Elderly care: activities of daily living classification with an S band radar

The Journal of Engineering

Julien Le Kernec¹  Francesco Fioranelli¹  Aman Shrestha¹  Qian He²  Yier Lin²  Olivier Romain³  Jordane Lorandel³ 

[1] Communication, Sensing and Imaging group, School of Engineering, University of Glasgow;School of Information and Electronics, University of Electronic Science and Technology of China;Université Cergy-Pontoise;

关键词: 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;   

DOI  :  10.1049/joe.2019.0561

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown