The invention encompasses systems and methods that allow a clinician who is untrained in the art of electroencephalography to insert and functionalize unitized intracranial electrode arrays at the bedside that, by specific design, position ground and reference electrodes in electrically “quiet” locations to record durable, high-fidelity intracortical EEG.

The present invention relates to a sound source providing system for stabilizing anxiety symptoms, and more particularly, to a sound source providing system that provides a sound source having a mental and physical stability effect to a person with anxiety symptoms before an exam or anxiety symptoms caused by accidents or stress events.

A sound source providing system according to an embodiment of the present invention comprises: a sensor unit that is worn on a user's body to sense a GSR or HRV; a control unit that receives a GSR or HRV sense signal from the sensor unit and transmits a sound source playback signal; an operation unit for receiving the sound source playback signal from the control unit and playing a sound source such as a tapping sound or a heartbeat sound that is played periodically; and a storage unit that stores the sound source in which the tapping sound or heartbeat sound is recorded.

Neural activity in the brain arising from a stimulus is monitored. A stimulus is applied to a target structure of the brain and a neural measurement is obtained from at least one electrode implanted in contact with the target structure. The neural measurement is configured to capture a measure of any late response arising in the target structure, typically being a neural response arising after conclusion of an ECAP, such as in the period 1.5-10 ms after stimulus onset. The late response(s) can be a useful biomarker such as of therapeutic ranges of deep brain stimulation, disease progression, medication efficacy, and intra-operative changes.

A computer-implemented method for operating an autonomous or semi-autonomous vehicle may include identifying a vehicle operator and retrieving an associated vehicle operator profile. Operating data regarding operation of the autonomous or semi-autonomous vehicle may be received that includes data from sensors disposed within the vehicle. When a request to enable an autonomous operation feature is received, (i) autonomous operation risk levels associated with vehicle operation by the autonomous operation feature based upon the received operating data, and (ii) operator risk levels associated with vehicle operation by the vehicle operator based upon the vehicle operator profile are determined. Autonomous operation feature enablement may be allowed based upon a comparison of (i) autonomous operation risk levels with (ii) operator risk levels. As a result, only safe autonomous feature engagement may be facilitated, and risk averse vehicle owners may receive insurance discounts based upon this safe autonomous feature engagement functionality.

A system and method to screen for malignant gliomas, other brain tumors, and brain injuries use disturbance coefficient, differential impedances, and artificial neural networks. The system uses prescribed excitation signals with several system configurations to measure the differential impedances, calculate harmonic responses and nonlinearity of brain tissue, and estimate the disturbance coefficient that indicates the likelihood of malignant gliomas, other brain tumors, and brain injuries. The disturbance coefficient is a weighted sum of many parameters such as receiving differential impedances, transmission differential impedances, harmonic responses, frequency dispersion, and nonlinear responses using different system configurations and different excitation signals. The method includes arranging the transmitters, receivers, and transmission lines to maximize the sensitivity of detecting brain tissue condition. The artificial neural network is trained to estimate the disturbance coefficient using clinical data. The method provides a sensitive and cost effective approach for screening malignant gliomas, other brain tumors, and brain injuries.

There is provided a system, system architecture, and method for neural cross-frequency coupling analysis. In an embodiment, the method includes: receiving neural signals; extracting a phase frequency signal and an amplitude frequency envelope signal from each of the neural signals; determining a first measure of cross-frequency coupling comprising a mean vector length modulation index (MVL-MI), determining the MVL-MI comprises determining a magnitude of an averaged complex-valued time series from a plurality of samples of the neural signals to extract a phase-amplitude coupling measure, each sample associated with a respective one of the amplitude frequency envelope signals and the phase frequency signals; and outputting at least one measure of the cross-frequency coupling.

The present invention identifies biomarkers that are diagnostic of nerve cell injury and/or neuronal disorders. Detection of different biomarkers of the invention are also diagnostic of the degree of severity of nerve injury, the cell(s) involved in the injury, and the subcellular localization of the injury.

A system for analyzing brain tissue components based on magnetic resonance image. The system includes a memory and a processor. The memory stores instructions. The processor accesses and executes the instructions to perform the following: extracting maps of tissue from a brain magnetic resonance imaging (MRI) corresponding to normal subjects; averaging the maps of tissue according to a number of the normal subjects to generate reference maps that correspond to different tissues; receiving a brain MRI sample having a targeted region; and analyzing the brain MRI sample based on the reference maps and the targeted region to generate an analysis result, in which the analysis result indicates a ratio of tissues in the targeted region of the brain MRI sample.

The present invention relates to a system and a method for determining a stroke based on a voice analysis. According to the present invention, voice data of subjects are collected to extract and analyze voice onset times to determine stroke patients based on voices. The system for determining a stroke generates and collects voice data from test subjects reading a predetermined word that includes a plosive sound. The system for determining a stroke extracts and calculates voice onset times from the voice data to calculate probability parameters for the voice onset times of each of a normal group and a stroke patient group. The system for determining a stroke uses a set of probability parameters to determine an integration section, and calculates probabilities of being in the normal group and the stroke patient group. The system for determining a stroke applies the calculated probabilities to the Bayes theorem to determine whether the subjects are stroke patients.

A measuring apparatus (100) is provided for fitting to an animal body for measuring changes in concentration of a chromophore in the animal body. The measuring apparatus (100) has a plurality of devices (120). Each device (120) has a light source (122) for emitting light towards an animal body and a light detector (124) for detecting light returning from the said animal body. A device controller (126) receives signals from and sends signals to a main controller (160). The device controllers (126) of the plural devices (120) are respectively connected to a connection arrangement (150).