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dc.contributor.authorBertschi, Mattia
dc.contributor.authorCelka, Patrick
dc.contributor.authorDelgado-Gonzalo, Ricard
dc.contributor.authorLemay, Mathieu
dc.contributor.authorMuntané, Enric
dc.contributor.authorGrossenbacher, Olivier
dc.contributor.authorRenevey, Philippe
dc.date.accessioned2022-02-14T17:07:45Z
dc.date.available2022-02-14T17:07:45Z
dc.date.issued2015
dc.identifier.citation2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan (Italy), pp. 8083-8086
dc.identifier.isbn978-1-4244-9271-8
dc.identifier.urihttps://yoda.csem.ch/handle/20.500.12839/636
dc.description.abstractIn this work, we present an accelerometry-based device for robust running speed estimation integrated into a watch-like device. The estimation is based on inertial data processing, which consists in applying a leg-and-arm dynamic motion model to 3D accelerometer signals. This motion model requires a calibration procedure that can be done either on a known distance or on a constant speed period. The protocol includes walking and running speeds between 1.8km/h and 19.8km/h. Preliminary results based on eleven subjects are characterized by unbiased estimations with 2nd and 3rd quartiles of the relative error dispersion in the interval ±5%. These results are comparable to accuracies obtained with classical foot pod devices.
dc.titleAccurate walking and running speed estimation using wrist inertial data
dc.typeProceedings Article
dc.type.csemdivisionsDiv-E
dc.type.csemresearchareasDigital Health
dc.identifier.urlhttps://ieeexplore.ieee.org/document/7320269/
dc.identifier.doi10.1109/EMBC.2015.7320269


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