Frailty is one of the major problems associated with an aging society. Therefore, frailty assessment tools which support early detection and autonomous monitoring of the frailty status are heavily needed. One of the most used tests for functional assessment of the elderly is the 'Timed Up-and-Go' test. In previous projects, we have developed an ultrasound-based device that enables performing the test autonomously. This paper described the development and validation of algorithms for detection of subtasks (stand up, walk, turn around, walk, sit down) and for step frequency estimation from the Timed Up-and-Go signals. The algorithms have been tested with an annotated test set recorded in 8 healthy subjects. The mean error for the developed subtask transition detection algorithms was in between 0.22 and 0.35 s. The mean step frequency error was 0.15 Hz. Future steps will include prospective evaluation of the algorithms with elderly people.
CITATION STYLE
Diz Felipe, A., Ziegl, A., Hayn, D., & Schreier, G. (2022). Development of Algorithms for Automated Timed Up-and-Go Test Subtask and Step Frequency Analysis. In Studies in Health Technology and Informatics (Vol. 289, pp. 367–370). IOS Press BV. https://doi.org/10.3233/SHTI210935
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