Articles | Volume 13, issue 2
https://doi.org/10.5194/jsss-13-187-2024
https://doi.org/10.5194/jsss-13-187-2024
Regular research article
 | 
22 Jul 2024
Regular research article |  | 22 Jul 2024

Human activity recognition system using wearable accelerometers for classification of leg movements: a first, detailed approach

Sandra Schober, Erwin Schimbäck, Klaus Pendl, Kurt Pichler, Valentin Sturm, and Frederick Runte

Cited articles

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Ashwini, K., Amutha, R., Rajave, R., and Anusha, D.: Classification of daily human activities using wearable inertial sensor, in: 2020 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), Chennai, India, 4–6 August 2020, IEEE, 1-6, https://doi.org/10.1109/WiSPNET48689.2020.9198406, 2020. a, b, c, d, e, f
Bajric, R., Zuber, N., Skrimpas, G. A., and Mijatovic, N.: Feature Extraction Using Discrete Wavelet Transform for Gear Fault Diagnosis of Wind Turbine Gearbox, Shock Vib., 2016, 6748469, https://doi.org/10.1155/2016/6748469, 2016. a
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Short summary
A human activity recognition (HAR) system carried by masseurs for controlling a therapy table via different movements of legs or hip was studied. This work starts with a survey on HAR systems using the sensor position "trouser pockets". Afterwards, in the experiments, the impacts of different parameters and configurations on the classification accuracy is examined to get a thorough understanding of the classification process.
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