Towards real-time detection of gait events on different terrains using time-frequency analysis and peak heuristics algorithm
文献类型：期刊论文
| 作者 | Zhou, Hui1; Ji, Ning1; Samuel, Oluwarotimi Williams1,2; Cao, Yafei3; Zhao, Zheyi4; Chen, Shixiong1; Li, Guanglin1 |
| 刊名 | Sensors
 |
| 出版日期 | 2016-10-01 |
| 卷号 | 16期号:10页码:17 |
| 关键词 | Gait event detection Accelerometer Continuous wavelet transform Heuristics Stairs walking |
| ISSN号 | 1424-8220 |
| DOI | 10.3390/s16101634 |
| 通讯作者 | Cao, yafei(caoyafei64@163.com) ; Li, guanglin(gl.li@siat.ac.cn) |
| 英文摘要 | Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. based on the acceleration signals, different algorithms have been proposed to detect toe off (to) and heel strike (hs) gait events in previous studies. while these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. in this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. the performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. our experimental results showed that the mean f1 scores of the proposed algorithm were above 0.98 for hs event detection and 0.95 for to event detection on the three terrains. this indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses. |
| WOS关键词 | WAVELET-TRANSFORM ; RATE GYROSCOPE ; WALKING ; VALIDATION ; CONTACT ; SENSORS |
| WOS研究方向 | Chemistry ; Electrochemistry ; Instruments & Instrumentation |
| WOS类目 | Chemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:000386131600086 |
| 出版者 | MDPI AG |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374973 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Cao, Yafei; Li, Guanglin |
| 作者单位 | 1.Chinese Acad Sci, Shenzhen Inst Adv Technol, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen 518055, Peoples R China 2.Univ Chinese Acad Sci, Shenzhen Coll Adv Technol, Shenzhen 518055, Peoples R China 3.Shenzhen Tradit Chinese Med Hosp, Shenzhen 518033, Peoples R China 4.Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhou, Hui,Ji, Ning,Samuel, Oluwarotimi Williams,et al. Towards real-time detection of gait events on different terrains using time-frequency analysis and peak heuristics algorithm[J]. Sensors,2016,16(10):17. |
| APA | Zhou, Hui.,Ji, Ning.,Samuel, Oluwarotimi Williams.,Cao, Yafei.,Zhao, Zheyi.,...&Li, Guanglin.(2016).Towards real-time detection of gait events on different terrains using time-frequency analysis and peak heuristics algorithm.Sensors,16(10),17. |
| MLA | Zhou, Hui,et al."Towards real-time detection of gait events on different terrains using time-frequency analysis and peak heuristics algorithm".Sensors 16.10(2016):17. |
入库方式： iSwitch采集
来源：中国科学院大学
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