@conference {1412,
	title = {Validation of a motion capture suit for clinical gait analysis},
	booktitle = {Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare - PervasiveHealth {\textquoteright}17},
	year = {2017},
	month = {2017},
	pages = {120 - 126},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Gait analysis is often supported by technology. Due to limitations in optical systems, such as limited measurement volumes and the requirement of a laboratory environment, low-cost inertial measurement unit (IMU) based motion capture system might be better suited for gait analysis since they involve no spatial limitations and are flexible applicable. In this paper we investigate, if a low-cost IMU-based motion capture suits are an adequate alternative for clinical gait analysis in terms of accuracy of the determination of joint flexions and gait parameters. For this reason, we developed a gait analysis system and a gait analysis algorithm, which detects joint positions based on the Joint Coordinate System and determines knee, hip, and ankle flexions, as well as spatiotemporal parameters such as the number of steps, cadence, step duration and step length, and the specific gait phases. We evaluated and validated the IMU-based system in comparison to camera-based measurements (as gold standard) with three different healthy adult subjects. The evaluation indicates that the full-body motion capture system achieves a high degree of precision (0.86) and recall (0.98) in the recognition of gait cycles. The harmonic mean F(0.15) of the two factors precision and recall is on average 0.96 and the mentioned temporal gait parameters can be determined with an error below 10 ms. The mean derivation in the determination of joint angles amounts 1.35{\textdegree} {\textpm} 2{\textdegree}. Consequently, the article at hand indicates that low-cost IMU-based motion capture suits are an accurate alternative for gait analysis.},
	isbn = {9781450363631},
	doi = {10.1145/3154862.3154884},
	url = {http://dl.acm.org/citation.cfm?doid=3154862.3154884},
	author = {Hellmers, Sandra and Fudickar, Sebastian and Lange, Eugen and Lins, Christian and Hein, Andreas}
}
