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 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 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 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.

Abstract: A textile structure adapted to be electrically connected to an electronic device is provided. The textile structure includes a first fabric layer, a second fabric layer, and a third fabric layer. The second fabric layer is electrically conductive. The first, the second, and the third fabric layers are combined with each other, and the second fabric layer is located between the first and the third fabric layers. The third fabric layer has an opening covered by the second fabric layer, and a portion of the second fabric layer is exposed from the third fabric layer through the opening. The electronic device is electrically connected to the second fabric layer, and a junction between the electronic device and the second fabric layer is far away from the opening.

Abstract: A gait evaluation method using a sensor worn by the user for evaluating the gait of the user includes the following steps. A plurality of first acceleration values, a plurality of second acceleration values and a plurality of third acceleration values on a first direction, a second direction and a third direction corresponding to the user within a walking period of the user are obtained from the sensor worn by the user. Based on the first acceleration values, the second acceleration values, the third acceleration values and a wearing position of the sensor on the user, a sway index, a step index and a slouch index related to the user are calculated. A gait evaluation is generated according to the sway index, the step index and the slouch index. An electronic device suitable for applying the gait evaluation method is also provided in the present application.

Abstract: A wearable medical sensor system includes a piece of clothes and an elastic bounding layer attached in the clothes. The piece of clothes includes a main body with a shape symmetric on both sides with respect to an axis of symmetry and a couple of sleeves symmetrically connected to both sides of the main body. At least a part of the main body is surrounded by the elastic bounding layer. First to Fifth electrodes are attached on the elastic bounding layer corresponding to the same surface of the clothes. The elastic bounding layer is more stretchable and more contractible than the clothes.

Abstract: A textile structure adapted to be electrically connected to an electronic device is provided. The textile structure includes a first fabric layer, a second fabric layer, and a third fabric layer. The second fabric layer is electrically conductive. The first, the second, and the third fabric layers are combined with each other, and the second fabric layer is located between the first and the third fabric layers. The third fabric layer has an opening covered by the second fabric layer, and a portion of the second fabric layer is exposed from the third fabric layer through the opening. The electronic device is electrically connected to the second fabric layer, and a junction between the electronic device and the second fabric layer is far away from the opening.

Abstract: A measurement system of respiration-related signals includes a plurality of electrodes, an ECG processing device, and an analysis device. The ECG processing device acquires a first analog differential signal and a second analog differential signal through the electrodes and generates a Lead-I ECG signal and a Lead-II ECG signal which is orthogonal to the Lead-I ECG signal after processing the two analog differential signals. The analysis device executes a trigonometric function to calculate angle change values of a cardiac axis based on the acquired Lead-I ECG signal and the Lead-II ECG signal, and further generate a cardiac axis angle change waveform according to the continuous angle change values. Accordingly, the cardiac axis angle change waveform is suitable for the prediction of respiratory conditions of the participant because of the high positive correlation between the frequency of the cardiac axis angle change waveform and the human respiratory frequency.