This paper is in the following e-collection/theme issue:

Aging in Place (158) mHealth for Wellness, Behavior Change and Prevention (2266) Wearable Devices and Sensors (657) Sensors at Home and Domotics (48) Chronic Conditions (146) Falls and Emergency Detection with Sensors and other Technologies (20)

Published on in Vol 5 , No 2 (2022) :Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28260, first published .
Detecting Anomalies in Daily Activity Routines of Older Persons in Single Resident Smart Homes: Proof-of-Concept Study

Detecting Anomalies in Daily Activity Routines of Older Persons in Single Resident Smart Homes: Proof-of-Concept Study

Detecting Anomalies in Daily Activity Routines of Older Persons in Single Resident Smart Homes: Proof-of-Concept Study

Authors of this article:

Zahraa Khais Shahid 1, 2 Author Orcid Image ;   Saguna Saguna 1 Author Orcid Image ;   Christer Åhlund 1 Author Orcid Image
Article Authors Cited by (7) Tweetations (11) Metrics

Journals

  1. Chifu V, Pop C, Rancea A, Morar A, Cioara T, Antal M, Anghel I. Deep Learning, Mining, and Collaborative Clustering to Identify Flexible Daily Activities Patterns. Sensors 2022;22(13):4803 View
  2. Lee B, Mohan P, Chaspari T, Ryan Ahn C. Assessing Daily Activity Routines Using an Unsupervised Approach in a Smart Home Environment. Journal of Computing in Civil Engineering 2023;37(1) View
  3. Chifu V, Cioara T, Pop C, Anghel I, Demjen D, Salomie I. Identification of Daily Living Recurrent Behavioral Patterns Using Genetic Algorithms for Elderly Care. Applied Sciences 2022;12(21):11030 View
  4. Kim J, Saguna S, Åhlund C. Acceptability of a Health Care App With 3 User Interfaces for Older Adults and Their Caregivers: Design and Evaluation Study. JMIR Human Factors 2023;10:e42145 View

Books/Policy Documents

  1. Khaemba N, Traoré I, Mamun M. Artificial Intelligence for Cyber-Physical Systems Hardening. View