Open AccessResearch on intelligent perception and human activity monitoring for people with inconvenient movement
Author(s) -
Tianping Zhang,
Xiaoping Tang,
LI Li-jie
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1883/1/012177
Subject(s) - activity recognition , acceleration , computer science , state (computer science) , perception , term (time) , domain (mathematical analysis) , time domain , artificial intelligence , window (computing) , sliding window protocol , real time computing , computer vision , human–computer interaction , psychology , algorithm , mathematics , classical mechanics , quantum mechanics , neuroscience , operating system , mathematical analysis , physics
Aiming at the problems of various sensors, complex recognition algorithm poor implement ability and real-time performance in current human activity state recognition methods, a human activity monitor based on single three-axis acceleration sensor is designed. By collecting acceleration data of human waist, using sliding time window method to extract time domain features, four active states are identified: long-term violent active state. Long-term static state, fall state and normal active state. The technical development and the existing difficulties and problems are discussed for future related research.