{"title":"Ambient assessment of daily activity and gait velocity","authors":"L. Walsh, B. Greene, Adrian Burns, C. N. Scanaill","doi":"10.4108/ICST.PERVASIVEHEALTH.2011.246077","DOIUrl":null,"url":null,"abstract":"This paper describes novel ambient technologies for domestic gait velocity measurement and in-home daily activity monitoring. This was achieved through low cost, easily deployable passive infrared motion detectors and an unobtrusive wireless sensor network. This system was deployed in the houses of eight older adults (1 faller; 7 non-fallers) living independently over eight weeks. Inter-daily gait velocity and daily activity metrics were derived from this data set. Consistent daily rhythms were found, however no correlations to clinical or daily ethnographic data were found. Long-term data collection, particularly surrounding serious life events, would validate the ability of this system to highlight deviations in health status. This paper provides a framework for collecting, analysing and interpreting gait velocity and daily activity data.","PeriodicalId":444978,"journal":{"name":"2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops","volume":"22 13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/ICST.PERVASIVEHEALTH.2011.246077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper describes novel ambient technologies for domestic gait velocity measurement and in-home daily activity monitoring. This was achieved through low cost, easily deployable passive infrared motion detectors and an unobtrusive wireless sensor network. This system was deployed in the houses of eight older adults (1 faller; 7 non-fallers) living independently over eight weeks. Inter-daily gait velocity and daily activity metrics were derived from this data set. Consistent daily rhythms were found, however no correlations to clinical or daily ethnographic data were found. Long-term data collection, particularly surrounding serious life events, would validate the ability of this system to highlight deviations in health status. This paper provides a framework for collecting, analysing and interpreting gait velocity and daily activity data.