Identifying irregular activity sequences : an application to passive household monitoring

Gillam, Jess and Killick, Rebecca and Taylor, Simon and Heal, Jack and Norwood, Ben (2023) Identifying irregular activity sequences : an application to passive household monitoring. Journal of the Royal Statistical Society: Series C (Applied Statistics), 72 (3). pp. 519-543. ISSN 0035-9254

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Abstract

Approximately one in five people will live to see their 100th birthday due to advancements in modern medicine and other factors. Over 65’s constitute 42% of elective admissions and 43% of emergency admissions to hospitals. Increasingly, people are turning to technology to help improve health and care of the elderly. There is mixed evidence of the success of wearables in older populations with a key barrier being adoption. In contrast, passive sensors such as infra-red motion and plug sensors have had more success. These passive sensors give us a sequence of categorical “trigger” events throughout the day. This paper proposes a method for detecting subtle changes in sequences while taking account of the natural day-to-day variability and differing numbers of “trigger” events per day.

Item Type:
Journal Article
Journal or Publication Title:
Journal of the Royal Statistical Society: Series C (Applied Statistics)
Uncontrolled Keywords:
Research Output Funding/yes_externally_funded
Subjects:
?? statistics, probability and uncertaintystatistics and probabilitycategorical datahome sensingroutinesyes - externally fundedyesstatistics and probabilitystatistics, probability and uncertainty ??
ID Code:
195372
Deposited By:
Deposited On:
09 Jun 2023 12:40
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 23:51