中原大學電機工程學系
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中醫氣虛証型之聞診語音訊號分析
指導老師:林康平   組長:孫譽豪   組員:孫譽豪
本研究利用現有語音信號處理常用的幾個方法,如快速傅利葉轉
換、線性預估、以及在頻譜上的高低頻能量分析,這些在時域與頻域上的分析方法,將"語音訊號處理"與"中醫聞診"兩者結合,並整合到Apple 公司的iPad裝置上,透過iPad 的錄音設備,將語音紀錄下來分析,發現正常人的聲音比氣虛患者的聲音更為穩定,語音的強度波形也幾乎沒什麼太大的變化。而氣虛患者的發音,因為無法維持語音波形的平穩,會出現較大的波形改變,用”費雪分類”這個方法來區分出正常人與虛症患者的不同。
This study used the methods of digital signal processing such as fast Fourier transformation, linear prediction coding, and power spectrum to analyze the recorded data in this study. The combination of Chinese medicine and automatic speech recognition technology based on major analysis methods of time-domain,frequency-domain and integrated interface with Apple iPad system. The study recorded voice for analysis by using iPad. The study compared all of the data and found that the voice signals of healthy subjects showed to be more stable than unhealthy subjects. Healthy subjects did not show difference from the start to the end of the recorded voice.
However, unhealthy subjects had difficulty of maintaining a stable voice. Their voices presented various formants around the end of lasting voice. Since unhealthy subjects could not maintain stable voice, their LPC spectrums drifted or disappeared. In addition, healthy subjects were more stable than unhealthy subjects in the special region of power spectrum. This study designed two features and used the fisher discriminate methods to analyze and discriminate subject’s health.
我們決定將壓電陶瓷晶片和鞋子做結合。
   
 
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