Abstract
An important field in physiotherapy is the rehabilitation of gait. A continuous assessment and progress tracking of a patient's ability to walk is of clinical interest. Unfortunately the tools available to the therapists are very time-consuming and subjective. Non-intrusive, small, wearable, wireless sensors can be worn by the patients and provide inertial measurements to estimate the pose of the lower body during walking. For this purpose, we propose two different kinematic models of the human lower body. We use an Extended Kalman Filter to estimate the joint angles and show that a variety of sensors, such as accelerometers, gyroscopes, and motion capture markers, can be used and fused together to aid the joint angle estimate. The algorithm is validated on gait data collected from healthy participants.
Original language | English |
---|---|
Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
Editors | Jeff Duerk, Jim Ji |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 2310-2313 |
Number of pages | 4 |
ISBN (Electronic) | 9781424479290 |
ISBN (Print) | 9781424479276 |
DOIs | |
Publication status | Published - 6 Nov 2014 |
Externally published | Yes |
Event | International Conference of the IEEE Engineering in Medicine and Biology Society 2014 - Sheraton Chicago Hotel and Towers, Chicago, United States of America Duration: 26 Aug 2014 → 30 Aug 2014 Conference number: 36th https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/6923026/proceeding (Proceedings) https://web.archive.org/web/20140331105330/http://embc.embs.org/2014/?page_id=120 (Website) |
Conference
Conference | International Conference of the IEEE Engineering in Medicine and Biology Society 2014 |
---|---|
Abbreviated title | EMBC 2014 |
Country/Territory | United States of America |
City | Chicago |
Period | 26/08/14 → 30/08/14 |
Internet address |