AMIE: Automatic Monitoring of Indoor Exercises
| العنوان: | AMIE: Automatic Monitoring of Indoor Exercises |
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| المؤلفون: | Kurt Schütte, Jesse Davis, Tom Decroos, Benedicte Vanwanseele, Tim Op De Beéck |
| المساهمون: | Brefeld, U, Curry, E, Daly, E, MacNamee, B, Marascu, A, Pinelli, F, Berlingerio, M, Hurley, N |
| المصدر: | Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967 ECML/PKDD (3) |
| بيانات النشر: | Springer International Publishing, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | 030506 rehabilitation, Correctness, Computer science, business.industry, Mistake, Proprietary software, 02 engineering and technology, Pipeline (software), 03 medical and health sciences, Software, Human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, 0305 other medical science, business |
| الوصف: | Patients with sports-related injuries need to learn to perform rehabilitative exercises with correct movement patterns. Unfortunately, the feedback a physiotherapist can provide is limited by the visitation frequency of the patient. We study the feasibility of a system that automatically provides feedback on correct movement patterns to patients using a Microsoft Kinect camera and Machine Learning techniques. We discuss several challenges related to the Kinect's proprietary software, the Kinect data's heterogeneity, and the Kinect data's temporal component. We introduce AMIE, a machine learning pipeline that detects the exercise being performed, the exercise's correctness, and if applicable, the mistake that was made. To evaluate AMIE, ten participants were instructed to perform three types of typical rehabilitation exercises (squats, forward lunges and side lunges) demonstrating both correct movement patterns and frequent types of mistakes, while being recorded with a Kinect. AMIE detects the type of exercise almost perfectly with 99% accuracy and the type of mistake with 73% accuracy. ispartof: pages:424-439 ispartof: Joint European Conference on Machine Learning and Knowledge Discovery in Databases vol:11053 pages:424-439 ispartof: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases location:Dublin, Ireland date:10 Sep - 14 Sep 2018 status: published |
| ردمك: | 978-3-030-10996-7 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1efad0d3733e5cdb5013ce40d6e29c73 https://doi.org/10.1007/978-3-030-10997-4_26 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....1efad0d3733e5cdb5013ce40d6e29c73 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783030109967 |
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