Certain aspects of the present disclosure provide methods and apparatus for determining a precise localization of an arrhythmia origin or exit site in a heart of a subject using internal electrocardiograph (ECG) signals sensed and stored by an implantable device implanted in the subject. One example method of analyzing an arrhythmia in a subject generally includes reading, from an implantable device implanted in the subject, a plurality of internal ECG signals sensed and stored by the implantable device while the subject was experiencing an arrhythmia event (e.g., at any time, including while the subject was ambulatory); performing an analysis of the read internal ECG signals; and determining a localization of the arrhythmia associated with the arrhythmia event, based on the analysis.

An input interface is configured to receive a signal corresponding to vital information that exhibits temporal variation. When at least one instruction stored in a memory is executed by a processor, waveform information (W) is generated based on the signal; a value of a profile factor of the waveform information (W) is obtained every time a predetermined time period is elapsed; and the value is displayed on the display section (15). The profile factor includes at least one of a rising angle, a top portion angle, a falling angle, a rising velocity, an absolute value of the rising velocity, a top portion velocity, an absolute value of the top portion velocity, a falling velocity, an absolute angle of the falling velocity, an under-waveform area, a rising-falling time interval, a falling-rising time interval, a rising-rising time interval and a falling-falling time interval.

Some embodiments of the present disclosure discuss an apparatus comprising a transceiver configured to generate and/or receive radio frequency (RF) electromagnetic signals, one or more antennae configured to radiate the generated RF electromagnetic signals toward a surface and to output signals corresponding to received reflections of the RF electromagnetic signals, and a processing circuitry configured to process the received reflections and/or the output signals so as to determine change in position of the apparatus with respect to the surface. The apparatus may be incorporated into a wearable garment and/or an adhesive patch, and it may be attached to an outer surface of a human or an animal body.

Disclosed is a method. The method may include receiving first data based on a stimulus defined according to a patient. The method may include receiving second data based on the stimulus. The method may include determining an indication of tinnitus. The indication of tinnitus may be based on a comparison between the first data and the second data. The method may include administering a tinnitus treatment on the patient. The treatment may be based on the indication. A tinnitus treatment may include one or more of an biological feedback with the patient, transcranial magnetic stimulation of the patient, surgical insertion of the cochlear implant, the cognitive behavioral therapy, the transcutaneous electrical stimulation, pharmacologic therapy on the patient, or applying a hearing aid to the patient.

Embodiments of the present technology may include a method for monitoring a health parameter of a person, the method including receiving data that corresponds to a digital pulse wave signal that is generated from radio frequency data that corresponds to radio waves that have reflected from below the skin surface of a person. In some embodiments, the radio frequency data is collected through a two-dimensional array of receive antennas. Embodiments may also include determining a value that corresponds to a blood glucose level in the person in response to the data that corresponds to the digital pulse wave signal.

The method and apparatus disclosed herein determine a user cadence from the output of an inertial sensor mounted to or proximate the user's body. In general, the disclosed cadence measurement system determines the user cadence based on frequency measurements acquired from an inertial signal output by the inertial sensor. More particularly, a cadence measurement system determines a user cadence from an inertial signal generated by an inertial sensor, where the inertial signal comprises one or more frequency components. The cadence measurement system determines a peak frequency of the inertial signal, where the peak frequency corresponds to the frequency component of the inertial signal having the largest amplitude. After applying the peak frequency to one or more frequency threshold comparisons, the cadence measurement system determines the user cadence based on the peak frequency and the frequency threshold comparison(s).

A wearable device utilizing flexible electronics is disclosed. The wearable device may comprise a flexible matrix material and may include sensors for measuring biometric measurements of an individual, an accelerometer for measuring an acceleration of a body part to which the wearable device is attached, a wireless transmitter, a flexible power source, and a microcontroller. During an activity, the microcontroller may receive signals from the sensors including the biometric measurements, and signals from the accelerometer including acceleration and force measurements associated with the individual. The microcontroller may convert the signals into digital signals and transmit the signals to a computing device for analysis. The computing device may analyze the digital signals to determine a performance metric for the individual. The performance metric may be compared to baseline data for the individual to determine a fatigue level, injury risk, or an adjustment to be made by the individual during the activity.

Apparatus for monitoring activation in a heart comprises a probe (100), a plurality of electrodes (102) supported at respective electrode positions on the probe and each arranged to contact a respective detection position on the heart. Each of the electrodes (102) is arranged to detect electrical potential at the respective detection position during movement of a series of activation wavefronts across the heart and to produce a respective electrode signal. Processing means is arranged to analyse the electrode signals to: identify pairs of the electrode signals between which there is a degree of Granger causality; define a causality vector between the electrode positions of each of the pairs of electrodes; identify a potential driver location; and analyse the direction of a plurality of the causality vectors around the potential driver position to generate an indicator of the presence of a driver at the potential driver location.

An automatic test device and method for auditory brainstem response (ABR) collects an ABR dataset at a plurality of sound loudness levels, increases the times of level averaging by iteration based on an adaptive average method, and improves a signal-to-noise ratio until ABR signal detection conditions are met. Signal detection includes determining that the time lag between average curves obtained from the ABR dataset is within a specified range. Iteration is terminated when the ABR signal is detected or a maximum number of iterations is reached. A minimum loudness level required to detect the ABR signal is used as a hearing threshold. An accurate loudness level corresponding to the hearing threshold is obtained by function fitting on the number of iterations used at each loudness level and interpolation. The threshold detection can effectively reduce the number of times that an ABR recording needs to be acquired.

A solution for estimating a cardiac pre-ejection period is disclosed. According to an aspect, a method includes: measuring, from a user by using a plurality of cardiac sensor devices, electrocardiogram measurement data, a first set of cardiac measurement data measured at a first location of the user's body a first distance from the user's heart, and a second set of cardiac measurement data measured at a second location of the user's body a second distance from the heart, the second distance different from the first distance, wherein the electrocardiogram measurement data is clock-synchronized with the first set of cardiac measurement data and second set of cardiac measurement data; determining, in the electrocardiogram measurement data, a first set of time instants associated with electric heart activations; determining, in the first set of cardiac measurement data, a second set of time instants associated with detections of blood pulses at the first location, the blood pulses resulting from the electric heart activations; determining, in the second set of cardiac measurement data, a third set of time instants associated with detections of the blood pulses at the second location; forming a set of scatter points on the basis of at least the second set of time instants and the third set of time instants and performing a fitting for the scatter points; and computing the cardiac pre-ejection period from at least one parameter describing the fitting.