Abstract: A bioinformatics sensor patch includes a plurality of sensing electrodes, a distance sensing element and an operation unit. The sensing electrodes senses bioinformatics of an organism. The distance sensing element senses a contact degree between the bioinformatics sensor patch and the organism and generates a corresponding contact signal. The operation unit is electrically connected to the sensing electrodes and the distance sensing element to receive the bioinformatics and the contact signal, wherein the operation unit compensates the bioinformatics or selectively outputs a control signal according to the contact signal. The above-mentioned bioinformatics sensor patch can improve a sensing accuracy of the bioinformatics.

Abstract: A heart rate detection method for calculating heart rate using heart sound from auscultation positions identified by a statistical approach utilizes a down-sampling and filtering process to acquire samples of heart sound from multiple auscultation positions of multiple testees and calculate heart rate with the samples, records time for calculating heart rate from each auscultation position of each testee and record the same from electrocardiogram, calculates a mean error and a standard deviation of the time to identify the auscultation positions allowing faster speed in heart rate detection, and applies a Bland-Altman difference plot and both a coefficient of determination and a Pearson's correlation coefficient to determine the degree of consistency and correlation of the heart rate measured from the multiple auscultation positions to identify the auscultation positions allowing generation of precise heart rate.

Abstract: A system for recognizing physiological sound comprises a receiving module, a feature extracting module, a classifier, and a comparing module. A method for recognizing physiological sound comprises receiving a physiological sound by the receiving module; extracting at least one feature from the physiological sound by the feature extraction module; classifying the at least one feature to identify at least one category by a classifier; and comparing the at least one category with a normal physiological sound and/or an abnormal physiological sound by the comparing module for evaluating a risk of disease. The method and system for recognizing physiological sound can precisely identify the specific physiological sound and exclude the noise.

Abstract: A heart rate detection method for calculating heart rate using heart sound from auscultation positions identified by a statistical approach utilizes a down-sampling and filtering process to acquire samples of heart sound from multiple auscultation positions of multiple testees and calculate heart rate with the samples, records time for calculating heart rate from each auscultation position of each testee and record the same from electrocardiogram, calculates a mean error and a standard deviation of the time to identify the auscultation positions allowing faster speed in heart rate detection, and applies a Bland-Altman difference plot and both a coefficient of determination and a Pearson's correlation coefficient to determine the degree of consistency and correlation of the heart rate measured from the multiple auscultation positions to identify the auscultation positions allowing generation of precise heart rate.

Abstract: A signal processing method in cochlear implant is performed by a speech processor and comprises a noise reduction stage and a signal compression stage. The noise reduction stage can efficiently reduce noise in a electrical speech signal of a normal speech. The signal compression stage can perform good signal compression to enhance signals to stimulate cochlear nerves of a hearing loss patient. The patient who uses a cochlear implant performing the signal processing method of the present invention can understand normal speech.

Abstract: A system for recognizing physiological sound comprises a receiving module, a feature extracting module, a classifier, and a comparing module. A method for recognizing physiological sound comprises receiving a physiological sound by the receiving module; extracting at least one feature from the physiological sound by the feature extraction module; classifying the at least one feature to identify at least one category by a classifier; and comparing the at least one category with a normal physiological sound and/or an abnormal physiological sound by the comparing module for evaluating a risk of disease. The method and system for recognizing physiological sound can precisely identify the specific physiological sound and exclude the noise.