뇌졸중으로 인한 편마비 환자의 보행평가를 위한 체중심 가속도센서 기반의 새로운 보 검출 알고리즘 개발
In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point...
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| Vydané v: | Journal of biomedical engineering research Ročník 30; číslo 3; s. 213 - 220 |
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| Hlavní autori: | , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | Korean |
| Vydavateľské údaje: |
대한의용생체공학회
01.06.2009
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| ISSN: | 1229-0807, 2288-9396 |
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| Abstract | In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients' data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects. |
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| AbstractList | In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients’ data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects.
In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients’ data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects. KCI Citation Count: 8 In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients' data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects. |
| Author | Cho, Sung-Pil 정하중 유승현 Lee, Kyoung-Joung 이경중 조성필 Hwang, Sung-Jae 김영호 Kim, Young-Ho You, Sung-Hyun 이동률 황성재 Lee, Dong-Ryul 이효기 Chung, Ha-Joong Lee, Hyo-Ki |
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| DocumentTitleAlternate | Development of a Novel Step Detection Algorithm for Gait Evaluation of Patients with Hemiplegia Based on Trunk Accelerometer |
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| Keywords | Step detection Accelerometer Least square acceleration filter Gait assessment Motion analysis system |
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| Title | 뇌졸중으로 인한 편마비 환자의 보행평가를 위한 체중심 가속도센서 기반의 새로운 보 검출 알고리즘 개발 |
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