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Citation |
Ziegl A, Hayn D, Kastner P, Loffler K, Weidinger L, Brix B, Goswami N, Schreier G. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2020; 2020: 808-811. |
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Copyright |
(Copyright © 2020, IEEE (Institute of Electrical and Electronics Engineers)) |
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DOI |
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PMID |
33018108 |
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Abstract |
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. Language: en |