Automatic measurement of physical mobility in Get-Up-and-Go Test using kinect sensor
| Autor: | H B Amir Kargar, Taylor Struemph, Wilson D. Pace, Mohammad H. Mahoor, Rodney D. Nielsen, Ali Mollahosseini |
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| Rok vydání: | 2014 |
| Předmět: |
FOS: Computer and information sciences
Support Vector Machine Get up and go test Computer science Computer Science - Human-Computer Interaction Monitoring Ambulatory Pilot Projects 02 engineering and technology Human-Computer Interaction (cs.HC) Gait (human) 0202 electrical engineering electronic engineering information engineering medicine Humans Computer vision Gait Aged Aged 80 and over business.industry Signal Processing Computer-Assisted 020207 software engineering Ranging 3. Good health Human skeleton medicine.anatomical_structure Feature (computer vision) Accidental Falls 020201 artificial intelligence & image processing Artificial intelligence business Algorithms Physical mobility |
| Zdroj: | EMBC |
| DOI: | 10.1109/embc.2014.6944375 |
| Popis: | Get-Up-and-Go Test is commonly used for assessing the physical mobility of the elderly by physicians. This paper presents a method for automatic analysis and classification of human gait in the Get-Up-and-Go Test using a Microsoft Kinect sensor. Two types of features are automatically extracted from the human skeleton data provided by the Kinect sensor. The first type of feature is related to the human gait (e.g., number of steps, step duration, and turning duration); whereas the other one describes the anatomical configuration (e.g., knee angles, leg angle, and distance between elbows). These features characterize the degree of human physical mobility. State-of-the-art machine learning algorithms (i.e. Bag of Words and Support Vector Machines) are used to classify the severity of gaits in 12 subjects with ages ranging between 65 and 90 enrolled in a pilot study. Our experimental results show that these features can discriminate between patients who have a high risk for falling and patients with a lower fall risk. Comment: Published in: Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE |
| Databáze: | OpenAIRE |
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