Activity recognition of local muscular endurance (LME) exercises using an inertial sensor
In: Prabhu, Ghanashyama orcid:0000-0003-2836-9734 , Ahmadi, Amin, O'Connor, Noel E. orcid:0000-0002-4033-9135 and Moran, Kieran orcid:0000-0003-2015-8967 (2017) Activity recognition of local muscular endurance (LME) exercises using an inertial sensor. In: 11th International Symposium on Computer Science in Sport 2017, 2017
Konferenz
Zugriff:
In this paper, we propose an algorithmic approach for a motion analysis framework to automatically recognize local muscular endurance (LME) exercises and to count their repetitions using a wrist-worn inertial sensor. LME exercises are prescribed for cardiovascular disease rehabilitation. As a technical solution, we propose activity recognition based on machine learning. We developed an algorithm to automatically segment the captured data from all participants. Relevant time and frequency domain features were extracted using a sliding window technique. Principal component analysis (PCA) was applied for dimensionality reduction of the extracted features. We trained 15 binary classifiers using support vector machine (SVM) to recognize individual LME exercises, achieving overall accuracy of more than 98%. We applied grid search technique to obtain the optimal SVM hyperplane parameters. The learning curves (mean ± stdev) for each model is investigated to verify that the models were not over-tted and performed well on any new test data. Also, we devised a method to count the repetitions of the upper body exercises.
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Activity recognition of local muscular endurance (LME) exercises using an inertial sensor
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Autor/in / Beteiligte Person: | Prabhu, Ghanashyama ; Ahmadi, Amin ; O'Connor, Noel E. ; Moran, Kieran ; Lames, Martin ; Saupe, Dietmar ; Wiemeyer, Josef |
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Zeitschrift: | Prabhu, Ghanashyama orcid:0000-0003-2836-9734 , Ahmadi, Amin, O'Connor, Noel E. orcid:0000-0002-4033-9135 and Moran, Kieran orcid:0000-0003-2015-8967 (2017) Activity recognition of local muscular endurance (LME) exercises using an inertial sensor. In: 11th International Symposium on Computer Science in Sport 2017, 2017 |
Veröffentlichung: | Springer International Publishing, 2017 |
Medientyp: | Konferenz |
DOI: | 10.1007/978-3-319-67846-7_4 |
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