Abstract: An apparatus and method for evaluating obstructive sleep apnea with PPG signal are provided. Measured heartbeat interval signal is used to evaluate whether there is obstructive apnea. The system includes a motion sensor for detecting whether a user is in a stationary state; an optical sensor for measuring the heartbeat interval signal of the user in a stationary state; a microprocessor for processing the heartbeat interval signal of the user to obtain an apnea parameter; an alert module for receiving the apnea parameter and feeding them back to the user; and a memory module for storing the apnea parameter after the signal processing. The system and method are used to determine whether the heartbeat interval signal is an obstructive sleep apnea signal, and further determine whether the user is in an obstructive sleep apnea situation.

Abstract: A computation apparatus, a cardiac arrhythmia assessment method thereof and a non-transitory computer-readable recording medium are provided. In the method, electrocardiography (ECG) signal is obtained. Whether the ECG signal is conformed to a first abnormal rhythm symptom is determined. Then, whether the ECG signal is conformed to a second abnormal rhythm symptom different from the first abnormal rhythm symptom is determined based on the determined result of the first abnormal rhythm symptom. Accordingly, multiple abnormal rhythm assessments are integrated, the subsequent assessment is speeded-up and optimized according to the determined result of a previous assessment, so as to enable to implement on a handheld apparatus.

Abstract: A transfer printing paper is provided. The transfer printing paper includes a release layer and a conductive layer. The conductive layer is formed on the release layer and is suitable for being transferred to a flexible material layer. After being transferred to the flexible material layer, the conductive layer is configured to be electrically in contact with a wearer wearing the flexible material layer, so as to conduct a physiological signal of the wearer.

Abstract: A computation apparatus, a cardiac arrhythmia assessment method thereof and a non-transitory computer-readable recording medium are provided. In the method, electrocardiography (ECG) signal is obtained. Whether the ECG signal is conformed to a first abnormal rhythm symptom is determined. Then, whether the ECG signal is conformed to a second abnormal rhythm symptom different from the first abnormal rhythm symptom is determined based on the determined result of the first abnormal rhythm symptom. Accordingly, multiple abnormal rhythm assessments are integrated, the subsequent assessment is speeded-up and optimized according to the determined result of a previous assessment, so as to enable to implement on a handheld apparatus.

Abstract: A wearable device capable of detecting sleep apnea comprising a processor and an electrocardiogram sensor is provided. The processor trains a neural network module to create a sleep apnea detection model. An electrocardiogram sensor senses an electrocardiogram signal of a sleep situation. The processor analyzes the electrocardiogram signal to detect a plurality of R-waves in the electrocardiogram signal. The processor performs an R-wave amplitude analysis operation, an R-wave angle analysis operation, and a heart rate variability analysis operation according to the R-waves to obtain a plurality of characteristic values. The processor utilizes the trained sleep apnea detection model to perform a sleep apnea detection operation based on the characteristic values, so as to detect whether the sleep situation has a sleep apnea event.

Abstract: A wearable device capable of recognizing sleep stage including a processor, an electrocardiogram sensor, an acceleration sensor and an angular acceleration sensor is provided. The processor trains a neural network module. The electrocardiogram sensor generates an electrocardiogram signal. The processor analyzes the electrocardiogram signal to generate a plurality of first characteristic values. The acceleration sensor generates an acceleration signal. The processor analyzes the acceleration signal to generate a plurality of second characteristic values. The angular acceleration sensor generates an angular acceleration signal. The processor analyzes the angular acceleration signal to generate a plurality of third characteristic values. The processor utilizes the trained neural network module to perform a sleep stage recognition operation according to the first characteristic values, the second characteristic values and the third characteristic values, so as to obtain a sleep stage recognition result.

Abstract: A wearable device capable of recognizing doze-off stage including a processor and an electrocardiogram sensor is provided. The processor trains a neural network module. The processor is coupled to the electrocardiogram sensor. The electrocardiogram sensor is configured to generate an electrocardiogram signal. The processor performs a heart rate variability analysis operation and a R-wave amplitude analysis operation to analyze a heart beat interval variation of the electrocardiogram signal, so as to generate a plurality of characteristic values. The processor utilizes the trained neural network module to perform a doze-off stage recognition operation according to the characteristic values, so as to obtain a doze-off stage recognition result. In addition, a recognition method is also provided.

Abstract: A transfer printing paper is provided. The transfer printing paper includes a release layer and a conductive layer. The conductive layer is formed on the release layer and is suitable for being transferred to a flexible material layer. After being transferred to the flexible material layer, the conductive layer is configured to be electrically in contact with a wearer wearing the flexible material layer, so as to conduct a physiological signal of the wearer.