Literature DB >> 26738169

Accurate walking and running speed estimation using wrist inertial data.

M Bertschi, P Celka, R Delgado-Gonzalo, M Lemay, E M Calvo, O Grossenbacher, Ph Renevey.   

Abstract

In 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 2(nd) and 3(rd) quartiles of the relative error dispersion in the interval ±5%. These results are comparable to accuracies obtained with classical foot pod devices.

Mesh:

Year:  2015        PMID: 26738169     DOI: 10.1109/EMBC.2015.7320269

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  MOBIlity assessment with modern TEChnology in older patients' real-life by the General Practitioner: the MOBITEC-GP study protocol.

Authors:  Mareike Münch; Robert Weibel; Alexandros Sofios; Haosheng Huang; Denis Infanger; Erja Portegijs; Eleftheria Giannouli; Jonas Mundwiler; Lindsey Conrow; Taina Rantanen; Arno Schmidt-Trucksäss; Andreas Zeller; Timo Hinrichs
Journal:  BMC Public Health       Date:  2019-12-19       Impact factor: 3.295

2.  Development and large-scale validation of the Watch Walk wrist-worn digital gait biomarkers.

Authors:  Lloyd L Y Chan; Tiffany C M Choi; Stephen R Lord; Matthew A Brodie
Journal:  Sci Rep       Date:  2022-10-10       Impact factor: 4.996

  2 in total

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