An information processing apparatus includes a processor configured to associate information indicating a recognition result of a voice of a user uttered at a time at which the user manually operates a device, biological information other than the voice of the user, and manual operation information indicating a manual operation for the device with each other, and operate the device based on the biological information in a subsequent operation.

The present disclosure relates to technology that controls a remote moving body based on collaboration between the moving body and human, and a method for controlling a moving body includes acquiring a first biosignal indicating an intention to start operation of the moving body from a user, operating the moving body, determining a surrounding situation of the moving body that autonomously controls the driving, providing the user with surrounding information of the moving body for inducing path setting, acquiring a second biosignal evoked by recognition of the surrounding information from the user, setting a driving direction of the moving body, commanding the moving body to automatically perform a driving operation to be carried out in the set driving direction, and acquiring a third biosignal responsive to recognition of a driving error from the user and correcting the driving direction of the moving body to induce driving path resetting.

Hearing assistance systems, devices and methods including obtaining, by the device, multiple brain and bio-signals indicative of the auditory and visual attentional focus of the user, obtaining a mixed sound signal from multiple sound sources and applying, by the device, speech-separation and enhancement processing to the mixed sound signal to derive a plurality of separated signals that each contains signals corresponding to different groups of the multiple sound sources, and selecting one of the pluralities of separated signals either solely based on the obtained brain signals, or on a combination of bio-signals, including but not limited to eye gaze direction, head, neck and trunk orientation, etc. The separated signals may then be processed (i.e., amplified, attenuated) based on the needs of the user.

A computer implemented method includes accessing a multivariate time series set of samples collected by multiple biological sensors sensing a first biological function over a first period of time, dividing the data set into windows, calculating statistical dependencies between the samples of the timeseries data collected by each sensor, generating a relationship matrix as a function of the statistical dependencies, and transforming the relationship matrix to generate a first feature vector for each window of time that captures the statistical dependencies amongst the sensors.

A computer implemented method includes accessing a multivariate time series set of samples collected by multiple biological sensors sensing a first biological function over a first period of time, dividing the data set into windows, calculating statistical dependencies between the samples of the timeseries data collected by each sensor, generating a relationship matrix as a function of the statistical dependencies, and transforming the relationship matrix to generate a first feature vector for each window of time that captures the statistical dependencies amongst the sensors.

A method and apparatus of processing a signal, where the method may include receiving spike signals of neurons detected by each of a plurality of electrodes, grouping electrodes, from among the plurality of electrodes, corresponding to spike signals generated from a neuron of the neurons into a group, calculating weights corresponding to the grouped electrodes, and processing signals for each of the neurons based on the weights.

A method and apparatus of processing a signal, where the method may include receiving spike signals of neurons detected by each of a plurality of electrodes, grouping electrodes, from among the plurality of electrodes, corresponding to spike signals generated from a neuron of the neurons into a group, calculating weights corresponding to the grouped electrodes, and processing signals for each of the neurons based on the weights.

According to various embodiments, a display device may be provided. The display device may include: a receiver configured to receive user data based on an electroencephalography measurement; at least one light source; and a controller configured to control the at least one light source based on the user data.

A method and an apparatus for generating a brain break alert is provided. The method includes receiving electroencephalographic (EEG) data of a patient engaged in a cognitive activity at a system server from a user device. The EEG data is captured by electrode of an EEG headset, where the electrode is in physical contact with the patient, and the EEG headset is communicably coupled to the user device. Brain energy used (BEU) by the patient is determined based on the EEG data, brain energy available (BEA) to the patient is determined as a function of the BEU and a predefined initial brain energy (BEI) of the patient, where the BEA is proportional to a difference between the BEI and the BEU, and the BEA satisfying a brain break alert threshold is determined, upon which an instruction to generate a brain break alert (BBA) is sent to the user device.

Systems and methods of the present disclosure are directed to neural stimulation via audio and visual stimulations. The combination and/or sequence of audio and visual brain stimulations can adjust, control or otherwise manage the frequency of the neural oscillations to provide beneficial effects to one or more cognitive states or cognitive functions of the brain, while mitigating or preventing adverse consequences on a cognitive state or cognitive function that stems from sleep deprivation. In doing so, the present systems and methods can reduce sleep fragmentation, improve sleep quality, and slow the progression of cognitive decline in a subject with Alzheimer's disease and MCI.