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Detail
Journal Article
Gait Event Detection Algorithm based on Smart Insoles
- Authors
- JeongKyun Kim, Myung-Nam Bae, Kang Bok Lee, Sang Gi Hong
- Issue Date
- 2020-02
- Citation
- ETRI Journal, v.42, no.1, pp.46-53
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03혻seconds for running toe-off events, and an average of 0??0.01혻seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance혻phase time,혻swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.
- KSP Keywords
- Gait Analysis, Gait event detection, Inertial measurement units(IMUs), Phase time, Smart Insole, Time-frequency Analysis, Toe-off, Walking and running, Wide range, clinical tool, event detection algorithm
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
