Disclosed herein are methods, systems, and apparatus for treating a medical condition of a patient, involving detecting a physiological cycle or cycles of the patient and applying an electrical signal to a portion of the patient's vagus nerve through an electrode at a selected point in the physiological cycle(s). The physiological cycle can be the cardiac and/or respiratory cycle. The selected point can be a point in the cardiac cycle correlated with increased afferent conduction on the vagus nerve, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during inspiration by the patient. The selected point can be a point in the cardiac cycle when said applying increases heart rate variability, such as a point from about 10 msec to about 800 msec after an R-wave of the patient's ECG, optionally during expiration by the patient.

A body monitoring system is designed for patients of varying needs with patients at risk for seizures, epilepsy, stroke, heart attack, bedsores, dementia, mental disorders, Old aged people on elderly, children specifically hyperactive ones. This system provides the user the control by online observation and activities algebra sum table sand database. The system has two warning systems: in APP and cell phone in the emergency. A plurality of sensors measuring angle and movement and acceleration in the XYZ axes in combination with a plurality of GPS sensors and GPS boundary makers and a heart rate sensor is used. Show and control and monitoring positions of the body during resting and the time and place activities and body movement of patients the states and tensions have problems psychological. Online display current status of patient and saving the states and conditions of the patient.

Systems, methods, and devices for automatic generation of a stimulation therapy that mimics electrographic activity in the brain at natural seizure termination define a stimulation therapy to be generated by an implanted component of a medical device system and delivered to a subject through identifying data characterizing a patient's seizures, especially at termination. A machine learning model identifies the seizures or seizure types from which to establish a canonical seizure or seizure type, and an algorithm translates the canonical seizure or seizure type into data that can be used to characterize a stimulation therapy. The systems, methods, and devices, include those configured to deliver the stimulation therapy that emulates the canonical seizure or seizure type when the seizure is detected, with the aim of terminating the seizure sooner than it would terminate without intervention.

An information processing device, an information processing method, a recording medium storing a program for causing a computer to execute the information processing method, and a biomedical-signal measuring system. The information processing device includes circuitry to control a display to superimpose a first image indicative of an estimated site or portion of a live subject on a biological image of the live subject, and control the display to superimpose a second image indicative of a result of analysis on the biological image. The result of the analysis indicates activity of the live subject. The information processing method includes controlling a display to superimpose a first image indicative of an estimated site or portion of a live subject on a biological image of the live subject, and controlling the display to superimpose a second image indicative of a result of analysis on the biological image.

A head mounted display includes a display unit capable of transparently displaying an outside world. The head mounted display includes a processing unit that displays a moving image on the display unit; and an external sensor that detects movement in the outside world which can be transparently displayed by the display unit. The processing unit acquires the movement in the outside world obtained by the external sensor, synthesizes the acquired movement in the outside world and the moving image to be displayed, and evaluates a biological effect based on the synthesized moving image obtained by the synthesis.

A method is provided for detecting an undesirable event or condition in a patient. The method may comprise receiving a first input signal from an UWB radar configured to monitor an environment occupied by the patient and including information representative of the patient's motion. Data derived from the first input signal is processed using a pattern recognition model to detect and classify patterns in the data derived from the first input signal as indicative or predictive of an undesirable event or condition involving the patient. When a pattern is classified as indicative or predictive of an undesirable event or condition in the patient an alarm is issued. A log of data derived from the first input signal and associated with a detection of a pattern classified as indicative or predictive of an undesirable event enables further machine learning in order to create an updated pattern recognition model based on individual patient behavior.

ElectroCorticoGraphy (ECoG) sensors and uses are disclosed. These ECoG arrays, systems, and processes may be operable or configured to: i) simultaneously record neural signals while providing stimulation on specific portions of the cortex using a user-guided stimulator; ii) acquire neural signals over a large cortex area; iii) provide individual or group stimulation while concurrently receiving neural feedback; and/or iv) acquire neural signals at a setting remote from the neural source using wireless or other communication techniques.

The present invention discloses a brain activity analysis method and apparatus, which is based on a nonlinear waveform decomposition technology, wherein the changes of the intrinsic features in brain waves are decomposed and demodulated to extract the modulation signals of the components, including the frequency-modulation signals and the amplitude-modulation signals. The present invention further uses a feature mask to determine whether to proceed further decomposition and demodulation of the extracted modulation signals. If not, the multidimensional changes of the intrinsic features are obtained according to the feature mask. Then, quantitation and identification is performed to obtain the status of brain function. The present invention not only effectively increases the accuracy of the identification but also uses the feature mask to obviously reduce the complexity and the load of computation.

A method of determining a length of an object by using an electronic device includes obtaining, by the electronic device, a length, of the electronic device, between a first point and a second point on the electronic device; obtaining, by the electronic device, a tension applied to a third point on the electronic device, the third point being located between the first point and the second point; and correcting the obtained length by using the obtained tension and prestored reference tension information, the prestored reference tension information indicating a relationship of the tension applied to the third point with respect to the length of the object, and determining the corrected length as a final length of the object.

A computer enabled method for analysing an electroencephalographic (EEG) waveform to detect the presence of a waveform indicative of an epileptic seizure. The method comprises the steps of, performing a time frequency analysis of the EEG waveform utilising a moving window to perform the analysis on a segment and calculating a power spectrum value of the analysed segment of the waveform to derive an index value. The calculated index value is utilised to determine the presence of a seizure. In a specific embodiment, the invention is directed to the detection of epileptic seizures in rats, mice and other rodents.