| 研究生: |
廖徑霆 Ching-ting Liao |
|---|---|
| 論文名稱: |
運用主成分分析於加速規訊號模擬壓力中心之人體靜態平衡評估 Analogy study of center of pressure and principal components analysis based acceleration signal for evaluating human balance |
| 指導教授: |
吳天堯
Tian-yau Wu 陳怡呈 Yi-cheng Chen |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系 Department of Mechanical Engineering |
| 論文出版年: | 2014 |
| 畢業學年度: | 102 |
| 語文別: | 中文 |
| 論文頁數: | 78 |
| 中文關鍵詞: | 人體平衡 、主成分分析 、希爾伯特-黃轉換 、壓力中心 、加速規 |
| 外文關鍵詞: | human balance, Principal Components Analysis, Hilbert-Huang Transform, center of pressure, accelerometer |
| 相關次數: | 點閱:20 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
從一個人的平衡能力中能得到很多訊息,如健康狀況、老化程度等,因此受到相當程度的重視。目前常用來做為人體平衡機制研究的訊號主要是人體壓力中心訊號(center of pressure, COP),而壓力中心訊號的量測是藉由生物力學量測設備測力板來作量測。不過由於測力板的造價昂貴,且量測上有諸多不便,本研究利用電容式低頻三軸加速規訊號針對人體平衡能力作評估,取代過去常用的測力板。由於人體不停擺動,使得加速規之鉛直方向於重力加速度方向之分量為時變問題,利用將訊號分為數段,各別做主成分分析的方式,將訊號降維至平面訊號,並消除垂直方向重力加速度對水平分量訊號之影響,藉以模擬壓力中心訊號,建立兩者間之轉換關係,使加速規量測之訊號能用以同壓力中心訊號進行人體之平衡能力評估。
Most people evaluate human balance ability by analyzing the center of pressure (COP). However, the force plate which is used to measure the COP is normally expensive and is limited for measurement capability. In this study, we evaluate human balance ability through the measurements of capacitor-type accelerometer. The principal components analysis (PCA) is employed to reduce the influence of gravity component on the horizontal components while the accelerometer tilts inevitably. The signals relationship between the COP and the acceleration will be derived, so that the measurements of accelerometer can be utilized for evaluating the human balance ability.
[1] R. Moe-Nilssen, “Test-retest reliability of trunk accelerometry during standing and walking, ” Archives of Physical Medicin and Rehabilitaion, vol. 79, no. 11, pp. 1377-1385, 1998.
[2] R. Moe-Nilssen and J. L. Helbostad, “Trunk accelerometry as a measure of balance control during quiet, ” Gait Posture, vol. 16, pp. 60-68, 2002.
[3] L. Chiari, M. Dozza, A. Cappello, F. B. Horak, V. Macellari and D. Giansanti, “Audio-Biofeedback for Balance Improvement: An Accelerometry-Based System,” IEEE Transactions on Biomedical Engineerin,vol.52,pp. 2108-2111, 2005
[4] H. Lee, S. Cho, J. H. You,and K. Lee, “The concurrent validity of the body center of mass in accelerometric measurement,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology, vol.29, pp. 659-661, 2007.
[5] Hassan Ghasemzadeh, Roozbeh Jafari, and Balakrishnan Prabharan, “A body sensor network with electromyogram and inertial sensor: multimodal interpretation of muscular activities,” IEEE Transactions on Infrmation Technology in Biomedicine, vol. 14, pp. 198-206,2010.
[6] A. Martinez-Ranmirez, P. Lecumberri, M. Gomez, L. Rodriguez-Manas, F. J. Garcia, and M. Izquierdo, “ Frailty assessment based on wavelet analysis during quiet standing balance test,” Journal of Biomechanics, vol. 44, pp.2213-2220,2011.
[7] N. E. Huang, Z. Shen, S. R. Long, M. L. C. Wu, H. H. Shih, Q. N. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of the Royal Society of London Series a-Mathematical Physical and Engineering Sciences, vol. 454, pp. 903-995, 1998.
[8] Z. Wu and N. E. Huang, “Ensemble empirical mode decomposition: a noise assisted data analysis method,” Center for Ocean-Land-Atmosphere Studies, Technical Report series, vol. 193, 2005.
[9] Z. Wu and N. E. Huang, “Ensemble empirical mode decomposition: a noise assisted data analysis method,” Advances in Adaptive Data Analysis, vol. 1, pp. 1-41, 2009.
[10] K. Pearson, “On Lines and Planes of closest Fit to Systems of Points in Space,” Philosophical Magazine, vol.21,no.6, pp.5591572,1901.
[11] H. Hotelling, “Analysis of a complex of statistical variables into principal components,” Journal of Educational Psychology, vol.24, pp. 417-441, 1933.