A medical device is configured to detect an atrial tachyarrhythmia episode. The device senses a cardiac signal, identifies R-waves in the cardiac signal attendant ventricular depolarizations and determines classification factors from the R-waves identified over a predetermined time period. The device classifies the predetermined time period as one of unclassified, atrial tachyarrhythmia and non-atrial tachyarrhythmia by comparing the determined classification factors to classification criteria. A classification criterion is adjusted from a first classification criterion to a second classification criterion after at least one time period being classified as atrial tachyarrhythmia. An atrial tachyarrhythmia episode is detected by the device in response to at least one subsequent time period being classified as atrial tachyarrhythmia based on the adjusted classification criterion.

The present disclosure provides a system and method of determining a risk score for triage. In particular, a system is provided for providing an assessment of risk of a cardiac event for a patient, for example an incoming patient to a hospital emergency department complaining of chest pain. In the disclosure, the system includes an input device for measuring physiological data based vital signs parameter of the patient, a twelve-lead electrocardiogram (ECG) device for establishing an ECG obtained from results of the electrocardiography procedure, and determining an ECG parameter and a heart rate variability (HRV) parameter therefrom. An ensemble-based scoring system is further provided, establishing weighted classifier based on past patient data and where the vital signs parameter, the ECG parameter and the HRV parameter are compared to corresponding weighted classifiers to determine a risk score. A corresponding method to determine a risk score for triage is also provided.

A blood pressure measurement device comprises a case, a first electrode and a stress sensor. The case includes a first surface and a second surface. The first electrode is disposed on the first surface, and the stress sensor is disposed on the second surface. The blood pressure measurement device is operated on a part of a body of a user. The part of the body has a blood vessel inside. Upon measurement of the blood pressure, the first electrode, the stress sensor and the blood vessel at least partially overlap in one projection orientation. Therefore, the stress sensor is able to be pressed on the part of the body when the user touches the first electrode. A method of blood pressure measurement is also disclosed.

A system and method for detecting and verifying bradycardia/asystole episodes includes sensing an electrogram (EGM) signal. The EGM signal is compared to a primary threshold to sense events in the EGM signal, and at least one of a bradycardia or an asystole is detected based on the comparison. In response to detecting at least one of a bradycardia or an asystole, the EGM signal is compared to a secondary threshold to sense events under-sensed by the primary threshold. The validity of the bradycardia or the asystole is determined based on the detected under-sensed events.

Methods and apparatus for monitoring fatigue and notifying an individual are described. The individual may be an operator of a vehicle, equipment, or machine, a student, or other person that may experience fatigue. Motion of the individual is monitored to detect a predescribed motion in response to a stimulus to first determine a base responsiveness profile. Afterwards, a current responsiveness profile is determined based on a prescribed motion in response to a stimulus, and if the current responsiveness profile exceeds a predetermined threshold of the base responsiveness profile, a notification is issued to the individual and, optionally, another person such as an employer, teacher, or parent.

A method of determining atrial fibrillation includes determining if a patient's pulse beats form an irregular pattern. If so, presence of an irregular pulse is indicated to a patient and, an electrocardiogram is obtained for determining atrial fibrillation. Initially, a pulse is detected at regular time intervals from a first appendage when motionless, using a pulse detector and pulse rhythms from a succession of time intervals, each corresponding to a respective interval of time between successive pulse beats of a sequence of the pulse beats. Then, a second appendage makes contact with an electrically conductive unit, and electrocardiogram signals are detected simultaneously with pulse rhythms while the first appendage is motionless and both appendages are relaxed. The signals are then analyzed to determine whether, in combination, they are indicative of atrial fibrillation. If atrial fibrillation is determined not to be present based on analysis of said ECG, then the pulse analyzer is adjusted to not detect that pulse pattern as irregular.

A method for determining the location of a medical device within a body is provided. The method includes transmitting from the medical device an acoustic signal; receiving with the medical device a reflected acoustic signal; advancing the medical device based on a first algorithm, the first algorithm including a first weighting factor and a first feature extracted from the reflected acoustic signal; determining a first location of the medical device based on the first algorithm; and moving the medical device to a second location based on a second algorithm, the second algorithm based on the determined first location and including at least one of a second weighting factor and a second feature extracted from the reflected acoustic signal. Also disclosed are systems and devices for performing the methods described herein.

The device for non-invasive monitoring of intracranial pressure (1) includes a measuring mat (2), processor unit (3), device for recording electrical activity of the heart (4), device for invasive measurement of arterial blood pressure (5), imaging device 6 and network connector (7). The measuring mat includes the processor unit (3) and sensors, at least one sensor (8) monitoring mechanical movement caused by the bloodstream dynamics. The ICP calculation methods use the Windkessel model and the relation between the start of the R-wave and the time delay of the mechanical movement of the head, which is related to the reflection of the pulse wave in the head.

The present invention discloses a depression assessment system based on physiological information, comprising an information acquisition module, a signal processing module, a parameters calculation module, a feature selection module, a machine learning module and an output result module. The present invention further discloses a depression assessment method based on various physiological information, comprising the following steps: 1, processing electrocardiogram (ECG) signal and one or more of photoplethysmography (PPG) signal, electroencephalogram (EEG) signal, galvanic skin response (GSR)signal, electrogastrography (EGG) signal, electromyogram (EMG) signal, electrooculogram (EOG) signal, polysomnogram (PSG) signal and temperature signal, and calculating signal parameters; 2, normalizing the obtained signal parameters, and performing the feature selection on parameters set formed by the normalized signal parameters to obtain feature parameters set; and 3, performing machine learning by utilizing the obtained feature parameters set, and establishing a depression assessment mathematic model to assess the depression level by utilizing a relationship between the feature parameters set and the depression level. The present invention has the advantage that the subjectivity of the assessment by utilizing the depression rating scale can be avoided.

A system comprising a remotely programmable micromonitor with a wireless sensing system-on-module (SOM), one or more sensors to detect one or more conditions in a subject by monitoring one or more parameters associated with the conditions by comparing any monitored parameter to a baseline measurement of the monitored parameter from the subject, a plurality of sensors corresponding to a monitored parameter and connected to the micromonitor to convey measurements of all monitored parameters, the sensors including at least one of a non-optical pulse wave sensor or an electrocardiogram (ECG) sensor, a communications module capable of communicating with a wireless technology, wherein the module can send an alert signal to the subject or an attending physician or a remote service center or any other subject, and one or more algorithms for monitoring conditions and/or for predicting conditions, including at least one of a fall detection or fall prediction algorithm.