University of Twente Student Theses
Measuring gait characteristics using wearable sensors in neurological patients
Cavelaars, D.J. (2023) Measuring gait characteristics using wearable sensors in neurological patients.
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| Abstract: | Chronic stroke patients often suffer from pathological gait due to decreased motor control. In therapy, a patient’s gait is usually assessed using an optical motion-capturing system, which can only be performed in a specialised lab. It would be beneficial to be able to determine the same gait characteristics at home using wearable sensors. This paper aims to determine gait events, and spatiotemporal and kinematic metrics using Inertial Measurement Units (IMUs) for chronic stroke patients with pathological gait. A group of eight chronic stroke patients aged between 49.0 and 69.4 years were analysed using IMUs. A total of 8799 strides in both affected and unaffected sides were recorded. The accuracy of foot-based and shank-based IMU systems was compared to the gold standard. In detecting gait events (initial contact, mid-stance, heel-off, terminal contact and mid-swing) on the participant’s affected side, the foot-based system had a smaller median error (initial contact: 0.01 s; mid-stance: 0.02 s; heel-off: 0.11 s; terminal contact: 0.02 s; mid-swing: 0.02 s) than the shank-based system. At all five gait events, the foot-based system also had a lower variance and fewer falsely identified gait events. In addition, the accuracy of spatiotemporal and foot kinematic metrics was compared between the foot-based and shank-based systems. The results show that the foot-based gait measurement algorithm is the most accurate for most metrics. In conclusion, foot-based IMUs are better used compared to shank- based IMUs to determine gait characteristics in patients with chronic stroke. |
| Item Type: | Essay (Master) |
| Clients: | Sint Maartenskliniek, Nijmegen, the Netherlands |
| Faculty: | ET: Engineering Technology |
| Subject: | 50 technical science in general |
| Programme: | Biomedical Engineering MSc (66226) |
| Link to this item: | https://purl.utwente.nl/essays/97492 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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