Abstract: A portrait image processing method, applying to a portrait image processing device, comprising: (a) acquiring a BVP (Blood Volume Pulse) signal of a user; (b) acquiring blood flow distribution of a specific portion of a user; (c) capturing an image of a specific portion of the user; and (d) adjusting the image of the specific portion according to the BVP signal and the blood flow distribution. A portrait image processing device, which comprises a camera and a processing circuit, is also disclosed. The processing circuit can acquire BVP signals from an image captured by the camera or from a PPG sensor.

Abstract: There is provided a treadmill capable of performing the fall detection. The treadmill includes a light sensor and a processor. The light sensor acquires an image frame toward an operation space. The processor performs the occupancy detection on the image frame using face detection and human detection. Upon not detecting the operation space being occupied by any user during a running state of the treadmill, the processor deactivates the treadmill and raises a fall alarm.

Abstract: A portrait image processing method, applying to a portrait image processing device, comprising: (a) acquiring a BVP (Blood Volume Pulse) signal of a user; (b) acquiring blood flow distribution of a specific portion of a user; (c) capturing an image of a specific portion of the user; and (d) adjusting the image of the specific portion according to the BVP signal and the blood flow distribution. A portrait image processing device, which comprises a camera and a processing circuit, is also disclosed. The processing circuit can acquire BVP signals from an image captured by the camera or from a PPG sensor.

Abstract: A method for establishing a personal blood pressure estimation model dedicated for a specific user includes: receiving a first reference measurement result of a reference sphygmomanometer; using a physiological sensor to measure the specific user's blood pressure to generate a first photoplethysmogram signal; calculating a first estimation result of the blood pressure of the specific user according to the first photoplethysmogram signal; generating a first regulating parameter by comparing the first reference measurement result with the first estimation result; and establishing the personal blood pressure estimation model by using the first regulating parameter to adjust a set of parameter factor(s) of a basic blood pressure estimation model.

Abstract: A method for obtaining an estimation of a physiological feature of a specific user includes: using a physiological sensor device under a normal sensing mode to sense the physiological feature of the specific user to generate a physiological signal of the normal sensing mode; determining a matched physiological signal from a plurality of test physiological signals by comparing the plurality of test physiological signals with the physiological signal of the normal sensing mode; and calculating a resultant estimation of the physiological feature of the specific user according to the matched physiological signal and the profile of the physiological feature of the specific user.

Abstract: There is provided an operating method of an AF detection device including a reference model construction step and a continuous detection step. In the reference model construction step, heartbeat waveforms of a PPG signal of a user are classified to construct a personal reference model. In the continuous detection step, current heartbeat waveforms of a PPG signal of the same user is compared with the personal reference model to identify whether each of the heartbeat waveforms is an AF waveform.

Abstract: A method for establishing a personal blood pressure estimation model dedicated for a specific user includes: receiving a first reference measurement result of a reference sphygmomanometer; using a PPG sensor to measure a blood pressure of the specific user to generate a first PPG signal; calculating a first estimation result of the blood pressure of the specific user according to the first PPG signal; generating a first regulating parameter by comparing the first reference measurement result with the first estimation result; and establishing the personal blood pressure estimation model by using the first regulating parameter to adjust a set of parameter factor (s) of a basic blood pressure estimation model.

Abstract: A method for obtaining an estimation of a physiological feature of a specific user includes: using a physiological sensor device under a normal sensing mode to sense the physiological feature of the specific user to generate a physiological signal of the normal sensing mode; determining a matched physiological signal from a plurality of test physiological signals by comparing the plurality of test physiological signals with the physiological signal of the normal sensing mode; and calculating a resultant estimation of the physiological feature of the specific user according to the matched physiological signal and the profile of the physiological feature of the specific user.

Abstract: A context-based adaptive binary arithmetic coding (CABAC) decoding device and a coding method thereof are provided. The device comprises: a context memory address calculator, calculating an address identifying a memory location in a context model memory for storage of a context model in next cycle; a mixed context memory, in which the context model of the context memory address calculator is stored and from which the context model is read; a two-bin context adaptive binary arithmetic decoder, outputting several parameters for updating the range and offset of the context model, based on the context model of the mixed context memory and deciding several bins; and a binary syntax element comparator, judging whether a current binary sequence corresponds to the value of syntax elements, based on the bins so as to select a correct memory address.

Abstract: A context-based adaptive binary arithmetic coding (CABAC) decoding device and a coding method thereof are provided. The device comprises: a context memory address calculator, calculating an address identifying a memory location in a context model memory for storage of a context model in next cycle; a mixed context memory, in which the context model of the context memory address calculator is stored and from which the context model is read; a two-bin context adaptive binary arithmetic decoder, outputting several parameters for updating the range and offset of the context model, based on the context model of the mixed context memory and deciding several bins; and a binary syntax element comparator, judging whether a current binary sequence corresponds to the value of syntax elements, based on the bins so as to select a correct memory address.