Abstract: A voice event detection apparatus is disclosed. The apparatus comprises a vibration to digital converter and a computing unit. The vibration to digital converter is configured to convert an input audio signal into vibration data. The computing unit is configured to trigger a downstream module according to a sum of vibration counts of the vibration data for a number X of frames. In an embodiment, the voice event detection apparatus is capable of correctly distinguishing a wake phoneme from the input vibration data so as to trigger a downstream module of a computing system. Thus, the power consumption of the computing system is saved.

Abstract: A vital-sign detection system is provided. The vital-sign detection system includes a vital-sign detection device and a controller. The vital-sign detection device is enabled to detect a vital-sign of a user. The controller determines whether the gets in the bed and controls the vital-sign detection device to switch to a disabled mode from a first enabled mode in response to the user getting in the bed. During a period when the vital-sign detection device is in the disabled mode, the controller determines whether the user falls asleep. In response to the user falling asleep, the controller controls the vital-sign detection device to switch to a second enabled mode from the disabled mode.

Abstract: A voice event detection apparatus is disclosed. The apparatus comprises a vibration to digital converter and a computing unit. The vibration to digital converter is configured to convert an input audio signal into vibration data. The computing unit is configured to trigger a downstream module according to a sum of vibration counts of the vibration data for a number X of frames. In an embodiment, the voice event detection apparatus is capable of correctly distinguishing a wake phoneme from the input vibration data so as to trigger a downstream module of a computing system. Thus, the power consumption of the computing system is saved.

Abstract: A vital-sign detection system is provided. The vital-sign detection system includes a vital-sign detection device and a controller. The vital-sign detection device is enabled to detect a vital-sign of a user. The controller determines whether the gets in the bed and controls the vital-sign detection device to switch to a disabled mode from a first enabled mode in response to the user getting in the bed. During a period when the vital-sign detection device is in the disabled mode, the controller determines whether the user falls asleep. In response to the user falling asleep, the controller controls the vital-sign detection device to switch to a second enabled mode from the disabled mode.

Abstract: A physiological monitoring system is provided. The physiological monitoring system includes a vital-sign detection device and a controller. The vital-sign detection device emits visible light during a first period to detect a vital-sign of an object. During the first period, the controller determines whether a first predetermined event occurs. In response to the first predetermined event occurring, the controller controls the vital-sign detection device to emit invisible light during a second period to detect the vital-sign.

Abstract: A physiological monitoring device is provided. The physiological monitoring device includes a physiological sensor, a quality estimator, and a feature extractor. The physiological sensor is configured to sense a physiological feature to generate a bio-signal. The quality estimator estimates quality of the bio-signal. The feature extractor receives the bio-signal and performs a predetermined operation to the bio-signal to obtain feature data. The amount of computation induced by the predetermined operation tier the feature extractor is changed according to the estimated quality of the bio-signal.

Abstract: A sleep quality management apparatus includes a sensor module and a processing unit. The sensor module is configured to provide a heart rate signal and a skin conductance signal. The processing unit is coupled to the sensor module. The processing unit is configured to determine a sleep stage and a stress level according to the heart rate signal and the skin conductance signal so as to identify a stressful dream occurrence. The stressful dream occurrence is identified when the sleep stage corresponds to a rapid eye movement (REM) stage and the stress level corresponds to a stressful state.