Example systems, methods, and apparatus, including cognitive platforms, are provided for computing performance metrics of an individual based at least in part on user interaction(s) with computerized tasks and/or interference and at least one physiological measure of the individual, where the performance metric provides an indication of the cognitive abilities of the individual. The apparatus can be coupled to at least one physiological component to perform the physiological measurement of the individual. The apparatus also can be configured to adapt the tasks and/or interferences to enhance the individual's cognitive abilities.

Example systems, methods, and apparatus, including cognitive platforms, are provided for computing performance metrics of an individual based at least in part on user interaction(s) with computerized tasks and/or interference and at least one physiological measure of the individual, where the performance metric provides an indication of the cognitive abilities of the individual. The apparatus can be coupled to at least one physiological component to perform the physiological measurement of the individual. The apparatus also can be configured to adapt the tasks and/or interferences to enhance the individual's cognitive abilities.

A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.

A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.

A multi-sensor patch for simultaneous abdominal monitoring of maternal and fetal physiological data includes a multi-layer flexible substrate with a center region and a plurality of electrode regions. A conductive layer of the flexile substrate provides an electrical connection between each of the plurality of electrode regions and the center region. A plurality of electrodes are formed into the flexible substrate. At least one mechanical motion sensor is connected to the multi-layer flexible substrate. A module unit is connected to the conductive layer at the center region. The module unit includes a controller configured to receive biopotential physiological data from the plurality of electrodes and mechanical sensor data from the at least one auxiliary sensor. The controller calculates at least fetal heart rate, maternal heart rate, and uterine activity from the biopotential physiological data and from the mechanical sensor data.

An environment control system includes: an environment control apparatus installed in a room; a human body state detection unit configured to detect human body sensor information; an environmental state detection unit configured to detect environmental sensor information; a sleep state determination unit configured to determine whether a sleep state is any one of a hypnagogic state, a sleeping state or a wakefulness state; a learning unit configured to learn a predicted sleep rhythm of the human body based on the human body sensor information, the environmental sensor information, and a determination result of the sleep state; a control content determination unit configured to determine control content of the environment control apparatus such that the predicted sleep rhythm obtained by learning approaches an ideal sleep rhythm; and an apparatus control unit configured to control the environment control apparatus based on the control content determined.

An emotion detecting device includes a memory, a processor and an output/input device. An emotion template with a plurality of emotional statuses is stored in the memory. The processor is configured to receive characteristic values transformed from brain waves of a pet and determine whether the brain waves correspond to a stable state based on variation of the characteristic values during a period. When it is determined that the brain waves correspond to the stable state, the processor determines whether the brain waves match some emotional status among the emotional statuses. When the brain waves match the emotional status, the output/input device outputs information regarding the pet being in the emotional status. When the brain waves do not match any of the emotional statuses in the emotion template, the processor updates the emotion template based on a confirm operation and the characteristic values.

An emotion detecting device includes a memory, a processor and an output/input device. An emotion template with a plurality of emotional statuses is stored in the memory. The processor is configured to receive characteristic values transformed from brain waves of a pet and determine whether the brain waves correspond to a stable state based on variation of the characteristic values during a period. When it is determined that the brain waves correspond to the stable state, the processor determines whether the brain waves match some emotional status among the emotional statuses. When the brain waves match the emotional status, the output/input device outputs information regarding the pet being in the emotional status. When the brain waves do not match any of the emotional statuses in the emotion template, the processor updates the emotion template based on a confirm operation and the characteristic values.

A system includes a sensing module configured to collect physiological information from a user; an audio input device configured to capture auditory content that is in an environment proximate the user; and one or more processors configured to: determine that a user has entered a state of inwardly focused attention based on first physiological information collected from the user; and in response, record the auditory content captured by the audio input device.

The present disclosure pertains to enhancement of slow wave activity and personalized measurement thereof. Sensory stimulation may be delivered to a subject upon detection of slow wave activity of the subject. The system may obtain a baseline model, which includes baseline information describing slow wave activity increases due to sensory stimulation delivered to an age matched population. The system may generate a personalized model based on the baseline information, the sensory stimulation delivered to the subject, and slow wave activity increases due to sensory stimulation delivered to the subject during prior sleep sessions. The system may then provide the subject with personalized measurements relating to the slow wave activity enhancement.