Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors  

作　　者：Hammad Rustam Muhammad Muneeb Suliman A.Alsuhibany Yazeed Yasin Ghadi Tamara Al Shloul Ahmad Jalal Jeongmin Park 

机构地区：[1]Department of Computer Science,Air University,Islamabad,44000,Pakistan [2]Department of Computer Science,College of Computer,Qassim University,Buraydah,51452,Saudi Arabia [3]Department of Computer Science and Software Engineering,Al Ain University,Al Ain,15551,UAE [4]Department of Humanities and Social Science,Al Ain University,Al Ain,15551,UAE [5]Department of Computer Engineering,Korea Polytechnic University,237 Sangidaehak-ro Siheung-si,Gyeonggi-do,15073,Korea

出　　处：《Computers, Materials & Continua》2023年第4期2331-2346,共16页计算机、材料和连续体（英文）

基　　金：supported by a grant (2021R1F1A1063634)of the Basic Science Research Program through the National Research Foundation (NRF)funded by the Ministry of Education,Republic of Korea.

摘　　要：Hand gesture recognition (HGR) is used in a numerous applications,including medical health-care, industrial purpose and sports detection.We have developed a real-time hand gesture recognition system using inertialsensors for the smart home application. Developing such a model facilitatesthe medical health field (elders or disabled ones). Home automation has alsobeen proven to be a tremendous benefit for the elderly and disabled. Residentsare admitted to smart homes for comfort, luxury, improved quality of life,and protection against intrusion and burglars. This paper proposes a novelsystem that uses principal component analysis, linear discrimination analysisfeature extraction, and random forest as a classifier to improveHGRaccuracy.We have achieved an accuracy of 94% over the publicly benchmarked HGRdataset. The proposed system can be used to detect hand gestures in thehealthcare industry as well as in the industrial and educational sectors.

关 键 词：Genetic algorithm human locomotion activity recognition human–computer interaction human gestures recognition principal hand gestures recognition inertial sensors principal component analysis linear discriminant analysis stochastic neighbor embedding 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]