An adaptive gyroscope-based algorithm for temporal gait analysis.
Body-worn kinematic sensors have been widely proposed as the optimal solution for portable, low cost, ambulatory monitoring of gait. This study aims to evaluate an adaptive gyroscope-based algorithm for automated temporal gait analysis using body-worn wireless gyroscopes. Gyroscope data from nine he...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 48; no. 12; pp. 1251 - 1261 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Dec2010
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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=104569457&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104569457 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2010 vid: 48 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104569457 NLM21042951 2010872577 10.1007/s11517-010-0692-0 NLM21042951 104569457 ppf: 1251 ppct: 10 formats: fmt: @attributes: type: P tig: atl: An adaptive gyroscope-based algorithm for temporal gait analysis. aug: au: Greene BR McGrath D O'Neill R O'Donovan KJ Burns A Caulfield B Greene, Barry R McGrath, Denise O'Neill, Ross O'Donovan, Karol J Burns, Adrian Caulfield, Brian affil: Intel Digital Health Group, Leixlip, Co, Kildare, Ireland sug: subj: Algorithms Gait Physiology Models, Biological Monitoring, Physiologic Methods Adult Female Gait Disorders, Neurologic Diagnosis Human Male Middle Age Monitoring, Physiologic Equipment and Supplies Wireless Communications Equipment and Supplies Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: Body-worn kinematic sensors have been widely proposed as the optimal solution for portable, low cost, ambulatory monitoring of gait. This study aims to evaluate an adaptive gyroscope-based algorithm for automated temporal gait analysis using body-worn wireless gyroscopes. Gyroscope data from nine healthy adult subjects performing four walks at four different speeds were then compared against data acquired simultaneously using two force plates and an optical motion capture system. Data from a poliomyelitis patient, exhibiting pathological gait walking with and without the aid of a crutch, were also compared to the force plate. Results show that the mean true error between the adaptive gyroscope algorithm and force plate was -4.5 ± 14.4 ms and 43.4 ± 6.0 ms for IC and TC points, respectively, in healthy subjects. Similarly, the mean true error when data from the polio patient were compared against the force plate was -75.61 ± 27.53 ms and 99.20 ± 46.00 ms for IC and TC points, respectively. A comparison of the present algorithm against temporal gait parameters derived from an optical motion analysis system showed good agreement for nine healthy subjects at four speeds. These results show that the algorithm reported here could constitute the basis of a robust, portable, low-cost system for ambulatory monitoring of gait. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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