Provided are methods that include presenting to a subject an embodied cognitive task that includes a cognitive component and a physical component. The methods further include assessing the subject's performance on each of the cognitive component and the physical component, and adapting the difficulty level of the embodied cognitive task based on the subject's performance on each of the cognitive component and the physical component. In certain aspects, the methods find use in enhancing cognition, physical fitness, or both, in a subject. Also provided are methods of treating and diagnosing cognitive disorders. Systems and computer readable media for practicing the methods of the present disclosure are also provided.

A medical system including electrodes for acquiring electroencephalography (EEG) signals, amplifiers to amplify the EEG signals, an analog-to-digital converter to generate digitalized EEG data from the EEG signals, and a processor for processing the digitalized EEG data to generate a indication of neurological or psychological symptom based on a combination selected among spectral, temporal, and spatial features of the digitalized EEG data. The medical system further including a transcranial electrical stimulator that regulates stimulation frequency, intensity, or polarity according to the indication.

Information is communicated to an individual by directing an acoustic signal transcranially to a target region in the brain. The target region is stimulated to produce a cognitive effect, and the cognitive effect is modulated or encoded to carry the desired information.

A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units.

Equipment for applying active elements to a cranium of a patient comprises a support and a plurality of active elements, wherein the support comprises a means of connection with a patient and means for positioning the active elements in order to excite N+M zones of the cranium, the N+M zones comprising the zones VG.sub.19, VG.sub.20, VG.sub.21, C.sub.4, C.sub.5R, C.sub.5L, C.sub.6R and C.sub.6L, N and M being two integer numbers, N being a number between 2 and 8, M being less than N/2.

In one aspect, a sensory, motor and/or cognitive analysis device includes a casing unit structured to include a contact side conformable to a forehead region of a user; a data acquisition unit structured to include one or more sensors to detect electrophysiological signals of the user when the user makes contact with the device; a data processing unit encased within the casing unit and in communication with the data acquisition unit to amplify and digitize the detected electrophysiological signals as data, to process the data, to store the data, and to transmit the data to a remote computer system; and a power supply unit encased within the casing unit to provide electrical power, in which the device is operable to acquire physiological and/or behavioral signal data from the user used to determine a quantitative and/or qualitative information set associated with a cognitive or sensory assessment.

A method for identifying and treating a neural pathway associated with chronic pain via nerve stimulation and brain wave monitoring of a mammalian brain includes positioning a probe to stimulate a target nerve, wherein the target nerve is suspected of being a source of chronic pain; delivering a first nerve stimulation from the probe to the target nerve, wherein the first nerve stimulation is sufficient to elicit a chronic pain response in the brain; and monitoring for evoked potential activity in the brain as a result of the first nerve stimulation. The method can also include delivering second and third nerve stimulations to confirm the correct identification of the neural pathway and to treat the chronic pain, respectively. A system and apparatus for performing a procedure to identify and treat a nerve that is the source of chronic pain are also described.

A knee orthosis provides varying levels of support to a patient during a stance phase and a swing phase of a gait cycle. The orthosis comprises an upper auxiliary support, a lower auxiliary support, an actuator, a sensor configured to detect a plurality of leg movements during the gait cycle and to output a plurality of detection signals corresponding to the detected leg movements, and a processor configured to determine whether the knee is in the stance phase or the swing phase of the gait cycle, to control the actuator to apply pressure on the lower auxiliary support when the knee is in the stance phase, and to release pressure when the knee is in the swing phase.

The temporal correlation between a bioelectrical brain signal of a patient and patient motion data, such as a signal indicative of patient motion or a patient posture indicator, is displayed by a display device. In some examples, the patient posture indicator comprises a graphical representation of at least a portion of a body of the patient. In some examples, the temporal correlation between a bioelectrical brain signal, a signal indicative of patient motion, and a signal indicative of cardiac activity of the patient is displayed by the display device.

A method and system for extracting important signal information is disclosed. The method examines a group of signals obtained from testing of a patient's nervous system and finds a signal area of interest. Once a cluster of signals that all have the area of interest is found—the system concludes that the area of interest is located and validated. Signals that are not within the cluster are rejected and the signals within the cluster are signal-averaged to yield a signal-averaged waveform. The signal averaged waveform represents the results of the test.