Energy analysis of rolling manipulation force signal based on wavelet transform

被引：0

作者：

Lv, Jie ^{[1
]}

Cao, Jin-Feng ^{[1
]}

Fang, Lei ^{[2
]}

Ma, Long-Long ^{[1
]}

Zhang, Dan-Song ^{[1
]}

Fang, Zhou ^{[1
]}

Xu, Shi-Xiong ^{[1
]}

Fang, Min ^{[2
]}

机构：

[1] Mechanics and Engineering Science Department, Fudan University, Shanghai 200433, China

[2] Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China

来源：

Yiyong Shengwu Lixue/Journal of Medical Biomechanics | 2010年 / 25卷 / 06期

关键词：

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

ObjectiveTo analyze the energy of rolling manipulation in different frequency bands and find the features of rolling manipulation dynamics. MethodThe force signals of rolling manipulation of six experts and six beginners were measured and divided into different frequency bands by wavelet transform to calculate the energy. Through statistical analysis, 18 characteristic quantities of horizontal force or vertical force were created and the overall evaluation coefficient R was proposed. ResultsAbout 70% of experts' rolling manipulation energy was found in 0~0.40625 Hz and about 20% energy in 1.625~3.25 Hz. The overall evaluation coefficient -R of 6 experts was over 0.70, while R of beginners was below 0.70, which showed the difference was significant. ConclusionsThe energy distribution of rolling manipulation reflects the characteristics of softness and periodicity. If the rolling manipulation is in accordance with the manipulative requirement and the overall evaluation coefficients R is over 0.70, it could be said that the operator masters the rolling manipulation well.

引用

页码：439 / 443

共 50 条

[21] Wavelet transform analysis and the detection of singularity signal
Chen Lu-ning
Ding Ning
[J]. Proceedings of 2004 Chinese Control and Decision Conference, 2004, : 668 - 670
[22] ERG signal analysis using wavelet transform
Barraco, R.
Adorno, D. Persano
Brai, M.
[J]. THEORY IN BIOSCIENCES, 2011, 130 (03) : 155 - 163
[23] Formantic Analysis of Speech Signal by Wavelet Transform
Falek, L.
Amrouche, A.
Fergani, L.
Teffahi, H.
Djeradi, A.
[J]. WORLD CONGRESS ON ENGINEERING, WCE 2011, VOL II, 2011, : 1572 - 1576
[24] Applications of wavelet transform to radar signal analysis
[J]. Dianzi Keji Diaxue Xuebao, 8 (198):
[25] Unsteady signal analysis by using wavelet transform
Zhang, Z
Kawabata, H
[J]. 1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT PROCESSING SYSTEMS, VOLS 1 & 2, 1997, : 1237 - 1241
[26] Signal analysis and synthesis with using the wavelet transform
Aleshin, V.B.
Krylov, V.V.
[J]. Radiotekhnika, 1998, (01): : 24 - 28
[27] Extraction of MHD Signal Based on Wavelet Transform
赵晴初
赵彤
李旻
黄胜华
徐佩霞
[J]. Plasma Science & Technology, 2002, (04) : 1367 - 1374
[28] A Signal Denoise Algorithm Based On Wavelet Transform
Jing, Jiang
Lin, Jiang
[J]. 2012 INTERNATIONAL CONFERENCE ON INDUSTRIAL CONTROL AND ELECTRONICS ENGINEERING (ICICEE), 2012, : 1819 - 1820
[29] The signal processing technology based on wavelet transform
Zhang, G
Zhou, Z
Chen, YP
[J]. INTERNATIONAL CONFERENCE ON SENSOR TECHNOLOGY (ISTC 2001), PROCEEDINGS, 2001, 4414 : 455 - 459
[30] EEG Signal Denoising based on Wavelet Transform
Harender
Sharma, R. K.
[J]. 2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 1, 2017, : 758 - 761

← 1 2 3 4 5 →