Indoor non‐rhythmic human motion classification using a frequency‐modulated continuous‐wave radar. Issue 20 (30th August 2019)

• Record Type: Journal Article
• Authors: Zou, Yu; Ding, Chuanwei; Hong, Hong; Li, Changzhi; Zhu, Xiaohua
• Is Part Of: Journal of engineering. Volume 2019:Issue 20(2019)
• Page Start: 6928
• Page End: 6930
• Publication Date: 2019-08-30
• Subjects: CW radar -- feature extraction -- learning (artificial intelligence) -- FM radar -- pattern classification -- Doppler radar -- indoor environment -- echo; indoor nonrhythmic human motion classification -- frequency‐modulated continuous‐wave radar -- indoor scenario -- range feature extraction -- Doppler feature extraction -- echo signals -- machine learning classifier subspace K‐nearest neighbour -- nonrhythmic motion recognition; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2019.0560
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Human motion classification is widely used in intelligent house, surveillance, search and rescue operation, intelligent house, and elder monitoring. In this study, a frequency‐modulated continuous‐wave radar is utilised to classify non‐rhythmic human motion in an indoor scenario. Both the range and Doppler features are extracted from echo signals for a machine learning classifier subspace K ‐nearest neighbour. Extensive experiments demonstrate its feasibility, and an accuracy rate of 94.2% was achieved in recognition of eight typical non‐rhythmic motions.