Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49587, first published .
Association of Prospective Falls in Older People With Ubiquitous Step-Based Fall Risk Parameters Calculated From Ambulatory Inertial Signals: Secondary Data Analysis

Association of Prospective Falls in Older People With Ubiquitous Step-Based Fall Risk Parameters Calculated From Ambulatory Inertial Signals: Secondary Data Analysis

Association of Prospective Falls in Older People With Ubiquitous Step-Based Fall Risk Parameters Calculated From Ambulatory Inertial Signals: Secondary Data Analysis

Journals

  1. Abiad N, Houdry E, El Khoury C, Renaudin V, Robert T. A method for calculating fall risk parameters from discrete stride time series regardless of sensor placement. Gait & Posture 2024;111:182 View
  2. Codina M, Castells-Rufas D, Torrelles M, Carrabina J. Technoeconomic Analysis for Deployment of Gait-Oriented Wearable Medical Internet-of-Things Platform in Catalonia. Information 2024;15(5):288 View
  3. van Gameren M, Voorn P, Bossen D, Hoozemans M, Bruijn S, Bosmans J, Visser B, Pijnappels M. The Short Physical Performance Battery does not correlate with daily life gait quality and quantity in community-dwelling older adults with an increased fall risk. Gait & Posture 2024;114:78 View
  4. Wang B, Liu Y, Lu A, Wang C. Application of wearable sensors in constructing a fall risk prediction model for community-dwelling older adults: A scoping review. Archives of Gerontology and Geriatrics 2025;129:105689 View

Books/Policy Documents

  1. Caragiuli M, Brunzini A, Massera C, Candelari M, Germani M. HCI International 2024 – Late Breaking Papers. View