Inertial sensors in estimating walking speed and inclination: an evaluation of sensor error models.
With the increasing interest of using inertial measurement units (IMU) in human biomechanics studies, methods dealing with inertial sensor measurement errors become more and more important. Pre-test calibration and in-test error compensation are commonly used to minimize the sensor errors and improv...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 50; no. 4; pp. 383 - 394 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104545220&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104545220 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2012 vid: 50 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104545220 NLM22418894 2011504890 10.1007/s11517-012-0887-7 NLM22418894 104545220 ppf: 383 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Inertial sensors in estimating walking speed and inclination: an evaluation of sensor error models. aug: au: Yang S Laudanski A Li Q Yang, Shuozhi Laudanski, Annemarie Li, Qingguo affil: Department of Mechanical and Materials Engineering, Queen's University, Kingston, ON, Canada sug: subj: Monitoring, Physiologic Equipment and Supplies Walking Physiology Motion Adult Algorithms Exercise Test Equipment and Supplies Exercise Test Methods Female Gait Physiology Human Male Models, Statistical Monitoring, Physiologic Methods Signal Processing, Computer Assisted Young Adult Adult: 19-44 years Female Male ab: With the increasing interest of using inertial measurement units (IMU) in human biomechanics studies, methods dealing with inertial sensor measurement errors become more and more important. Pre-test calibration and in-test error compensation are commonly used to minimize the sensor errors and improve the accuracy of the walking speed estimation results. However, the performance of a given sensor error compensation method does not only depend on the accuracy of the calibration or the sensor error evaluation, but also strongly relies on the selected sensor error model. The best performance could be achieved only when the essential components of sensor errors are included and compensated. Two new sensor error models, with the concerns about sensor acceleration measurement biases and sensor attachment misalignment, have been developed. The performance of these two error models were evaluated in the shank-mounted IMU-based walking speed/inclination estimation algorithm with a comparison of an existing error model. The treadmill walking experiment, conducted at both level and incline conditions, demonstrated the importance of sensor error model selection on the spatio-temporal gait parameter estimation performance. Accurate walking inclination estimation was made possible with a newly developed sensor error model. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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