A transcranial magnetic stimulation (TMS) treatment system is provided. The system includes a sensor device that senses EEG signals from a subject through one or more leads and a server device configured to receive EEG data corresponding to the subject. The server includes an analysis module configured to process the EEG data and determine a personalized resonant brain frequency and a minimum neuronal activation threshold of the subject based at least in part on EEG data corresponding to one or more leads of the sensor device. The analysis module is also configured to determine a TMS treatment protocol where the treatment protocol includes at least a frequency based on the personalized resonant brain frequency and an amplitude based on the minimum neuronal activation threshold. The system also includes a treatment device configured to deliver a TMS treatment to the subject based on the TMS treatment protocol received from the server.

A transcranial magnetic stimulation (TMS) treatment system is provided. The system includes a sensor device that senses EEG signals from a subject through one or more leads and a server device configured to receive EEG data corresponding to the subject. The server includes an analysis module configured to process the EEG data and determine a personalized resonant brain frequency and a minimum neuronal activation threshold of the subject based at least in part on EEG data corresponding to one or more leads of the sensor device. The analysis module is also configured to determine a TMS treatment protocol where the treatment protocol includes at least a frequency based on the personalized resonant brain frequency and an amplitude based on the minimum neuronal activation threshold. The system also includes a treatment device configured to deliver a TMS treatment to the subject based on the TMS treatment protocol received from the server.

A system and method for promoting, tracking, and assessing mental wellness. The method includes receiving an entry from a subject user, the entry including an input and a mood indicator, storing the entry in within a set of entries, the set including at least two entries received over a period of time, and determining a presence of at least one marker in the input of each entry within the set. The method further includes analyzing the set of entries for occurrences of markers or sequences of markers and alerting a supervisory user if the occurrences of markers or sequences of markers exceed a predetermined threshold. The method further includes associating contextual content from a supervisory user to an entry, the contextual content including a note, an attachment, a form, and/or a flag. The system includes a platform for accessing, managing, and storing data and analytics for implementing the method.

A system includes a memory storing a user profile for a user of the system and machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive physiological data associated with the user during a sleep session, determine, based at least in part on the received physiological data, a set of sleep-related parameters for the sleep session, subsequent to the sleep session, select one of the set of sleep-related parameters as a targeted parameter, the selection of the targeted parameter being based at least in part on the stored user profile, the set of sleep-related parameters, or both, and cause information to be communicated to the user via a user device, the information being indicative of the targeted parameter, a recommendation associated with improving the targeted parameter for the user in one or more subsequent sleep sessions, or both.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

The present invention provides for a data acquisition system for EEG and other physiological conditions, preferably wireless, and method of using such system. The wireless EEG system can be used in a number of applications including both studies and clinical work. These include both clinical and research sleep studies, alertness studies, emergency brain monitoring, and any other tests or studies where a subject's or patient's EEG reading is required or helpful. This system includes a number of features, which enhance this system over other systems presently in the marketplace. These features include but are not limited to the having multiple channels for looking at a number of physiological features of the subject or patient, a built in accelerometer for looking at a subject's or patient's body motion, a removable memory for data buffering and storage, capability of operating below 2.0 GHz, which among other things allows for more channels, movement artifact correction including video, pressure sensors capable of measuring or determining airflow, tidal volume and ventilation rate, and capability of manual and automatic RF sweep.

The present invention provides for a data acquisition system for EEG and other physiological conditions, preferably wireless, and method of using such system. The wireless EEG system can be used in a number of applications including both studies and clinical work. These include both clinical and research sleep studies, alertness studies, emergency brain monitoring, and any other tests or studies where a subject's or patient's EEG reading is required or helpful. This system includes a number of features, which enhance this system over other systems presently in the marketplace. These features include but are not limited to the having multiple channels for looking at a number of physiological features of the subject or patient, a built in accelerometer for looking at a subject's or patient's body motion, a removable memory for data buffering and storage, capability of operating below 2.0 GHz, which among other things allows for more channels, movement artifact correction including video, pressure sensors capable of measuring or determining airflow, tidal volume and ventilation rate, and capability of manual and automatic RF sweep.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.

Provided are a brain stimulation system, method, apparatus and storage medium based on artificial intelligence. The system includes: a plurality of brain stimulation terminals and a cloud platform. The cloud platform is configured to, with artificial intelligence algorithm especially machine learning and deep learning, generate multi-dimensional psychological big data using physiological data and psychological state evaluation parameters gotten from the plurality of brain stimulation terminals and established models of algorithm for disease diagnosis. The brain stimulation terminal is configured to analyze the physiological data and psychological state evaluation parameters of a target subject, measure a mental state of the target subject, obtain brain stimulation parameters required for the target subject according to the mental state, and generate corresponding non-invasive brain stimulation for the target subject according to the brain stimulation parameters based on the multi-dimensional big data through the artificial intelligence algorithm.