Elderly care: activities of daily living classification with an S band radar. Issue 21 (7th October 2019)

• Record Type: Journal Article
• Authors: Shrestha, Aman; Le Kernec, Julien; Fioranelli, Francesco; Lin, Yier; He, Qian; Lorandel, Jordane; Romain, Olivier
• Is Part Of: Journal of engineering. Volume 2019:Issue 21(2019)
• Page Start: 7601
• Page End: 7606
• Publication Date: 2019-10-07
• Subjects: geriatrics -- pattern classification -- data privacy -- health care -- radar -- feature selection; feature selection -- elderly care -- daily living classification -- privacy -- activity detection -- human movement classification -- S band radar; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2019.0561
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : Falls in the elderly represent a serious challenge for the global population. To address it, monitoring of daily living has been suggested, with radar emerging to be a useful platform for it due to its various benefits with acceptance and privacy. Here, we show results from the use of an S band radar for activity detection and the importance of selecting specific frequency bins to improve its suitability for human movement classification. The use of feature selection to improve detection of key activities such as falls has been presented. Initial results of 65% are improved to 85% and further to 90% with the aforementioned methods.