Methods and systems are presented for determining physiological information in a physiological monitor. A physiological signal (e.g., an EEG signal) received from a subject is wavelet transformed and first and second related features that vary in scale over time are identified in the transformed signal. First and second coupled ridges of the respective first and second related features may also be identified in the transformed signal. A non-stationary relationship parameter is determined and is indicative of the relationship between the first and second features and/or between the first and second ridges. Physiological information, which may be indicative of a level of awareness of a subject, is determined based on the non-stationary relationship parameter. This physiological information may be used, for example, in an operating room to monitor/regulate the subject's anesthetic state while under general anesthesia or in an intensive care unit to monitor the subject's sedateness and administer medication accordingly.

The present disclosure pertains to a system configured to adjust an intensity of sensory stimulation delivered to a subject during a sleep session based on sleep spindles in the subject during the sleep session. The system is configured to adjust the intensity of the stimulation based on a sleep spindle frequency and/or a sleep spindle density. The system is configured to determine a recent spindle density and/or a recent spindle frequency for a recent period of time during the sleep session based on detected sleep spindles, and to determine a previous spindle density and/or a previous spindle frequency for a previous period of time during the sleep session based on the detected sleep spindles. The system controls the intensity of sensory stimulation provided to the subject based on a comparison of the previous spindle density to the recent spindle density and/or the previous spindle frequency to the recent spindle frequency.

A biological information measuring apparatus includes a distortion calculating unit that calculates, based on video pulse wave information representing a video pulse wave expressing a temporal change in a brightness value included in a video signal of a predetermined part of a subject, a waveform distortion obtained from a heartbeat basic component containing a frequency component of a heartbeat frequency band corresponding to a heart rate of the subject and a heartbeat high-frequency component related to a waveform of a pulse wave and containing a frequency component of a frequency band higher than the heartbeat frequency band, the heartbeat basic component and the heartbeat high-frequency component being included in the video pulse wave; and a measuring unit that measures a fluctuation in a blood pressure of the subject based on the waveform distortion calculated by the distortion calculating unit.

An information processing device, an information processing method, a recording medium storing a program, and a biomedical-signal measuring system. The information processing device includes circuitry to obtain specific information of a first intensity distribution of a biomedical signal from a source, the specific information being displayed on a display, and extract, based on the specific information, a specified area of the first intensity distribution to obtain second intensity distribution of the biomedical signal to be superimposed on an image indicative of the source. The information processing method includes obtaining specific information of a first intensity distribution of a biomedical signal from a prescribed source, the specific information being displayed on a display, and extracting, based on the specific information, a specified area of the first intensity distribution to obtain second intensity distribution of the biomedical signal to be superimposed on an image indicative of the source.

A biometric information measurement system includes a first measurement apparatus, a second measurement apparatus, and a control apparatus. The first measurement apparatus measures first biometric information of a subject. The second measurement apparatus measures second biometric information which is biometric information of the subject and which is different from the first biometric information. The control apparatus changes a condition of measurement performed by the second measurement apparatus on the basis of the first biometric information.

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.

Representative embodiments are directed to detecting neurological activity in a patient. The detection of neurological activity includes identifying cross-frequency coupling and determining whether the cross-frequency coupling is physiological or pathological. When pathological cross-frequency coupling is detected, neurostimulation of one or more sites is applied. In some embodiments, an implantable pulse generator is adapted to analyze neural activity for pathological cross-frequency coupling and to provide electrical stimulation in response to the detected pathological cross-frequency coupling.

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.

Media content recommendation systems and methods are operable to recommend one or more media content events to a user based on identified changes in the user's emotional state during a life event that is experienced by the user.

An electrode includes a core of beryllium copper alloy and a safe metal coating. In some embodiments, the beryllium copper alloy comprises more than three percent beryllium, less than three percent other metals and a remaining percent copper. In some embodiments, an apparatus includes a headband, and a first and second safe metal coated copper-beryllium alloy electrode. The headband is configured to fit snugly to a head of a subject in an orientation from behind a first ear, across a crown of the subject, to a position behind a second ear. The first electrode and second electrode are disposed in the headband to contact a head of the subject at a first position and a different second position, respectively, without gels. In various embodiments, the headband includes a chip to determine an analog signal and transmit data; and, a system includes the headband and a signal analyzing unit.