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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.01540 |
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| _version_ | 1866914526406901760 |
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| author | Schulthess, Lukas Pleisch, Fabian Käch, Matheo Bruhin, Björn P. Magno, Michele Benini, Luca Leitner, Christoph |
| author_facet | Schulthess, Lukas Pleisch, Fabian Käch, Matheo Bruhin, Björn P. Magno, Michele Benini, Luca Leitner, Christoph |
| contents | Wearable body-attached multi-sensor systems enable detailed analysis of human motion and physiological signals in sports, rehabilitation, and movement research. While wireless synchronization techniques can reliably align sensor data streams, interpreting and validating complex or unconstrained activities often requires an additional, objective visual reference. Existing laboratory-grade reference systems provide high accuracy but are impractical for outdoor or field deployments. In contrast, commercial video timecode solutions typically rely on local device-to-device synchronization, which increases the power required to maintain synchronization. This is not desirable in many application scenarios. This paper presents a lightweight Timecode Generator (TCG) that converts Global Navigation Satellite System (GNSS)-derived time directly into a Linear Timecode (LTC) signal that is injected into the recording via a camera audio channel. The approach eliminates continuous handshaking, allowing the system to be activated immediately before the action of interest, thus reducing power consumption and enabling smaller batteries and unobtrusive hardware designs of body-attached sensor nodes. The TCG supports common video frame rates of 24, 25, and 30 frames per second (fps). Experimental evaluation confirms that accurate time alignment is maintained for several minutes without GNSS updates. At 30 fps, the alignment duration is 543 s before a potential frame-level shift occurs. With an average power consumption of 35.37 mW, the system achieves an operating time of up to 75 h when powered by two standard AAA alkaline batteries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_01540 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Time-Synchronized Video Reference System for Data Analysis of Body-Attached Sensor Nodes in Outdoor Scenarios Schulthess, Lukas Pleisch, Fabian Käch, Matheo Bruhin, Björn P. Magno, Michele Benini, Luca Leitner, Christoph Signal Processing Wearable body-attached multi-sensor systems enable detailed analysis of human motion and physiological signals in sports, rehabilitation, and movement research. While wireless synchronization techniques can reliably align sensor data streams, interpreting and validating complex or unconstrained activities often requires an additional, objective visual reference. Existing laboratory-grade reference systems provide high accuracy but are impractical for outdoor or field deployments. In contrast, commercial video timecode solutions typically rely on local device-to-device synchronization, which increases the power required to maintain synchronization. This is not desirable in many application scenarios. This paper presents a lightweight Timecode Generator (TCG) that converts Global Navigation Satellite System (GNSS)-derived time directly into a Linear Timecode (LTC) signal that is injected into the recording via a camera audio channel. The approach eliminates continuous handshaking, allowing the system to be activated immediately before the action of interest, thus reducing power consumption and enabling smaller batteries and unobtrusive hardware designs of body-attached sensor nodes. The TCG supports common video frame rates of 24, 25, and 30 frames per second (fps). Experimental evaluation confirms that accurate time alignment is maintained for several minutes without GNSS updates. At 30 fps, the alignment duration is 543 s before a potential frame-level shift occurs. With an average power consumption of 35.37 mW, the system achieves an operating time of up to 75 h when powered by two standard AAA alkaline batteries. |
| title | A Time-Synchronized Video Reference System for Data Analysis of Body-Attached Sensor Nodes in Outdoor Scenarios |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2605.01540 |