fitted robot arm, are processed to recognize four basic geometric shapes. Patterns representing each shape,(More)
In this work, we analyse the Electroencephalogram (EEG) and tactile signals acquired during dynamic exploration of objects of seven different geometric shapes and observe that classification performance using features from both the domains together is better than using the either alone. Classification is done by Support Vector Machine and Naïve Bayesian(More)
A simple method to detect gestures revealing muscle and joint pain is described in this paper. Kinect Sensor is used for data acquisition. This sensor only processes twenty joint coordinates in three dimensional space for feature extraction. The recognition part is achieved using a neural network optimized by Levenberg-Marquardt learning rule. A high(More)
  • 1