| Summary: | 碩士 === 中原大學 === 電機工程研究所 === 96 === The main goal of this thesis is to use the Recording Gauge for Chinese Medical Auscultation Examination and Diagnosis to classify and identify the voice signal between the healthy people and the deficiency of vital energy patients.
The traditional Chinese Medicine doctor uses the major methods of diagnosis “observing, auscultation and smelling, enquiry and feeling patients’ pulse “to discriminate and diagnose symptoms of a disease clinically. In listening examination, the method used in diagnosis is divided into listening and smelling. Because the diagnosis process usually needs to be judged by the Chinese Medicine doctor with enough clinical experience, it leads to the diagnosis which is not objective. Up to now, the major study in listening examination still emphasizes on analyzing patients’ voices.
We collected 63 patients’ voice samples (There were 52 healthy people and 11 deficiency of vital energy patients). We recorded the voice signals of English vowel /a/ and let these signals to be analyzed by 4 deficiency of vital energy disease parameters. We use the Recording Gauge for Chinese Medical Auscultation Examination and Diagnosis to examine and record human data.
Our research uses the Recording Gauge for Chinese Medical Auscultation Examination and Diagnosis to examine and record human data. The main structure of the Recording Gauge for Chinese Medical Auscultation Examination and Diagnosis is based on MSP430 microprocessor. The Recording Gauge for Chinese Medical Auscultation Examination and Diagnosis uses its microphone which can fix distance to record voice signals of healthy people and patients, establishes signal files, then analyzes these data. We use four parameters(Average zero-crossing rates, variations in local peaks and valleys, and Spectral energy ratio of high frequency region and low frequency region ) to analyze signals and find difference property of signals.
According to recognizing vital energy patients and healthy people, The voice waveform of deficiency of vital energy patients is weaker than healthy people in minor-wave intensity. We also find out that the power spectrum has clear difference between the two voice waveform. As the analysis result, we came up with a 76% accuracy comparing to physician’s diagnosis.
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