A biological signal acquirer is attached to a subject and acquires a biological signal of the subject. A transmitter carried by the subject transmits the biological signal. A first communication port and a first camera are installed in a first location and connectable to a network. A second communication port and a second camera are installed in a second location and connectable to the network. A biological information acquiring device is connectable to the network and provided with a switcher. The switcher acquires, when communication establishment between the transmitter and the first communication port is detected, the biological signal through the first communication port as well as a first image taken by the first camera, and acquires, when communication establishment between the transmitter and the second communication port is detected, the biological signal through the second communication port as well as a second image taken by the second camera.

A biological signal acquirer is attached to a subject and acquires a biological signal of the subject. A transmitter carried by the subject transmits the biological signal. A first communication port and a first camera are installed in a first location and connectable to a network. A second communication port and a second camera are installed in a second location and connectable to the network. A biological information acquiring device is connectable to the network and provided with a switcher. The switcher acquires, when communication establishment between the transmitter and the first communication port is detected, the biological signal through the first communication port as well as a first image taken by the first camera, and acquires, when communication establishment between the transmitter and the second communication port is detected, the biological signal through the second communication port as well as a second image taken by the second camera.

Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.

Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.

A method for evaluating a treatment for a brain condition, including: extracting one or more microstate parameter values from at least one EEG signal that was measured after the treatment; and evaluating at least one parameter of the treatment based on the one or more microstate parameter values.

A method for evaluating a treatment for a brain condition, including: extracting one or more microstate parameter values from at least one EEG signal that was measured after the treatment; and evaluating at least one parameter of the treatment based on the one or more microstate parameter values.

A light health care system including a physiological sensing device, a processor, and a light source device is provided. The physiological sensing device is adapted to acquire physiological data of a user. The processor is coupled to the physiological sensing device, and the processor acquires at least one light parameter corresponding to the physiological data according to the physiological data. The light source device is coupled to the processor, and the light source device outputs a light beam according to the at least one light parameter, wherein a green light beam or a blue light beam in the light beam accounts for more than 40% of the light beam. A light health care method is also provided.

A light health care system including a physiological sensing device, a processor, and a light source device is provided. The physiological sensing device is adapted to acquire physiological data of a user. The processor is coupled to the physiological sensing device, and the processor acquires at least one light parameter corresponding to the physiological data according to the physiological data. The light source device is coupled to the processor, and the light source device outputs a light beam according to the at least one light parameter, wherein a green light beam or a blue light beam in the light beam accounts for more than 40% of the light beam. A light health care method is also provided.

A method for monitoring a subject, includes: capturing high-bandwidth data pertaining to the subject; cyclically storing a recent portion of the high-bandwidth data in a first memory; monitoring one or more physiological signals of the subject; analyzing the monitored physiological signals to allow detection of one or more target events; upon detection of a target event: copying a then recent portion of the high-bandwidth data from the first memory to a second memory; and storing high-bandwidth captured in a predetermined period subsequent to the detection in the second memory. The one or more physiological signals include EEG. The one or more target events include epileptic seizures. A computer program product and a system may use the method.

A method for monitoring a subject, includes: capturing high-bandwidth data pertaining to the subject; cyclically storing a recent portion of the high-bandwidth data in a first memory; monitoring one or more physiological signals of the subject; analyzing the monitored physiological signals to allow detection of one or more target events; upon detection of a target event: copying a then recent portion of the high-bandwidth data from the first memory to a second memory; and storing high-bandwidth captured in a predetermined period subsequent to the detection in the second memory. The one or more physiological signals include EEG. The one or more target events include epileptic seizures. A computer program product and a system may use the method.