Older adults are at risk of falling, which is a major threat to their quality of life.
Some fall risk factors which increase the likelihood that a person will fall, have been identified. Variables used here are demographics, anthropometric measurements, gait spatiotemporal parameters, and SPPB, MMSE and POMA-G test scores.
The aim of this project is to develop and train predictive models to assess and predict risk of falling in older adults. This will provide information to clinicians how likely that a patient with specific features (demographics, gait parameters, etc) that he/she will fall.
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