Journal article
Home-based monitor for gait and activity analysis
- Abstract:
- Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical evaluators. These measures are slightly subjective and are performed during a visit to a clinic or hospital and constitute therefore a point assessment. Point assessments can be influenced by daily patient condition or factors such as fatigue, motivation, and intercurrent illness. To enable home-based monitoring of gait and activity, a wearable magneto-inertial sensor (WMIS) has been developed. This device is a movement monitor composed of two very light watch-like sensors and a docking station. Each sensor contains a tri-axial accelerometer, gyroscope, magnetometer, and a barometer that record linear acceleration, angular velocity, the magnetic field of the movement in all directions, and barometric altitude, respectively. The sensors can be worn on the wrist, ankle, or wheelchair to record the subject's movements during the day. The docking station enables data uploading and recharging of sensor batteries during the night. Data are analyzed using proprietary algorithms to compute parameters representative of the type and intensity of the performed movement. This WMIS can record a set of digital biomarkers, including cumulative variables, such as total number of meters walked, and descriptive gait variables, such as the percentage of the most rapid or longest stride that represents the top performance of patient over a predefined period of time.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 235.0KB, Terms of use)
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- Publisher copy:
- 10.3791/59668
Authors
- Publisher:
- Journal of Visualized Experiments
- Journal:
- Journal of Visualized Experiments More from this journal
- Volume:
- 2019
- Issue:
- 150
- Article number:
- e59668
- Publication date:
- 2019-08-08
- DOI:
- EISSN:
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1940-087X
- Pmid:
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31449251
- Language:
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English
- Keywords:
- Pubs id:
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1092836
- Local pid:
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pubs:1092836
- Deposit date:
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2020-03-12
Terms of use
- Copyright holder:
- Journal of Visualized Experiments
- Copyright date:
- 2019
- Rights statement:
- Copyright © 2019 Journal of Visualized Experiments
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