Difference between revisions of "Publications:A wearable gait analysis system using inertial sensors Part II: Evaluation in a clinical setting"
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|HostPublication=BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing | |HostPublication=BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing | ||
| − | |Conference=International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012, Vilamoura, Algarve, 1 - 4 February, 2012 | + | |Conference=International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012, Vilamoura, Algarve, 1 - 4 February, 2012 (best paper) |
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Latest revision as of 19:53, 2 April 2014
| Title | A wearable gait analysis system using inertial sensors Part II: Evaluation in a clinical setting |
|---|---|
| Author | Anita Sant'Anna and Nicholas Wickström and Helene Eklund and Roy Tranberg |
| Year | 2012 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing |
| Conference | International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012, Vilamoura, Algarve, 1 - 4 February, 2012 (best paper) |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:516207 |
| Abstract | The gold standard for gait analysis, in-lab 3D motion capture, is not routinely used for clinical assessment due to limitations in availability, cost and required training. Inexpensive alternatives to quantitative gait analysis are needed to increase the its adoption. Inertial sensors such as accelerometers and gyroscopes are promising tools for the development of wearable gait analysis (WGA) systems. The present study evaluates the use of a WGA system on hip-arthroplasty patients in a real clinical setting. The system provides information about gait symmetry and normality. Results show that the normality measurements are well correlated with various quantitative and qualitative measures of recovery and health status. |
