Background and Aims: In the timed Get Up and Go Test (T-GUGT) to total time required to rise from a chair, walk 3m., turn, walk back and sit down again, is compared to a threshold. This test is widely used in fall risk and mobility assessment. The total time is measured by an observer and hence prone to errors. The durations of the different phases are typically not available. This small study aims to investigate whether image processing methods applied to 3D camera images could be applied to automate the T-GUGT test. Methods: Custom image processing, calibration and pose transition methods were developed and applied to 3D camera recordings of 4 healthy controls, each performing 6 consecutive instances of the T-GUGT. The durations of the different phases of the test and the total time taken were compared using Pearson{\textquoteright}s Correlation to the respective durations obtained from manually annotating the recorded images at the frame level. Results: The calculated total duration of the test correlates well to the ground truth (R2 = 0.761), while the correlation between the durations of the individual phases ranges from 0.69 for the forward walking phase down to 0.2 for sitting down and rising from the chair. Conclusions: The initial results suggest that a camera based automatic T-GUGT test is feasible, but that more research followed by proper validation is required. The added value of the proposed approach is that it additionally provides durations of the individual phases.
Jansen, B & Deklerck, R 2010, 'A 3D camera based automated T-GUGT tes', Parkinsonism and Related Disorders, vol. 16, no. s1, pp. 26-26.
Jansen, B., & Deklerck, R. (2010). A 3D camera based automated T-GUGT tes. Parkinsonism and Related Disorders, 16(s1), 26-26.
@article{198e40f241e94c89a672faad004b0043,
title = "A 3D camera based automated T-GUGT tes",
abstract = "Background and Aims: In the timed Get Up and Go Test (T-GUGT) to total time required to rise from a chair, walk 3m., turn, walk back and sit down again, is compared to a threshold. This test is widely used in fall risk and mobility assessment. The total time is measured by an observer and hence prone to errors. The durations of the different phases are typically not available. This small study aims to investigate whether image processing methods applied to 3D camera images could be applied to automate the T-GUGT test. Methods: Custom image processing, calibration and pose transition methods were developed and applied to 3D camera recordings of 4 healthy controls, each performing 6 consecutive instances of the T-GUGT. The durations of the different phases of the test and the total time taken were compared using Pearson{\textquoteright}s Correlation to the respective durations obtained from manually annotating the recorded images at the frame level. Results: The calculated total duration of the test correlates well to the ground truth (R2 = 0.761), while the correlation between the durations of the individual phases ranges from 0.69 for the forward walking phase down to 0.2 for sitting down and rising from the chair. Conclusions: The initial results suggest that a camera based automatic T-GUGT test is feasible, but that more research followed by proper validation is required. The added value of the proposed approach is that it additionally provides durations of the individual phases.",
keywords = "e-health, timed up and go test",
author = "Bart Jansen and Rudi Deklerck",
year = "2010",
month = feb,
day = "26",
language = "English",
volume = "16",
pages = "26--26",
journal = "Parkinsonism and Related Disorders",
issn = "1353-8020",
publisher = "Elsevier BV",
number = "s1",
note = "3rd International Congress on Gait \& Mental Function ; Conference date: 26-02-2010 Through 28-02-2010",
}