Abstract | ||
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A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with real-time auditory biofeedback at the instructed speed of 3.2 ms(-1). Because inter-subject variation may underline the importance of individualized retraining, a change-point analysis was used for each subject. The tuned change-point application detected major and subtle changes in the time series. No changes were found in the no-biofeedback condition. In the biofeedback condition, a first change in the axial peak tibial acceleration occurred on average after 309 running gait cycles (3 ' 40 "). The major change was a mean reduction of 2.45 g which occurred after 699 running gait cycles (8 ' 04 ") in this group. The time needed to achieve the major reduction varied considerably between subjects. Because of the individualized approach to gait retraining and its relatively quick response due to a strong sensorimotor coupling, we want to highlight the potential of a stand-alone biofeedback system that provides real-time, continuous, and auditory feedback in response to the axial peak tibial acceleration for lower-impact running. |
Year | DOI | Venue |
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2020 | 10.3390/s20061720 | SENSORS |
Keywords | DocType | Volume |
biomechanics,augmented feedback,motor learning,gait adaptation,music | Journal | 20 |
Issue | ISSN | Citations |
6 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Pieter Van den Berghe | 1 | 0 | 0.34 |
Maxim Gosseries | 2 | 0 | 0.34 |
Joeri Gerlo | 3 | 0 | 0.34 |
Matthieu Lenoir | 4 | 1 | 1.05 |
Marc Leman | 5 | 67 | 11.96 |
Dirk De Clercq | 6 | 7 | 1.58 |