Abstract: Some embodiments of the current disclosure are directed toward physiological monitoring of patients, and more particularly, systems, devices and methods for physiological monitoring of patients with a continuous or near-continuous transmission and analysis of monitored physiological data during the monitoring process. In some embodiments, a physiological patient monitoring system is provided which includes a physiological monitoring device which comprises a housing disposed on a patch, and the patch is configured for removable attachment to or proximate the skin of a patient, the housing including at least one memory. Antenna disposed on the housing transmit radio-frequency (RF) waves towards a targeted portion of an internal tissue of the patient and receive reflected RF waves from the internal tissue. RF circuitry in communication with the at least one memory perform an RF-based measurement of a lung fluid level of the patient during a predetermined time period.

Abstract: Some embodiments of the current disclosure are directed toward cardiac diagnosis and/or arrhythmia monitoring, and more particularly, systems, devices and methods for arrhythmia monitoring with a trained classifier including at least one neural network. In some embodiments, an external heart monitoring device may include a plurality ECG electrodes to sense surface ECG activity, ECG processing circuitry to process the surface ECG activity to provide at least one ECG signal, a non-transitory computer-readable medium comprising a rhythm change classifier comprising at least one neural network, and at least one processor to receive the ECG signal(s), detect with the rhythm change classifier time data corresponding to a predetermined rhythm change in the ECG signal(s), determine based on the detected time data at least one ECG signal portion corresponding to the predetermined rhythm change, and transmit the at least one determined ECG signal portion to a remote computer system.

Abstract: Some embodiments of the current disclosure are directed toward cardiac diagnosis and/or arrhythmia monitoring, and more particularly, systems, devices and methods for arrhythmia monitoring with a trained classifier including at least one neural network. In some embodiments, an external heart monitoring device may include a plurality ECG electrodes to sense surface ECG activity, ECG processing circuitry to process the surface ECG activity to provide at least one ECG signal, a non-transitory computer-readable medium comprising a rhythm change classifier comprising at least one neural network, and at least one processor to receive the ECG signal(s), detect with the rhythm change classifier time data corresponding to a predetermined rhythm change in the ECG signal(s), determine based on the detected time data at least one ECG signal portion corresponding to the predetermined rhythm change, and transmit the at least one determined ECG signal portion to a remote computer system.

Abstract: A patient monitoring system for use in either a patch mode or a holster mode for monitoring physiological data of a patient includes a multi-mode sensor configured to continuously and/or intermittently acquire the physiological data from the patient in the least two modes and to transmit the acquired physiological data to a remote location and/or record the acquired physiological data in an internal memory, the physiological data including one or more of patient electrocardiogram (ECG) data, patient posture, patient movement, radio-frequency (RF) based physiological data, body temperature, and/or patient respiration; an attachment mechanism disposed on the multi-mode sensor, the attachment mechanism configured to removably connect the multi-mode sensor to either a holster and associated monitoring cables worn by the patient or a patch worn by the patient; at least one electrical contact disposed on the multi-mode sensor, the at least one electrical contact configured to engage a counterpart electrical contact

Abstract: Some embodiments of the current disclosure are directed toward cardiac diagnosis and/or arrhythmia monitoring, and more particularly, systems, devices and methods for arrhythmia monitoring with a trained classifier including at least one neural network. In some embodiments, an external heart monitoring device may include a plurality ECG electrodes to sense surface ECG activity, ECG processing circuitry to process the surface ECG activity to provide at least one ECG signal, a non-transitory computer-readable medium comprising a rhythm change classifier comprising at least one neural network, and at least one processor to receive the ECG signal(s), detect with the rhythm change classifier time data corresponding to a predetermined rhythm change in the ECG signal(s), determine based on the detected time data at least one ECG signal portion corresponding to the predetermined rhythm change, and transmit the at least one determined ECG signal portion to a remote computer system.

Abstract: Apparatus for monitoring a clinical condition of a subject is described. A motion sensor monitors the subject, and generates a signal in response thereto. A control unit analyzes the signal, and, in response to the analyzing, (a) identifies a sleep stage of the subject, and (b) identifies a clinical parameter of the subject in the identified sleep stage. The control unit monitors the clinical condition, by comparing the clinical parameter to a baseline clinical parameter for the identified sleep stage, and generates an output in response thereto. Other applications are also described.

Abstract: Apparatus for monitoring a clinical condition of a subject is described. A motion sensor monitors the subject, and generates a signal in response thereto. A control unit analyzes the signal, and, in response to the analyzing, (a) identifies a sleep stage of the subject, and (b) identifies a clinical parameter of the subject in the identified sleep stage. The control unit monitors the clinical condition, by comparing the clinical parameter to a baseline clinical parameter for the identified sleep stage, and generates an output in response thereto. Other applications are also described.

Abstract: Apparatus and methods are described, included a method for detecting uterine contractions in a pregnant woman. The method includes sensing motion of the woman without contacting the woman, generating a signal corresponding to the sensed motion, and analyzing the signal to detect presence of labor contractions. Other applications are also described.

Abstract: Apparatus and methods are described, included a method for detecting uterine contractions in a pregnant woman. The method includes sensing motion of the woman without contacting the woman, generating a signal corresponding to the sensed motion, and analyzing the signal to detect presence of labor contractions. Other applications are also described.

Abstract: Apparatus and methods are described, including a method for detecting an onset of a hypoglycemia episode in a subject. One or more critical parameters for hypoglycemia are monitored without contacting the subject. A variation of at least one of the critical parameters is detected, and an alarm is activated when at least one of the critical parameters deviates from an accepted value. Other applications are also described.

Abstract: Apparatus and methods are described, including a method for detecting an onset of a hypoglycemia episode in a subject. One or more critical parameters for hypoglycemia are monitored without contacting the subject. A variation of at least one of the critical parameters is detected, and an alarm is activated when at least one of the critical parameters deviates from an accepted value. Other applications are also described.

Abstract: Apparatus and methods are described for monitoring a subject. A motion sensor senses motion of the subject and generates a sensor signal in response thereto. A control unit includes a filter configured to extract from the sensor signal at least one signal selected from the group consisting of: a breathing-related signal and a heartbeat-related signal. The control unit is configured to analyze the selected signal and to detect changes in body posture of the subject at least partially in response thereto. Other applications are also described.

Abstract: Apparatus (10) is provided that includes at least one sensor (30), configured to sense a physiological parameter of a subject (12) and to sense large body movement of the subject (12), an output unit (24), and a control unit (14). The control unit (14) is configured to monitor a condition of the subject (12) by analyzing 5 the physiological parameter and the sensed large body movement, and to drive the output unit (24) to generate an alert upon detecting a deterioration of the monitored condition. Other embodiments are also described.

Abstract: Apparatus (10) is provided that includes at least one sensor (30), configured to sense a physiological parameter of a subject (12) and to sense large body movement of the subject (12), an output unit (24), and a control unit (14). The control unit (14) is configured to monitor a condition of the subject (12) by analyzing the physiological parameter and the sensed large body movement, and to drive the output unit (24) to generate an alert upon detecting a deterioration of the monitored condition. Other embodiments are also described.

Abstract: Methods and systems for monitoring vital signs for the prediction and treatment of physiological ailments are provided. The methods and systems may be applied to the monitoring of a broad range of physiological ailments or “episodes,” including, but not limited to, asthma, hypoglycemia, coughing, edema, sleep apnea, labor, and REM sleep stages, among others. The methods employ sensors, for example, non-contact sensors, adapted to detect vital signs, such as heart rate or respiration rate, to produce signals that can be analyzed for trends, for deviations, or for comparison to prior conditions or criteria. The sensors may be positioned whereby the subject need not be viewed by the health care provider. Some methods and systems employ the use of “scores” based upon the combination of sensed vital signs or based upon a comparison of the vital signs to criteria.