Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43726, first published .
An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

Journals

  1. Kowahl N, Shin S, Barman P, Rainaldi E, Popham S, Kapur R. Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-Worn Sensor in Healthy Individuals: Performance Characterization Study. JMIR Human Factors 2023;10:e48270 View
  2. de Graaf D, de Vries N, van de Zande T, Schimmel J, Shin S, Kowahl N, Barman P, Kapur R, Marks Jr W, van 't Hul A, Bloem B. The ADAPT-study protocol: measuring physical functioning using wearable sensors in Parkinson’s Disease and COPD (Preprint). JMIR Research Protocols 2023 View
  3. Shin S, Kowahl N, Hansen T, Ling A, Barman P, Cauwenberghs N, Rainaldi E, Short S, Dunn J, Shandhi M, Shah S, Mahaffey K, Kuznetsova T, Daubert M, Douglas P, Haddad F, Kapur R. Real-world walking behaviors are associated with early-stage heart failure: a Project Baseline Health Study. Journal of Cardiac Failure 2024 View

Books/Policy Documents

  1. Asiamah N, Danquah E, Sghaier S, Mensah H, Kouveliotis K. Sustainable Neighbourhoods for Ageing in Place. View