Event-based sampling for reducing communication load in realtime human motion analysis by wireless inertial sensor networks
Laidig D, Trimpe S, Seel T (2016)
Publication Type: Journal article
Publication year: 2016
Journal
Book Volume: 2
Pages Range: 711-714
Journal Issue: 1
Abstract
We examine the usefulness of event-based sampling approaches for reducing communication in inertial-sensor-based analysis of human motion. To this end we consider realtime measurement of the knee joint angle during walking, employing a recently developed sensor fusion algorithm. We simulate the effects of different event-based sampling methods on a large set of experimental data with ground truth obtained from an external motion capture system. This results in a reduced wireless communication load at the cost of a slightly increased error in the calculated angles. The proposed methods are compared in terms of best balance of these two aspects. We show that the transmitted data can be reduced by 66% while maintaining the same level of accuracy.
Authors with CRIS profile
Involved external institutions
Technische Universität Berlin
Germany (DE)
Max Planck Institute for Intelligent Systems (MPI-IS) / Max-Planck-Institut für Intelligente Systeme
Germany (DE)
Germany (DE)
Max Planck Institute for Intelligent Systems (MPI-IS) / Max-Planck-Institut für Intelligente Systeme
Germany (DE)
How to cite
APA:
Laidig, D., Trimpe, S., & Seel, T. (2016). Event-based sampling for reducing communication load in realtime human motion analysis by wireless inertial sensor networks. Current Directions in Biomedical Engineering, 2(1), 711-714. https://doi.org/10.1515/cdbme-2016-0154
MLA:
Laidig, Daniel, Sebastian Trimpe, and Thomas Seel. "Event-based sampling for reducing communication load in realtime human motion analysis by wireless inertial sensor networks." Current Directions in Biomedical Engineering 2.1 (2016): 711-714.
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