Machine learning model predicts fall risk

Image: The Ottawa Hospital Rehabilitation Centre (TOHRC) Walk Test app was used to collect data in this study. Left: Participants complete a walking test with a smartphone connected to their lower back. Right: The user interface of the TOHRC Walk Test App after the walk test is complete.
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Image credit: Juneau P et al, 2022, PLOS Digital Health, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

In your articles, please use this URL to provide access to free articles PLOS Digital Health: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000088

Article title: Automated step count detection using a 6-minute walk test smartphone sensor for fall risk classification in lower-extremity amputees

author country: Canada, Slovenia

funds: This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). NSERC CREATE READI: RGPIN-2019-04106, EDL, https://carleton.ca/readi/ NSERC CREATE BEST 482728-2016-CREAT, NB, http://create-best.com/#focus No role for funders In study design, data collection and analysis, publication decisions, or manuscript preparation.


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