Herrera, RR;
Heravi, BM;
Barbareschi, G;
Carlson, T;
Holloway, C;
(2018)
Towards a Wearable Wheelchair Monitor: Classification of push style based on inertial sensors at multiple upper limb locations.
In:
(Proceedings) IEEE International Conference on Systems, Man, and Cybernetics (SMC).
(pp. pp. 1535-1540).
IEEE
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Abstract
Measuring manual wheelchair activity by using wearable sensors is becoming increasingly common for rehabilitation and monitoring purposes. Until recently most research has focused on the identification of activities of daily living or on counting the number of strokes. However, how a person pushes their wheelchair - their stroke pattern - is an important descriptor of the wheelchair user's quality of movement. This paper evaluates the capability of inertial sensors located at different upper limb locations plus the wheel of the wheelchair, to classify two types of stroke pattern for manual wheelchairs: semicircle and arc. Data was collected using bespoke inertial sensors with a wheelchair fixed to a treadmill. Classification was completed with a linear SVM algorithm, and classification performance was computed for each sensor location in the upper limb, and then in combination with wheel sensor. For single sensors, forearm location had the highest accuracy (96%) followed by hand (93%) and arm (90%). For combined sensor location with wheel, best accuracy came in combination with forearm. These results set the direction towards a wearable wheelchair monitor that can measure the quality as well as the quantity of movement and which offers multiple on-body locations for increased usability.
| Type: | Proceedings paper |
|---|---|
| Title: | Towards a Wearable Wheelchair Monitor: Classification of push style based on inertial sensors at multiple upper limb locations |
| Event: | IEEE International Conference on Systems, Man, and Cybernetics (SMC) |
| Location: | IEEE Syst Man & Cybernet Soc, Miyazaki, JAPAN |
| Dates: | 07 October 2018 - 10 October 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/SMC.2018.00266 |
| Publisher version: | https://doi.org/10.1109/SMC.2018.00266 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Cybernetics, Computer Science, Information Systems, Computer Science, manual wheelchair, inertial sensor, push style, stroke pattern, wearable technology, PROPULSION, BIOMECHANICS, PATTERNS, USERS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Ortho and MSK Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10071328 |
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