Fall detection from a manual wheelchair: preliminary findings based on accelerometers using machine learning techniques-Reference-Cited by-同舟云学术

Fall detection from a manual wheelchair: preliminary findings based on accelerometers using machine learning techniques

Published:2023-02-28 Issue:6 Volume:35 Page:523-531
ISSN:1040-0435
Container-title:Assistive Technology
language:en
Short-container-title:Assistive Technology

Author:

Abou Libak¹^ORCID,Fliflet Alexander²,Presti Peter³,Sosnoff Jacob J.⁴,Mahajan Harshal P.²⁵^ORCID,Frechette Mikaela L.²,Rice Laura A.²⁵^ORCID

Affiliation:

1. Department of Physical Medicine & Rehabilitation, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA

2. Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

3. Interactive Media Technology Center, Georgia Institute of Technology, Atlanta, Georgia, USA

4. Department of Physical Therapy and Rehabilitation Science, School of Health Professions, University of Kansas Medical Center, Kansas City, Kansas USA

5. Center for Health, Aging and Disability, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

Funder

National Institute on Disability, Independent Living, and Rehabilitation Research

Technology to Support Aging

Publisher

Informa UK Limited

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation

Link

https://www.tandfonline.com/doi/pdf/10.1080/10400435.2023.2177775

Reference26 articles.

1. Effectiveness of Physical Therapy Interventions in Reducing Fear of Falling Among Individuals With Neurologic Diseases: A Systematic Review and Meta-analysis