Lozano-García, Manuel, Doheny, Emer P., Mann, Elliot, Morgan-Jones, Philippa, Drew, Cheney  ORCID: https://orcid.org/0000-0002-4397-6252, Busse, Monica ORCID: https://orcid.org/0000-0002-5331-5909 and Lowery, Madeleine M.
2024.
F033 Real-world walking bout and gait event detection using wearable inertial sensors in Huntington’s disease.
Journal of Neurology, Neurosurgery and Psychiatry
95
, A77.
10.1136/jnnp-2024-EHDN.151
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Abstract
Abstract Background Walking detection and monitoring of temporal gait parameters under free-living conditions using wearable inertial sensors could provide valuable information on gait impairment progression in Huntington’s disease (HD). A gait event detection algorithm was previously validated in HD participants [1], but the algorithm has not been deployed under free-living conditions. Aim To compare an algorithm for walking bout and gait event detection from a single leg-worn accelerometer, with reference data under free-living conditions in HD. Methods Thirteen HD participants (51 ± 10 yrs., UHDRS-TMS=25.85 ± 19.52, UHDRS gait score=0.69 ± 0.75) wore a thigh-worn (AP: ActivPAL4, 40Hz) tri-axial accelerometer and a wrist-worn (FB: Fitbit Charge 4) device for 7 days during free-living conditions. Walking bouts and gait events were detected from thigh acceleration using the Teager-Kaiser energy operator combined with unsupervised clustering. Daily time spent walking (Wt) and step count (SC) were estimated from all detected walking bouts on each day, and compared with proprietary AP data. Results Excellent agreement was observed for Wt and SC between the proposed algorithm (Wt=121.9 ± 75.4 min, SC=4032 ± 3222) and AP software (Wt=111.1 ± 76.8 min, SC=3893 ± 2740) (ICC2,1>0.975), with the presented algorithm additionally allowing stride and stance time estimation. The wrist-worn FB device overestimated SC by 34.2% as compared with thigh data. Conclusions An accurate method for walking bout detection and estimation of gait parameters has been deployed at home in HD participants using a single leg-worn accelerometer, which provides more accurate estimates of SC compared with wrist-worn devices.
| Item Type: | Short Communication |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Medicine Research Institutes & Centres > Centre for Trials Research (CNTRR) |
| Publisher: | BMJ Publishing Group |
| ISSN: | 0022-3050 |
| Funders: | JNPD |
| Last Modified: | 20 Jan 2026 16:36 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/184049 |
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