33 results about "Brain surface" patented technology

The present invention provides systems and methods for detection and diagnosis of concussion and/or acute neurologic injury comprising a portable headwear-based electrode array and computerized control system to automatically and accurately detect cortical spreading depression and acute neurological injury-based peri-infarct depolarization (CSD/PID). The portable headwear-based electrode system is applied to a patient or athlete, and is capable of performing an assessment automatically and with minimal user input. The user display indicates the presence of CSD/PID, gauges its severity and location, and stores the information for future use by medical professionals. The systems and methods of the invention use an instrumented DC-coupled electrode/amplifier array which performs real-time data analysis using unique algorithms to produce a voltage intensity-map revealing the temporally propagating wave depressed voltage across the scalp that originates from a CSD/PID on the brain surface.

In a method and an apparatus for measuring degree of neuronal impairment in brain cortex, scalp potentials or magnetic fields of a subject are measured by mounting a plurality of sensors on a head of the subject, the measured scalp potentials or magnetic fields are converted into numerical data to obtain a dipolarity at each sampling, mean values of squared errors, within a fixed time interval, between a scalp potential or a magnetic field by an equivalent dipole at a dipolarity peak emergence time and the measured scalp potentials or magnetic fields, or variances of the squared errors from the mean values are obtained for the sensors, and a contour concerning a distribution of the mean values or the variances on a scalp or a brain surface corresponding thereto is mapped as an output. Alternatively, the squares of potentials sensed by the sensors are averaged for several seconds, and variances of these mean values are obtained for numerous reference persons. The mean value and the standard deviation of the variances for a group of the reference persons are obtained, so that the variance of an individual subject is ranked depending on which area of the standard deviation of the group of the reference persons the variance is located. By allocating the values to a brain surface corresponding to the sensors, maps are prepared. By these maps, a local impairment degree of a neuronal function is indicated.

The electroencephalogram electrode unit for small animals includes a base that covers the scalp or brain surface of a small animal and has a plurality of through holes and a plurality of electrodes. Each of the plurality of electrodes is inserted into each of the plurality of through holes, and each of the plurality of electrodes is equipped with an insulating tube, an electrode section disposed within the tube, an extraction conducting wire that is connected to the electrode section and extracts the EEG signal to outside, and a paste that is filled within the tube. The tube is installed in the through hole in a manner of standing upright from the scalp or brain surface, and the electrode section is formed in the form of a wire and is disposed, in a manner of standing upright from the scalp or brain surface, within the paste filled within the tube.

We have developed a novel method of brain surface dialysis that reduces intracranial pressure and modifies movement of extracellular fluid in a rat model of brain injury. A chamber with a semipermeable membrane at the site of brain contact is perfused with a hyperosmolar solution (e.g. 15% dextran, inulin, hydroxyethyl starch). It is also capable of providing local brain cooling. In principle, osmotic forces draw water and small molecules from the injured brain into the dialysis chamber thereby reducing brain swelling. The dialysate does not move into the brain.

Described here are systems and method for predicting clinically relevant brain features using geometric deep learning techniques, such as may be implemented with graph convolutional neural networks or autoencoder networks that are applied to graph representations of brain surface morphology derived from medical images. As an example, graph convolutional neural networks can be applied to brain surface morphology data derived from magnetic resonance images (e.g., T1-weighted) using surface extraction techniques in order to predict brain feature data.

A cortical sensing device for contact with the surface of the brain is provided that includes a support member, at least one macroelectrode sensing element secured with respect to the support member and at least one microelectrode sensing element secured with respect to the macroelectrode. The support member is substantially thin and made from flexibly-conformable material to accurately and safely place the sensing device upon the brain surface. The microelectrode sensing element is surrounded by the macroelectrode brain-contact surface of the macroelectrode sensing element. The first surface of the support member, the macroelectrode brain-contact surface and the microelectrode brain-contact surface are substantially co-planar to abut the surface of the brain for sensoring and monitoring.

For measuring a brain local activity, a predetermined frequency bandwidth wider than a frequency bandwidth of alpha waves of scalp potentials is divided into a predetermined number of frequency banks each having a fixed frequency width, data of each divided frequency bank is divided into segments of a predetermined duration on a time axis, a Z-score of the subject is determined from a first mean value of normalized power variances determined for the segments and a second mean value of normalized power variances predetermined in the same manner as the first mean value for a predetermined normal person group and a standard deviation of the normalized power variances in the group, and a mean value of the Z-scores determined over all of the frequency banks is mapped on a brain surface for each sensor, whereby a template of a specified brain disorder and likelihood of a subject to a specified brain disorder are calculated.

A cortical sensing device is provided that includes a sensing element and at least one pad attached adjacent to a support member. The pad is substantially thin and made from flexibly-conformable material to accurately and safely place the sensing device upon the brain surface. Contact between the lower surface of the pad and the brain surface anchors the sensing element at a desired position against unintentional movement. The sensing device preferably has three circular pads equidistant from one another. A method to position a cortical sensing device upon a brain surface is also disclosed comprising the steps of providing a cortical sensing device having a sensing element and three dielectric pads attached to a support dielectric member where the member and the pads are thin and flexibly-conformable, placing the sensing device upon the brain surface at a desired position for sensing brain activity, and allowing the pads to conform to the brain surface so that interaction therebetween prevents movement of the sensing element along the brain surface.

The invention provides a brainwave signal acquisition device and a preprocessing method thereof. The acquisition device comprises an elastic arc-shaped headband and a brainwave acquisition sensor arm connected to the elastic arc-shaped headband at both ends, wherein one end of the brainwave acquisition sensor arm is connected to a wireless transceiver module, and two ends of the elastic arc-shaped headband are connected to a jaw-fixing elastic soft belt used for making the elastic arc-shaped headband cling to the brain surface tightly; The brainwave acquisition sensor arm is electrically connected to at least three brainwave acquisition electrodes. The acquisition device has the advantages of simple structure, low cost and easy popularization. The brainwave signal preprocessing analysis uses analysis methods of intelligent blind source signal separation and intelligent learning algorithm to extract features, and solves the difficult problems that the signals collected by a simple brainwave signal acquisition device have too large noise interference and low precision to separate the real brainwave signals.

The invention relates to the field of medical instruments, in particular to an anti-damage directional guide subdural drainage tube kit. The anti-damage directional guide subdural drainage tube kit comprises a drainage tube implanting sleeve, a top opening is formed in the top of the drainage tube implanting sleeve; a positioning skirt edge is arranged on the outer edge of the top opening; a drainage tube leading-out hole is formed in the bottom of the drainage tube implanting sleeve; and an arc-shaped curvature guide platform is arranged on one side of the drainage tube guide-out hole. Blood vessels, blood supply arteries, drainage veins, bridge veins and arachnoid particles exist on the surface of the brain tissue cortex; the drainage tube is inserted into the drainage tube, so that bridge veins, drainage veins on the brain surface and the like can be effectively avoided, and damage to blood vessels is avoided. On the basis of the arc-shaped curvature guide platform, the drainage tube can smoothly turn into the subdural space and enter the encephalic in parallel; therefore, local brain injury caused by the fact that the drainage tube is difficult to turn into the subdural space is effectively avoided.

The invention discloses a functional near-infrared cerebral function imaging system using high-low dual density optrode configuration, and belongs to the crossed technical field of bioimaging and information processing. The system comprises at least an emitting electrode configured on the surface of a brain, a receiving electrode configured on a brain surface and forming a low-density fNIRS channel with the emitting electrode, a receiving electrode configured on the brain surface and forming a high-density fNIRS channel with the emitting electrode in the low-density fNIRS channel, and a signalprocessor. Through independent component analysis and correlation analysis on the acquired fNIRS signals, independent components representing superficial tissue fNIRS signals in the fNIRS signals areremoved, so that the superficial tissue fNIRS signals included in an existing fNIRS system are effectively separated and removed. The system can obtain fNIRS signals which actually reflect cerebral cortex neural activities, and improves signal quality of an fNIRS system.

The invention discloses a dura-puncturing trocar and a support handle thereof. The dura-puncturing trocar is composed of integration of a cylindrical portion at the lower end and a triangular blade-shaped conical head at the upper end. The cross section of the triangular blade-shaped conical head is of a triangular tip shape, and the triangular blade-shaped conical head is formed by connection oftails of three triangular small blades. A junction of the three triangular small blades constitutes a blunt-tip portion in 0.5mm diameter. According to the present invention, the dura-puncturing trocar cooperates with a traditional meninx-puncturing trocar to puncture dura, thereby avoiding damage of blood vessels on a brain surface, and a support limit handle of the dura-puncturing trocar can bequickly assembled and used to quickly adjust length of the conical head, so that the dura-puncturing trocar is simple, convenient, and easy to disinfect and store.