Frailty and falls are the main causes of morbidity and disability in elderly people. The Timed Up-and-Go (TUG) test has been proposed as an appropriate method for evaluating elderly individuals' risk of falling. To analyze the TUG's potential for falls prediction, we conducted a clinical study with participants aged ≥ 65 years, living in nursing homes. We harvested 138 TUG recordings with the information, if patients used a walking aid or not and developed a method to predict the use of walking aids using a Random Forest Classifier for ultrasonic based TUG test recordings. We achieved a high accuracy with an Area Under the Curve (AUC) of 96,9% using a 20% leave out evaluation strategy. Automated collection of structured data from TUG recordings - like the use of a walking aid - may help to improve fall risk tools in future.
|Titel||2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)|
|Publikationsstatus||Veröffentlicht - 2020|
|Veranstaltung||Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) - |
Dauer: 20 Juli 2020 → 24 Juli 2020
|Konferenz||Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)|
|Zeitraum||20/07/20 → 24/07/20|
- Exploration of Digital Health