In an aspect of the invention, a method of identifying sensory inputs affecting working memory load of an individual is provided. The method comprises monitoring (S101) working memory load of the individual using a sensor device, detecting (S102) an increase in the working memory load of the individual, and identifying (S103), in response to the detected increase, at least one sensory input affecting the working memory load of the individual.

In an aspect of the invention, a method of identifying sensory inputs affecting working memory load of an individual is provided. The method comprises monitoring (S101) working memory load of the individual using a sensor device, detecting (S102) an increase in the working memory load of the individual, and identifying (S103), in response to the detected increase, at least one sensory input affecting the working memory load of the individual.

A method of calibrating stimulation threshold levels of a cochlear implant, comprises sending a series of stimulation signals having a predetermined length in time to a selected subset of a plurality of stimulation electrodes of the cochlear implant of a user, wherein for each signal of the series of stimulation signals, the stimulation level is larger compared to the stimulation level of the previous stimulation signal; receiving an electrophysiological signal for each stimulation signal from a measurement electrode attached to the head of the user; calculating a cross-correlation signal for each of the received electrophysiological signals for each stimulation level following the first stimulation signal with respect to the first electrophysiological signal received for the first stimulation signal, determining, whether the respective cross-correlation signal exceeds a predetermined threshold level, wherein the sending of the series of stimulation signals is stopped and the stimulation level is set as the threshold stimulation level for the selected subset of stimulation electrodes, in case it is determined that the cross-correlation signal exceeds the predetermined threshold level for a first time, and outputting the level of stimulation at which the sending is stopped.

The object is to acquire electroencephalogram of high resolution with fewer number of electrodes than usual. An electroencephalogram measurement apparatus comprising: a plurality of electrodes 110 attached on the scalp of a subject for acquisition of electroencephalogram signals of the subject; and an electroencephalogram generation unit 150 for generating an electroencephalograms at locations of the scalp where the electrodes are attached and electroencephalograms at locations of the scalp where the electrodes are not attached.

An apparatus and method are provided to determine a parameter using an auditory model of a hearing loss patient. The parameter determination apparatus determines a similarity between a neurogram of a normal subject and a neurogram of a hearing loss patient, and determines an optimal frequency band for the hearing loss patient based on the similarity.

A method of analyzing performance of frequency lowering hearing aids. The method includes generating a sequentially of noise signals and transmitting acoustical sounds from a sound output device in response to the sequence of noise signals. A sound input device records the acoustical sounds and saves as a first device data. The sound input device with a frequency lowering hearing aid records the acoustical sounds and save as a second device data. The second device data is compared to the first device data and, in response to the comparison, at least one function of the frequency lowering hearing aid is optionally adjusted.

Certain examples provide systems and methods to enhance slow wave sleep. An example method includes identifying a sleep stage for slow wave sleep in a subject being monitored. The example method also includes generating, following identification of slow wave sleep and using a processor including a phase locked loop, an output signal based on a phase of a reference input signal, the output signal phase locked according to the reference input signal. The example method includes delivering, during slow wave sleep for the subject, a stimulus to the subject based on the phase locked output signal. The delivering includes providing the stimulus in a series of signal pulses for a first period of time; and providing a refractory period without pulses in a second period of time. The method further includes measuring feedback from the stimulus.

An evaluation apparatus comprises a brain wave acquiring unit that acquires a brain wave signal from each of a plurality of subjects; an intensity data generating unit that generates intensity data that represents an intensity of a signal component in a predetermined frequency band or a relation between intensities of signal components in a plurality of frequency bands; a correlation data generating unit that acquires pairs of two subjects for all combinations, calculates a cross-correlation coefficient for the intensity data at each point in time for the respective pairs, and generates, correlation data in the time-series form; and an output unit that generates evaluation data that numerically represents a degree of synchronization of brain wave fluctuation based on the correlation data.

Provided are systems, methods, and devices for biomarker shaping and sleep profile enhancement. Systems include a plurality of electrodes configured to be coupled to a brain of a user and configured to obtain a plurality of measurements from the brain of the user, and an interface configured to obtain the plurality of measurements from at least the plurality of electrodes. Systems also include a processing device comprising one or more processors configured to generate a first target sleep profile for the user based, at least in part, on the plurality of measurements and a plurality of biomarkers, the processing device being further configured to generate a plurality of stimulus parameters based, at least in part, on the target profile.

The present disclosure provides methods for identifying non-penetrating brain injury in a subject, as well as methods for classifying a subject that received a hit to the body that transmitted an impulsive force to the brain as either having a non-penetrating brain injury or not, by analyzing one or more components of frequency-following response (FFR) following administration of an acoustic stimulus to the subject. In addition, the present disclosure provides methods for assessing a subject's recovery from a non-penetrating brain injury. Also disclosed herein are processes and systems for automatically generating acoustic stimuli and processing brain response data to identify non-penetrating brain injuries in subjects.