Affiliation:
1. Department of Mechanical Engineering, Faculty of Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada
2. Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M2, Canada
Abstract
The Timed Up and Go test (TUG) and L Test are functional mobility tests that allow healthcare providers to assess a person’s balance and fall risk. Segmenting these mobility tests into their respective subtasks, using sensors, can provide further and more precise information on mobility status. To identify and compare current methods for subtask segmentation using inertial sensor data, a scoping review of the literature was conducted using PubMed, Scopus, and Google Scholar. Articles were identified that described subtask segmentation methods for the TUG and L Test using only inertial sensor data. The filtering method, ground truth estimation device, demographic, and algorithm type were compared. One article segmenting the L Test and 24 articles segmenting the TUG met the criteria. The articles were published between 2008 and 2022. Five studies used a mobile smart device’s inertial measurement system, while 20 studies used a varying number of external inertial measurement units. Healthy adults, people with Parkinson’s Disease, and the elderly were the most common demographics. A universally accepted method for segmenting the TUG test and the L Test has yet to be published. Angular velocity in the vertical and mediolateral directions were common signals for subtask differentiation. Increasing sample sizes and furthering the comparison of segmentation methods with the same test sets will allow us to expand the knowledge generated from these clinically accessible tests.
Reference37 articles.
1. Validity of the Timed Up and Go Test as a Measure of Functional Mobility in Persons With Multiple Sclerosis;Sandroff;Arch. Phys. Med. Rehabil.,2016
2. The reliability and validity of the L-test in people with Parkinson’s disease;Haas;Physiotherapy,2019
3. Quantitative evaluation of movement using the timed up-and-go test;Higashi;IEEE Eng. Med. Biol. Mag.,2008
4. Hellmers, S., Izadpanah, B., Dasenbrock, L., Diekmann, R., Bauer, J.M., Hein, A., and Fudickar, S. (2018). Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements. Sensors, 18.
5. Automatic Timed Up-and-Go Sub-Task Segmentation for Parkinson’s Disease Patients Using Video-Based Activity Classification;Li;IEEE Trans. Neural Syst. Rehabil. Eng.,2018
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