Automate Appliances via Gestures Recognition for Elderly Living Assistance

Abstract

Smart homes have grown in popularity not only as a luxury but also because of the numerous benefits they provide. In this research, a home automation system is developed for the elders because as the number of elders rises, so does the probability that patients will develop geriatric problems, which necessitates society to address the issue. It is especially beneficial for senior citizens and disabled youngsters. Many research and innovation are conducting on in the field of gestures recognition. In this project, home automation is performed through the use of gestures to control appliances and contradicting the computer vision approaches as an elder person is not capable for ensuring the environment for the computer vision techniques as it requires proper lightning conditions and angle to ensure the parameters. Sensor embedded Hand glove that collects hand motions has been discussed in this study. The wearable device detects and records tilting, rotation, and acceleration of the hand movement using accelerometers and gyroscopes. Our proposed human gestures recognition (HGR) system recognizes nine different hand gestures taken from benchmarked dataset. We used a combination of features extraction algorithms and a random forest classifier to compare our system's performance with other well-known classifiers. We have achieved an accuracy of 94% over the benchmark HGR dataset. Experiments have shown that the proposed approach has the capability to recognize gestures for controlling home appliances and can be used in healthcare, residences, offices, and educational environments.