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Exploring Accelerometer-based Step Detection by using a Wheeled Walking Frame

: Bieber, Gerald; Haescher, Marian; Hanschmann, Paul; Matthies, Denys J.C.


Matthies, D.J.C.; Haescher, M.; Yordanova, K.; Bieber, G.; Schröder, M.; Kirste, T.; Urban, B. ; Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Computer and Human Interaction -SIGCHI-; Fraunhofer-Institut für Graphische Datenverarbeitung -IGD-, Institutsteil Rostock:
iWOAR 2018, 5th international Workshop on Sensor-based Activity Recognition and Interaction. Proceedings : September 20-21, 2018, Berlin, Germany
New York: ACM, 2018 (ACM International Conference Proceeding Series)
ISBN: 978-1-4503-6487-4
Art. 8, 6 pp.
International Workshop on Sensor-based Activity Recognition and Interaction (iWOAR) <5, 2018, Rostock>
Conference Paper
Fraunhofer IGD ()
Fraunhofer IGD-R ()
Guiding Theme: Individual Health; Research Area: Human computer interaction (HCI); step detection; smart watches; elderly user

Step detection with accelerometers is a very common feature that smart wearables already include. However, when using a wheeled walking frame / rollator, current algorithms may be of limited use, since a different type of motion is being excreted. In this paper, we uncover these limitations of current wearables by a pilot study. Furthermore, we investigated an accelerometer-based step detection for using a wheeled walking frame, when mounting an accelerometer to the frame and at the user’s wrist. Our findings include knowledge on signal propagation of each axis, knowledge on the required sensor quality and knowledge on the impact of different surfaces and floor types. In conclusion, we outline a new step detection algorithm based on accelerometer input data. Our algorithm can significantly empower future off-the-shelf wearables with the capability to sufficiently detect steps with elderly people using a wheeled walking frame. This can help to evaluate the state of health with regard to the human behavior and motor system and even to determine the progress of certain diseases.