Provided in the embodiments of the present disclosure are a control method and device based on brain signal, and a human-machine interaction device, which periodically acquire EEG signals and cerebral oxygen signals within a target period, generate an electroencephalogram (EEG) wave curve representing changes of the EEG signals and a cerebral oxygen wave curve representing changes of the cerebral oxygen signals respectively within the target period, determine whether the EEG wave curve and the cerebral oxygen wave curve satisfy a condition for controlling a controlled device to perform a target operation, and control the controlled device to perform the target operation when the EEG wave curve and the cerebral oxygen wave curve satisfy the condition.

In some variations provided herein, a system for deep brain stimulation includes an implantable device that acquire and store neural activity signal records and apply electrical stimulation. The system further includes a personal controller device that establishes a first wireless connection to the implantable device. The personal controller device transmits power to the implantable device, and the implantable device transmits neural activity signal records to the personal controller device over the first wireless connection. The system further includes a clinician programmer device that receive the neural activity signal records from the implantable device by establishing a second wireless connection based on activation of the first wireless connection. The clinician programmer device sets one or more stimulation parameters based on the neural activity signal records.

An apparatus for evaluating cognitive function of a patient. The apparatus has a physiological monitor adapted to output physiological measurements of a given bodily function of the patient, wherein the bodily function is regulated by the autonomic nervous system of the patient; a cognitive exercise evaluator adapted to obtain performance information of the patient when carrying out a cognitive exercise with a given difficulty; a general-purpose processor; and computer-readable memory adapted to store program code for evaluating the cognitive function of the patient, the program code comprising instructions to receive the physiological measurements and the performance information, and provide an evaluation of the cognitive function of the patient.

An interactive assessment system for measuring neurologic function and method of use are provided herein. The interactive assessment system includes an interactive assessment device comprising an interactive display defining longitudinal and lateral columns of interactive nodes, each interactive node is coupled to a sensor, and has an illumination mode and a delumination mode. The interactive assessment system also including a processing device in communication with the interactive assessment device and configured to perform logic functions based upon user inputs on the interactive assessment device. The processing device includes memory wherein previously input interactions with the interactive assessment device are stored and tagged as successes, failure, or interaction events. The processing device provides instruction to the interactive assessment device to assign nodes to the illumination mode and the delumination mode

A method of determining structured behavior from network adjacency matrices is described. A method of detecting physiological signals from a subject is described.

Devices and methods for monitoring, stimulating, and entraining electrical activity generated by the brain of a person are provided. Electroencephalography (EEG) and photobiomodulation (PBM) devices in the form of headphones for monitoring, stimulating, and entraining electrical activity generated by a person's brain are described, along with methods for monitoring and stimulating a person's cognitive and physiological state using the provided devices. PBM light is pulsed to stimulate an increase in targeted brainwave frequencies through entrainment and providing additional energy to mitochondria. PBM stimulation is combined with EEG sensors and neurofeedback. The neurofeedback may be used to assist users with stress, anxiety, fatigue, mood, creativity and mental focus and acuity.

A process for medical imaging, the process including: (i) receiving scattering data representing mono-static or multi-static measurements of scattering of electromagnetic signals from tissues of a body part of a subject at a plurality of different signal frequencies, wherein electromagnetic signals are emitted from one or more antennas and the corresponding scattered signals are measured by the one or more antennas; (ii) processing the scattering data to calculate electric field power values at each of a plurality of scattering locations of the subject's tissues within the body part and for each of the plurality of frequencies; (iii) for each of the scattering locations, summing the calculated electric field power values at the scattering location over the plurality of frequencies and the plurality of antennas to generate an image of the tissues within the body part; and (iv) iteratively updating a model of the tissues within the body part based on a comparison of the model with the generated image until a termination criterion is satisfied, wherein the updated model is output as an image of the subject's tissues within the body part.

Specific parameter sets are provided that makes the transcranial focused ultrasound to selectively activate a certain neuronal type at cortical brain and enables the transcranial focused ultrasound to non-invasively induce long-term effects at deep brain. A type of ultrasound collimator with incidence angle control is designed and validated through acoustic field pressure mapping in order to target brain areas at different depths. Multi-elements transducer arrays are also used to achieve transmission of focused ultrasound.

Methods, systems, and computer readable media to detect and model a brain tumor in an electronic image and to predict features of the brain tumor based on the model. The method can include classifying one or more magnetic resonance imaging (MRI) images of a brain into one or more of one or more tumorous images containing an image of a tumor or one or more non-tumorous images, wherein the classification is performed using a deep learning CNN system. The method can also include segmenting a tumor region from one of the one or more tumorous images. The segmenting can include a neighboring Fuzzy C-Means (FCM) process. The method can further include classifying the segmented tumor region into one of four classes of brain tumor types. The segmented tumor region is classified as a particular brain tumor type using the deep learning CNN system. The method can also include reconstructing a 3D model of the tumor region and measuring one or more of a location of the tumor, a shape of the tumor, or a volume of the tumor.

Methods, systems, and computer readable media to detect and model a brain tumor in an electronic image and to predict features of the brain tumor based on the model. The method can include classifying one or more magnetic resonance imaging (MRI) images of a brain into one or more of one or more tumorous images containing an image of a tumor or one or more non-tumorous images, wherein the classification is performed using a deep learning CNN system. The method can also include segmenting a tumor region from one of the one or more tumorous images. The segmenting can include a neighboring Fuzzy C-Means (FCM) process. The method can further include classifying the segmented tumor region into one of four classes of brain tumor types. The segmented tumor region is classified as a particular brain tumor type using the deep learning CNN system. The method can also include reconstructing a 3D model of the tumor region and measuring one or more of a location of the tumor, a shape of the tumor, or a volume of the tumor.