@inproceedings{be326f4649de488eb94a632582bf79d8,
title = "Frequency-Domain Analysis for Accurate and Robust Gait Cycle Time Detection with Clinical Data",
abstract = "Gait tasks have become a topic of increasing inter-est in biological engineering research in recent years. One way to obtain the gait cycle time (GCT) is to analyze a subject's gait acceleration signal as recorded by an inertial measurement unit (IMU) [1]. An accurate peak detection of the IMU acceleration has thus become a requirement for GCT analysis. This study proposes a detection procedure for accurately detecting the peaks in a noisy IMU acceleration signal based on a frequency-domain analysis of the acceleration.",
keywords = "Detection procedure, Frequency-Domain analysis, Gait Cycle Time",
author = "Yeh, {Yu Hung} and Yan, {Jiun Lin} and Gu, {Meng Xun} and Chen, {Yi Wei} and Lee, {Ta Sung}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 ; Conference date: 11-07-2022 Through 15-07-2022",
year = "2022",
doi = "10.1109/EMBC48229.2022.9871244",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4200--4204",
booktitle = "44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022",
address = "美國",
}