Detection and Application of Organic Disease With Phonocardiac Spectrometry

Western medicine, as to disease detection, is based on histological pathology and organ anatomy, therefore biochemistry and medical imageology were developed to determine the location and mechanism of the sickness. Chinese medicine, in the other way around, follow the harmony between man and nature, creating four ways of diagnosis, namely looking, listening, questioning and pulse feeling, which evaluate the physiological homeostasis by the yin-yang of qi and blood, further judging the energy exchange between individual and the universe.

Pulse sound provides perfect detection of disease in Chinese medicine. Hence we plan to digitalize the pulse sound for a better interpretation of the sickness. According to past studies of pulse sound from radial artery, the lower frequency is below 25Hz, which falls into the detection range of Messener's corpuscles (2-80Hz), which are located intensively in index and middle fingers. However, radial artery is relative thinner and the pulse sound is not easy to target by the microphone, not to mention the interference from artery sclerosis. To this end our research group developed Phonocardiac spectrometry (PCS) to replace the traditional pulse instrument.

Since heart beats continuously, we hypothesize that each organ is regularly sending the signal back to heart, which modulate the contraction and beating of heart, reflecting different state of each organ. Heart is just like the commander of an orchestra band, who can direct the rhythm and style of the band by the music score and instruments. Once the instrument is damaged, the commander (heart) also adjusts himself. PCS can easily locate the pulse sound, and directly detect and analyze the cardiac spectrum. The real-time state in heart-organ axis can be readily monitored, recorded and investigated by PCS.

Our preliminary analysis focuses on patients with liver and pancreatic cancers. The results demonstrate the different pattern of cardiac spectrum between patients and normal people, which can be further sorted by disease types. By applying PCS measurement and the novel algorithm calculation to various diseases, we aim to build up a novel platform for disease screening or even diagnosis.