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 apparatus for use with a plurality of clinicians. The apparatus includes a patient-monitoring system. A clinical sensor measures a clinical parameter of a patient, and generates a clinical-sensor signal in response thereto. In response to the clinical-sensor signal, a control unit determines that an alert event has occurred, and communicates an alert to a first subset of the plurality of clinicians before communicating the alert to any other clinician. The control unit designates the first subset of the plurality of clinicians in response to respective numbers of alerts that the plurality of clinicians have received within a previous given time period. Other applications are also described.

Abstract: 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.

Abstract: Apparatus and methods are described including a location sensing system that comprises a plurality of location sensors, and which is configured to identify respective locations of a plurality of clinicians, and to generate a location-sensing-system signal in response thereto. A patient-monitoring system includes a sensor, configured to measure a clinical parameter of a patient, and to generate a sensor signal in response thereto. A control unit of the patient-monitoring system includes signal analysis functionality that is configured to determine that an alert event has occurred, in response to the first sensor signal. In response to the location-sensing-system signal, the signal analysis functionality designates a first subset of the clinicians, and, in response to having determined that the alert event has occurred, the signal analysis functionality communicates the alert to the first subset of clinicians. Other applications are also described.

Abstract: Apparatus is provided, including a sensor configured to sense motion of a subject and generate a motion signal in response thereto. The apparatus includes an output unit and a control unit. The control unit is configured to: (a) analyze the motion signal, (b) at a first time, determine that the motion signal is indicative that the subject is likely sleeping, (c) at a second time following the first time, determine that the motion signal is indicative that the subject is likely no longer sleeping, and (d) in response thereto, drive the output unit to alert a clinician if the subject is at an increased risk for falling out of a bed. Other applications are also described.

Abstract: 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.

Abstract: Apparatus and methods are provided including sensing at least one parameter of a subject while the subject sleeps. The parameter is analyzed, and a condition of the subject is determined at least in part responsively to the analysis. The subject is alerted to the condition only after the subject awakes. Other applications are also described.

Abstract: A method of predicting an onset of apnea is described. Motion of a subject, including at least breathing-related motion, is sensed, and a signal corresponding to the sensed motion is generated. A breathing-related signal is extracted from the sensed motion signal, and the onset of apnea is predicted at least partially in response to analyzing the breathing-related signal. Other applications are also described.

Abstract: Apparatus and methods are provided for monitoring a subject, including setting respective first and second thresholds that are different from one another, sensing at least one parameter of the subject, and analyzing the parameter to generate a score. If the score is between the first and second thresholds, an alert that is indicative of a condition of the subject is generated only after the subject awakes. If the score passes the second threshold, an alert that is indicative of the subject's condition is generated immediately. Other applications are also described.

Abstract: 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.

Abstract: Apparatus and methods are provided including sensing at least one parameter of a subject while the subject sleeps. The parameter is analyzed, and a condition of the subject is determined at least in part responsively to the analysis. The subject is alerted to the condition only after the subject awakes. Other applications are also described.

Abstract: Apparatus is described, including a motion sensor configured to sense motion of a patient and to generate a motion signal in response thereto. The apparatus includes an output unit and a control unit. The control unit is configured to analyze the motion signal, to identify breathing of the patient as being shallow breathing in response to the analyzing, and to drive the output unit to generate an alert in response to identifying the breathing of the patient as being shallow breathing. Other applications are also described.

Abstract: Apparatus and methods are provided for measuring a heartbeat of a fetus in a pregnant subject. A motion-related parameter of the pregnant subject is sensed without contacting or viewing the subject or clothes the subject is wearing. The fetal heartbeat is derived from the motion-related parameter, and an output is generated in response thereto. Other applications are also described.

Abstract: 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.

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: A method is provided for predicting an onset of a clinical episode, the method including sensing breathing of a subject, determining at least one breathing pattern of the subject responsively to the sensed breathing, comparing the breathing pattern with a baseline breathing pattern, and predicting the onset of the episode at least in part responsively to the comparison. Other embodiments are also described.

Abstract: Apparatus and methods are described including a mechanical sensor configured to detect a physiological signal of a subject. A control unit receives the signal over a time duration of at least two hours at a given period of a first baseline day, and determines a baseline physiological parameter of the subject in response thereto. The control unit receives the signal over a time duration of at least two hours at a given period of a second day, the period on the second day overlapping with the period over which the signal is detected on the first baseline day. The control unit determines a physiological parameter of the subject based upon the detected signal on the second day, and compares the parameter to the subject's baseline physiological parameter. The control unit generates an alert in response to the comparison. Other applications are also described.

Abstract: 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.

Abstract: A method is provided for predicting an onset of a clinical episode, the method including sensing breathing of a subject, determining at least one breathing pattern of the subject responsively to the sensed breathing, comparing the breathing pattern with a baseline breathing pattern, and predicting the onset of the episode at least in part responsively to the comparison. Other embodiments are also described.

Abstract: 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.