Apparatus and methods are provided for use with a subject who is undergoing respiration. A motion sensor senses motion of a subject. A breathing pattern analysis unit analyzes components of the sensed motion that result from the subject's respiration. The breathing pattern analysis unit includes double-movement-respiration-cycle-pattern-identification functionality that designates respiration cycles as being double-movement-respiration-cycles (DMRC's) by determining that the cycles define two subcycles. Double-movement-respiration-cycle-event-identification functionality of the breathing pattern analysis unit identifies a DMRC event by detecting that the subject has undergone a plurality of DMRC's. An output is generated that is indicative of the subject having used accessory muscles in breathing, in response to identification of the double-movement-respiration-cycle event. Other embodiments are also described.

Monitoring, predicting and treating clinical episodes

The invention provides a body-worn vital sign monitor that measures a patient's vital signs (e.g. blood pressure, SpO2, heart rate, respiratory rate, and temperature) while simultaneously characterizing their activity state (e.g. resting, walking, convulsing, falling) and posture (upright, supine). The monitor processes this information to minimize corruption of the vital signs and associated alarms/alerts by motion-related artifacts. It also features a graphical user interface (GUI) rendered on a touchpanel display that facilitates a number of features to simplify and improve patient monitoring and safety in both the hospital and home.

Body-worn vital sign monitor

An apparatus, system, and method monitors the motion, breathing, heart rate and sleep state of subjects, e.g., humans, in a convenient, non-invasive/non-contact, and low-cost fashion. More particularly, the motion, breathing, and heart rate signals are obtained through processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Periods of sleep disturbed respiration, or central apnea can be detected through analysis of the respiratory signal. The mean heart rate, and derived information, such as the presence of cardiac arrhythmias can be determined from the cardiac signal. Motion estimates can be used to recognize disturbed sleep and periodic limb movements. The sleep state may be determined by applying a classifier model to the resulting streams of respiratory, cardiac and motion data. A means for display of the sleep state, respiratory, cardiac, and movement status may also be provided.

Apparatus, system, and method for monitoring physiological signs

A method is provided for predicting an onset of an asthma attack. The method includes sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the asthma attack at least in part responsively to the sensed parameter. Also provided is a method for predicting an onset of an episode associated with congestive heart failure (CHF), including sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the episode at least in part responsively to the sensed parameter. Other embodiments are also described.

Techniques for prediction and monitoring of clinical episodes

The invention provides a system for measuring respiratory rate (RR) from a patient. The system includes an impedance pneumography (IP) sensor, connected to at least two electrodes, and a processing system that receives and processes signals from the electrodes to measure an IP signal. A motion sensor (e.g. an accelerometer) measures at least one motion signal (e.g. an ACC waveform) describing movement of a portion of the patient's body to which it is attached. The processing system receives the IP and motion signals, and processes them to determine, respectfully, frequency-domain IP and motion spectra. Both spectra are then collectively processed to remove motion components from the IP spectrum and determine RR. For example, during the processing, an algorithm determines motion frequency components from the frequency-domain motion spectrum, and then using a digital filter removes these, or parameters calculated therefrom, from the IP spectrum.

Body-worn monitor for measuring respiration rate

Methods and systems (10) for monitoring vital signs for the prediction and treatment of physiological ailments are provided. The methods and systems (10) 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 and systems (10) employ sensors (30, 110, 380), for example, non-contact sensors, adapted to detect vital signs, such as heart rate or respiration rate, to produce signals (50) that can be analyzed for trends, for deviations, or for comparison to prior conditions or criteria. The sensors (30, 110, 380) may be positioned whereby the subject (12) 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.

Methods and systems for monitoring patients for clinical episodes

Apparatus and methods are described, including a method for treating a clinical episode. The method comprises sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, analyzing the parameter, detecting the clinical episode at least in part responsively to the analysis, and responsively to detecting the clinical episode, treating the clinical episode using a device implanted in the subject. Other applications are also described.

Prediction and monitoring of clinical episodes

PROBLEM TO BE SOLVED: To provide a system for monitoring vital signs for the prediction and treatment of physiological ailments.SOLUTION: A system for monitoring a subject in which a bed for the subject to lie down and a second object for the subject to have a rest includes: a first motion sensor arranged in a bed for detecting motions of the subject lied down on the bed; a second motion sensor arranged in the second object for detecting motions of the subject when the subject is positioned on the second object; and a simple pattern analysis module for receiving data from the first motion sensor and the second motion sensor and responding the data to monitor clinical symptoms.

Method and system for monitoring patient for clinical episode

Verfahren und systeme zur überwachung von patienten für klinische episoden

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