| Autor: |
Raviraj Nataraj, Sean Patrick Sanford, Mingxiao Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Biomechanics, Vol 3, Iss 3, Pp 425-442 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2673-7078 |
| DOI: |
10.3390/biomechanics3030035 |
| Popis: |
This study examined the effects of different modes of augmented visual feedback of joint kinematics on the emerging joint moment patterns during the two-legged squat maneuver. Training with augmented visual feedback supports improved kinematic performance of maneuvers related to sports or daily activities. Despite being representative of intrinsic motor actions, joint moments are not traditionally evaluated with kinematic feedback training. Furthermore, stabilizing joint moment patterns with physical training is beneficial to rehabilitating joint-level function (e.g., targeted strengthening and conditioning of muscles articulating that joint). Participants were presented with different modes of augmented visual feedback to track a target squat-motion trajectory. The feedback modes varied along features of complexity (i.e., number of segment trajectories shown) and body representation (i.e., trajectories shown as sinusoids versus dynamic stick-figure avatars). Our results indicated that mean values and variability (trial-to-trial standard deviations) of joint moments are significantly (p < 0.05) altered depending on the visual feedback features being applied, the specific joint (ankle, knee, hip), and the squat movement phase (early, middle, or late time window). This study should incentivize more optimal delivery of visual guidance during rehabilitative training with computerized interfaces (e.g., virtual reality). |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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