A method for monitoring physiological signals of a subject from sounds produced by the subject, including: receiving recorded sounds, including sounds from the subject's chest and being transmitted by the subject's biological tissues to the subject's ears, the recorded sounds being recorded by sound recording element(s) positioned inside earcup(s) of headphones worn by the subject; receiving signals from an accelerometer and a gyroscope being recorded simultaneously with the recorded sounds; detecting heart beats from the cardiac peaks sounds and calculating inter-beat intervals from the heart beats; extracting a first estimation of the breathing signal from the inter-beat intervals presenting respiratory sinus arrhythmia; extracting a second estimation of the breathing signal from residual sounds; extracting a third estimation of the breathing signal and motion artifacts from the signals of the accelerometer and the gyroscope; calculating the breathing signal by combining the first, second and third estimations of the breathing signal.

Systems and methods for dynamically and intelligently estimating analyte data from a continuous analyte sensor, including receiving a data stream, selecting one of a plurality of algorithms, and employing the selected algorithm to estimate analyte values. Additional data processing includes evaluating the selected estimative algorithms, analyzing a variation of the estimated analyte values based on statistical, clinical, or physiological parameters, comparing the estimated analyte values with corresponding measure analyte values, and providing output to a user. Estimation can be used to compensate for time lag, match sensor data with corresponding reference data, warn of upcoming clinical risk, replace erroneous sensor data signals, and provide more timely analyte information encourage proactive behavior and preempt clinical risk.

Methods and apparatus for utilizing multiple sources of physiologic data to enhance measurement robustness and accuracy. In one embodiment, phonocardiography or “heart sounds” data is used in combination with one or more other techniques (for example, impedance cardiography or ICG waveforms, and/or electrocardiography or ECG waveforms) to provide more accurate and robust physiological and/or hemodynamic assessment of living subjects. In one variant, the aforementioned methods and apparatus are used to improve ICG fiducial point (e.g., B, C and X point) detection and identification accuracy. Moreover, the new ICG fiducial points that may be clinically important may be identified using the disclosed methods and apparatus. In a further aspect, the invention discloses methods and apparatus for utilization of ICG and/or ECG waveform information to improve the identification and characterization of heart sounds (such as e.g., S1, S2, S3, or S4 heart 20 sounds), murmurs, and other such artifacts or phenomena.

A method for measuring sound from vortices in the carotid artery comprising: a first and second quality control provisions, wherein the quality control compares detected sounds to pre-determined sounds, and upon confirmation of the quality control procedures, detecting sounds generated by the heart and sounds from vortices in the carotid artery for at least 30 seconds. A method for determining stenosis of the carotid artery in a human patient consisting of a first step of placing a sensing device comprising an array and three sensing elements onto the patient, wherein a first sensing element is placed near the heart and the two remaining sensing elements are placed adjacent to the carotid arteries; the sensing elements then measure sounds from each of the three sensing elements, resulting in sound from three channels. The sound is measured in analog and modified to digital format and then each of the three channels are analyzed before a power spectral density analysis is performed. The power spectral density graph reveals peaks that are not due to noise, that are then analyzed to provide for a calculation of percent stenosis or complete occlusion of the carotid artery.

A defibrillator having a pair of electrodes for delivering an artifact-compensated defibrillation shock and a method thereof is provided. The defibrillator can be deployed rapidly while administering a cardio-pulmonary resuscitation (CPR) on the patient. Upon detection of an end of the CPR operation, a correlation signal indicative of signal corruption is detected and analyzed rapidly to determine an appropriate energy level discharged across the pair of electrodes. Thereafter, a notification signal is sent to the user of the defibrillator prior to delivering the defibrillation shock to the patient. The artifact-compensated defibrillation shock is delivered if for a predetermined period of time no movement is detected.

A monitoring system includes a wearable appliance; and a processor coupled to the wearable appliance to analyze vital data or wellness data.

A swallowing diagnosis apparatus includes a controller which enables a first swallowing determination process of determining whether or not there is an aspiration risk in the swallowing on the basis of respiratory phases before and after a period in which swallowing has been estimated as having occurred; and a second swallowing determination process of extracting reference information including at least one of the sound information and the respiration information in a predetermined period including the period in which swallowing has been estimated as having occurred, obtaining a feature quantity from the extracted reference information, and performing a machine learning process on the obtained feature quantity to determine whether or not there is a possibility of dysphagia in the swallowing; and a display control process of causing a determination result obtained by the first swallowing determination process and a determination result obtained by the second swallowing determination process to be displayed.

An example method includes performing amplitude-based detection to determine location of R-peaks for a plurality of electrograms. The method also includes performing wavelet-based detection to determine location of R-peaks for the plurality of electrograms. The method also includes adjusting the location of the R-peaks determined by the wavelet-based detection of R-peaks based on the location of R-peaks determined by the amplitude-based detection of R-peaks. The method also includes storing, in memory, R-peak location data to specify R-peak locations for the plurality of electrograms based on the adjusting.

Devices and methods are described that provide improved diagnosis from the processing of physiological data. The methods include use of transforms prior to submitting the data to a multiple level neural network. In one embodiment for ECG analysis, a template is used to subtract data that is not pertinent to the diagnosis and then a Fourier transform is applied to the time series data. Examples are shown with applications to electrocardiogram data, but the methods taught are applicable to many types of physiological data.

The invention relates to a system for electroencephalographic detection of an improper adjustment of a ventilator used on a mammal. The system includes an electroencephalograph, capable of measuring, as a function of time, an electroencephalographic signal representative of a breathing process; and an input for receiving a respiratory initiation signal, different from the electroencephalographic signal, capable of indicating a respiratory initiation time. The detection system further includes means for specifying a beta frequency band comprised between 15 and 30 Hz and with a width comprising between 5 and 10 Hz; means for processing the measured electroencephalographic signal, configured for processing the measured electroencephalographic signal as it is being acquired, in the sole specified beta frequency band; and means for identifying, for each breathing cycle, an improper adjustment of the ventilator from the electroencephalographic signals processed in the sole beta frequency band.