COMPUTERIZED RADIAL ARTERY PULSE SIGNAL CLASSIFICATION FOR LUNG CANCER DETECTION

Pulse diagnosis, the main diagnosis method in traditional Chinese medicine, is a non-invasive and convenient way to check the health status. Doctors usually use three fingers to feel three positions; Cun, Guan, and Chi of the wrist pulse, to diagnose the body’s healthy status. However, it takes many years to master the pulse diagnosis. This paper aims at finding the best position for acquiring wrist-pulse-signal for lung cancer diagnosis. In our paper, the wrist-pulse-signals of Cun, Guan, and Chi are acquired by three optic fiber pressure sensors of the same type. Twelve features are extracted from the signals of these three positions, respectively. Eight classifiers are applied to detect the effectiveness of the signal acquired from each position by classifying the pulse signals of healthy individuals and lung cancer patients. The results achieved by the proposed features show that the signal acquired at Cun is more effective for lung cancer diagnosis than the signals acquired at Guan and Chi

COMPUTERIZED RADIAL ARTERY PULSE SIGNAL CLASSIFICATION FOR LUNG CANCER DETECTION

Pulse diagnosis, the main diagnosis method in traditional Chinese medicine, is a non-invasive and convenient way to check the health status. Doctors usually use three fingers to feel three positions; Cun, Guan, and Chi of the wrist pulse, to diagnose the body’s healthy status. However, it takes many years to master the pulse diagnosis. This paper aims at finding the best position for acquiring wrist-pulse-signal for lung cancer diagnosis. In our paper, the wrist-pulse-signals of Cun, Guan, and Chi are acquired by three optic fiber pressure sensors of the same type. Twelve features are extracted from the signals of these three positions, respectively. Eight classifiers are applied to detect the effectiveness of the signal acquired from each position by classifying the pulse signals of healthy individuals and lung cancer patients. The results achieved by the proposed features show that the signal acquired at Cun is more effective for lung cancer diagnosis than the signals acquired at Guan and Chi

Development of a Tonometric Sensor with a Decoupled Circular Array for Precisely Measuring Radial Artery Pulse

The radial artery pulse is one of the major diagnostic indices used clinically in both Eastern and Western medicine. One of the prominent methods for measuring the radial artery pulse is the piezoresistive sensor array. Independence among channels and an appropriate sensor arrangement are important for effectively assessing the spatial-temporal information of the pulse. This study developed a circular-type seven-channel piezoresistive sensor array using face-down bonding (FDB) as one of the sensor combination methods. The three-layered housing structure that included independent pressure sensor units using the FDB method not only enabled elimination of the crosstalk among channels, but also allowed various array patterns to be created for effective pulse measurement. The sensors were arranged in a circular-type arrangement such that they could estimate the direction of the radial artery and precisely measure the pulse wave. The performance of the fabricated sensor array was validated by evaluating the sensor sensitivity per channel, and the possibility of estimating the blood vessel direction was demonstrated through a radial artery pulse simulator. We expect the proposed sensor to allow accurate extraction of the pulse indices for pulse diagnosis