Abstract: The present invention discloses a home infotainment system having function of non-contact imaging-based physiological signal measurement. In the present invention, an image-based physiological signal (IBPS) measuring device is integrated with a television, and is configured for capture at least one image frame of a user who is watching the television. As such, after detecting detects a face portion from the image frame, the IBPS measuring device is able to subsequently extract at least one physiological signal from the face portion. Consequently, after the physiological signal is applied with at least one signal process by a display processor of the television or the IBPS measuring device, physiological indices of the user are hence calculated, and are subsequently applied with data processes of data storing, data transmitting, and/or displaying the physiological indices by a form of graphs, or diagrams, and/or numeric values.

Abstract: A health management system using contactless physiological measurement technology is disclosed. The health management system principally comprises a camera and a first processor, of which the camera is faced to a user for capturing a user image. The first processor is particularly configured to have a face detection unit and an activity index calculating unit therein. By such arrangement, after receiving the user image from the camera, the first processor detects a face portion from the user image, thereby subsequently extracting a PPG signal from the face portion. Consequently, after completing at least one process of the PPG signal, multiple indexes for describing a user's health activity are generated. The health activity indexes include health index, activity index, stability index, relaxation index, metabolism index, and balance index. Therefore, the first processor achieves an evaluation of the user's health activity state according to the forgoing health activity indexes.

Abstract: A biological image processing method is provided. The method acquires first time-frequency data from an image data; processing the first time-frequency data into the second time-frequency data using a filter module; and converting the second time-frequency data into a time domain signal. The filter module is obtained by machine learning, and is trained using a first sample time-frequency signal as input and a second sample time-frequency signal as output, wherein the noise of the time domain signal corresponding to the second sample time-frequency signal is less than the noise of the time domain signal corresponding to the first sample time-frequency signal. A biological information detection device is also provided.

Abstract: A method of liveness detection for a computing device comprises acquiring at least one full cycle of a remote photoplethysmography, rPPG, signal from a skin image, extracting at least one rPPG waveform characteristic from the full cycle of the rPPG signal, and determining whether the skin image includes a life according to the extracted rPPG waveform characteristic.

Abstract: The present invention discloses a home infotainment system having function of non-contact imaging-based physiological signal measurement. In the present invention, an image-based physiological signal (IBPS) measuring device is integrated with a television, and is configured for capture at least one image frame of a user who is watching the television. As such, after detecting detects a face portion from the image frame, the IBPS measuring device is able to subsequently extract at least one physiological signal from the face portion. Consequently, after the physiological signal is applied with at least one signal process by a display processor of the television or the IBPS measuring device, physiological indices of the user are hence calculated, and are subsequently applied with data processes of data storing, data transmitting, and/or displaying the physiological indices by a form of graphs, or diagrams, and/or numeric values.

Abstract: Disclosures of the present invention describe a non-contact physiological signal measuring device comprising a light sensing unit and a signal processing module, wherein the light sensing unit is adopted for collecting a scattered light from a surface of a sensing portion of a subject. After receiving the scattered light by a signal receiving unit of the signal processing module, a signal processing unit can subsequently obtain physiological characteristic(s) after applying signal process to a physiological signal with respect to the scattered light. Particularly, this novel non-contact physiological signal measuring device does not include any one camera or image capturing unit, such that the subject is able to receive a physiological signal measurement in the case of having well a personal privacy protection as well as preventing the subject's skin from being hurt.

Abstract: A method of liveness detection for a computing device comprises acquiring at least one full cycle of a remote photoplethysmography, rPPG, signal from a skin image, extracting at least one rPPG waveform characteristic from the full cycle of the rPPG signal, and determining whether the skin image includes a life according to the extracted rPPG waveform characteristic.

Abstract: A drunken driving judgment system includes an image capturing module configured to obtain multiple images associated with a subject; a physiological parameter computing module coupled to the image capturing module, and configured to generate at least one physiological parameter according to the multiple images associated with the subject, wherein the at least one physiological parameter comprises at least one of a Remote PhotoPlethysmoGraphy, a heart rate, a heart rate variability, a blood oxygen, a breath rate, and a blood pressure; and an alcohol detection calculation unit coupled to the physiological parameter computing module, and configured to generate a drunken driving judgment result according to the at least one physiological parameter to indicate whether the subject is drunken.

Abstract: A biological image processing method is provided. The method acquires first time-frequency data from an image data; processing the first time-frequency data into the second time-frequency data using a filter module; and converting the second time-frequency data into a time domain signal. The filter module is obtained by machine learning, and is trained using a first sample time-frequency signal as input and a second sample time-frequency signal as output, wherein the noise of the time domain signal corresponding to the second sample time-frequency signal is less than the noise of the time domain signal corresponding to the first sample time-frequency signal. A biological information detection device is also provided.

Abstract: An image processing method for image-based physiological measurement, includes converting at least one user's image signal into image data; determining at least one region of interest within the image data; analyzing image information inside the region of interest to generate physiological information of the user; determining a feedback control signal or a control signal to optimize the physiological information of the user; and adjusting an image sensing unit or an image signal processing unit according to the feedback control signal or the control signal.

Abstract: A system of determining physiological state includes a physiological measuring device configured to measure at least one physiological parameter of a user, a user interface configured to receive at least one physiological information of the user, and a processing unit coupled to the physiological measuring device and the user interface, and configured to determine at least one normal threshold and at least one abnormal threshold of the at least one physiological parameter according to the at least one physiological information, and determine a physiological state of the user is normal or abnormal according to the at least one physiological parameter, the at least one normal threshold and the at least one abnormal threshold.

Abstract: A method for evaluating systolic and diastolic blood pressures of a subject for a blood pressure detecting system is disclosed. The blood pressure detecting system includes a processing module and an image capturing module configured to continuously records a hand and a face of a subject to retrieve multiple hand and face images associated with the subject. The method includes, by the processing module, obtaining biological information related to blood pressure of the subject according to the multiple hand and face images retrieved by the image capturing module; and, by the processing module, obtaining prediction results of systolic and diastolic blood pressures of the subject according to the biological information related to blood pressure of the subject.