Conventional training integrated with SteamVR Tracking 2.0: Body stability and coordination training evaluation on ICAROS Pro
(Konventionelles Training integriert mit SteamVR Tracking 2.0: Bewertung der Körperstabilität und des Koordinationstrainings auf ICAROS Pro)
Technological advances continually reduce the effort to digitally transform health-related activities such as rehabilitation and training. Exemplary systems use tracking and vital sign monitoring to assess physical condition and training progress. This paper presents a system for body stability training and coordination evaluation, using cost-efficient tracking and monitoring solutions. It implements the use case of app-guided back posture tracking on the ICAROS Pro training device via SteamVR Tracking 2.0, with pulse and respiration rate monitoring via Zephyr BioHarness 3.0. A longitudinal study on training effects with 20 subjects was conducted, involving a representative procedure created with a sports manager. Posture errors served as the main progress indicator, and pulse and respiration rates as co-indicators. Outcomes suggest the system`s capabilities to foster comprehension of effects and steering of exercises. Further, a secondary study presents a self-developed VR-based exergame demo for future system expansion. The Empatica EmbracePlus smartwatch was used as an alternative for vital sign acquisition. The user experiences of five subjects gathered via a survey highlight its motivating and entertaining character. For both the main and secondary studies, a thorough discussion elaborates on potentials and current limitations. The developed training system can serve as template and be adjusted for further use cases, and the exergame`s reception revealed prospective extension directions. Software components are available via GitHub.
© Copyright 2025 Sensors. Alle Rechte vorbehalten.
| Schlagworte: | |
|---|---|
| Notationen: | Naturwissenschaften und Technik Biowissenschaften und Sportmedizin |
| Tagging: | virtuelle Realität |
| Veröffentlicht in: | Sensors |
| Sprache: | Englisch |
| Veröffentlicht: |
2025
|
| Online-Zugang: | https://doi.org/10.3390/s25092840 |
| Jahrgang: | 25 |
| Heft: | 9 |
| Seiten: | 2840 |
| Dokumentenarten: | Artikel |
| Level: | hoch |