In the last decade the introduction of wearable technologies supported the implementation of reliable quantification tools for clinical functional assessment. Within this frame, this work was focused on the development and validation of a wearable system for analyzing motor function, particularly using the Timed-Up and Go (TUG) test. This study specifically aimed to create a wearable device that could quantify and automate the TUG test, collecting not only the time taken but also various kinematic parameters like accelerations, velocity, and number of steps. The wearable actigraph, fixed at the pelvis by means of an elastic band, measured and stored 3D inertial parameters for processing and analysis. The validation involved comparing manual TUG test times with those obtained using the actigraph, showing a high level of agreement and accuracy. The study included healthy subjects and individuals with different pathologies like post-stroke, multiple sclerosis, and Parkinson's, demonstrating the system's feasibility in clinical settings. Overall, the wearable system proved effective in quantifying and automating the TUG test, offering a possible remote, self, and unsupervised method for functional evaluation and tele-rehabilitation programs.
A Wearable and Semi-automated Timed-Up and Go Test: Implementation and Accuracy Validation
Perego, Paolo;Fusca, Marcello Cono;Lopomo, Nicola Francesco;Andreoni, Giuseppe
2024-01-01
Abstract
In the last decade the introduction of wearable technologies supported the implementation of reliable quantification tools for clinical functional assessment. Within this frame, this work was focused on the development and validation of a wearable system for analyzing motor function, particularly using the Timed-Up and Go (TUG) test. This study specifically aimed to create a wearable device that could quantify and automate the TUG test, collecting not only the time taken but also various kinematic parameters like accelerations, velocity, and number of steps. The wearable actigraph, fixed at the pelvis by means of an elastic band, measured and stored 3D inertial parameters for processing and analysis. The validation involved comparing manual TUG test times with those obtained using the actigraph, showing a high level of agreement and accuracy. The study included healthy subjects and individuals with different pathologies like post-stroke, multiple sclerosis, and Parkinson's, demonstrating the system's feasibility in clinical settings. Overall, the wearable system proved effective in quantifying and automating the TUG test, offering a possible remote, self, and unsupervised method for functional evaluation and tele-rehabilitation programs.File | Dimensione | Formato | |
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