Systems, devices, and methods are described for monitoring uterine activity, the system comprising: a sensor module coupled to a belly region of a female, the sensor module including at least one inertial measurement unit; a processor communicatively coupled to the sensor module, the processor being configured to execute instructions comprising: acquiring inertial motion data from the sensor module; processing the inertial motion data to differentiate uterine motion data from other physiological motion data; generating, based on the uterine motion data, a uterine activity signal by transforming the uterine motion data from a first signal domain to a second signal domain; and generating, based on the generated uterine activity signal, an output representing at least one uterine contraction within the generated uterine activity signal or activity indicating a lack of uterine contraction.
A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/021 - Measuring pressure in heart or blood vessels
A system for monitoring fetal wellbeing over time during pregnancy includes a sensor coupled to a pregnant woman; a processor communicatively coupled to the sensor; and a computer-readable medium having non-transitory, processor-executable instructions stored thereon. Execution of the instructions causes the processor to perform a method including: acquiring a signal from a sensor; processing the signal to identify and extract a parameter of interest from the signal; and analyzing the parameter of interest to determine a degree of fetal wellbeing. The parameter of interest may include one or more of: an average fetal heart rate, an average fetal heart rate variability, a fetal kick or movement count, an average placental oxygenation level, an average placental temperature, an average placental pH, an average amount of amniotic fluid, a fetal heart rate profile, a fetal heart rate variability profile, and a fetal movement profile.
A61B 5/053 - Measuring electrical impedance or conductance of a portion of the body
A61B 5/08 - Measuring devices for evaluating the respiratory organs
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
A61B 5/1477 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value using chemical or electrochemical methods, e.g. by polarographic means non-invasive
Described herein are methods for identifying a labor state in a pregnant female, including: receiving an input indicating a gestational age; acquiring a physiological signal; processing the physiological signal to extract a parameter of interest; and feeding the parameter of interest into a machine learning model. The machine learning model is configured to: determine a first labor probability based on the parameter of interest, determine a second labor probability based on the parameter of interest or a second parameter of interest and the gestational age, and classify the labor state of the pregnant female based on the first and second labor probability.
A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.
A system for monitoring fetal wellbeing over time during pregnancy includes a sensor coupled to a pregnant woman; a processor communicatively coupled to the sensor; and a computer-readable medium having non-transitory, processor-executable instructions stored thereon. Execution of the instructions causes the processor to perform a method including: acquiring a signal from a sensor; processing the signal to identify and extract a parameter of interest from the signal; and analyzing the parameter of interest to determine a degree of fetal wellbeing. The parameter of interest may include one or more of: an average fetal heart rate, an average fetal heart rate variability, a fetal kick or movement count, an average placental oxygenation level, an average placental temperature, an average placental pH, an average amount of amniotic fluid, a fetal heart rate profile, a fetal heart rate variability profile, and a fetal movement profile.
Described herein are systems and methods for contraction monitoring. For example, a system for contraction monitoring includes an electrode patch including at least two electrodes, and a sensor module configured to be connected to the electrode patch. In some embodiments, the sensor module includes a signal acquisition module, a signal processing module, a power management module, a sensor control module, and a memory module and/or a data transmission module. In some embodiments, a method for contraction monitoring includes measuring, using the signal acquisition module, bio-potential signals by providing at least two electrodes on the abdomen of a pregnant woman. In some embodiments, a method for contraction monitoring includes processing, using the signal processing module, the bio-potential signal to extract electrohysterogram signals, maternal electrocardiogram signals and fetus electrocardiogram signals, and processing, using the signal processing module, the individual signals to extract uterine contraction.
A system for monitoring health parameters of a user includes a housing including: a plurality of sensors disposed on an outer surface of the housing or within the housing for measuring a plurality of parameters of interest; a processor disposed in the housing and communicatively coupled to the plurality of sensors; a coupling element on the housing for coupling the housing to an accessory; and an accessory identifier positioned on or within the housing and communicatively coupled to the processor. In some embodiments, the housing is reversibly transitionable between an uncoupled state and a coupled state with the accessory. In the coupled state, the accessory identifier senses a type of accessory and the processor activates a subset of the plurality of sensors to measure a subset of the plurality of parameters of interest. In some embodiments, the user is a pregnant female and a fetus developing in the pregnant female.
A61B 5/16 - Devices for psychotechnicsTesting reaction times
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
A61B 5/1468 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value using chemical or electrochemical methods, e.g. by polarographic means
Described herein are systems and methods for providing information to a user based on acquire sensor data and linking observations to acquired sensor data. A computer-implemented method for providing information to a user based on acquired sensor data and database information includes acquiring a first signal output from a first sensor; identifying a reproducible feature in the first signal output; extracting the reproducible feature from the first signal output; translating the reproducible feature into a first human-intelligible element; and querying, using the first human-intelligible element, a data source to identify a second human-intelligible element. Together, the first and second human-intelligible elements describe or identify the unknown condition. The method may include identifying similarities in a plurality of human- intelligible elements received from a user and a signal output received from a sensor associated with the user; and creating a link between the similar human-intelligible elements and the signal output.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
A apparatus for automatically detecting a pregnancy status of a patient include a patch for adhering to human skin, a uterine contraction sensor, such as electromyography (EMG), coupled to the patch with at least two electrodes, and an inertial sensor for sensing fetal movement, or Fetal Heart Rate (FHR) sensor, such as Fetal EKG or a Doppler Ultrasound. An electronic circuit is coupled to the patch, the EMG sensor and the inertial sensor, and/or FHR sensor. The circuit provides an output based on a uterine contraction signal from the EMG sensor (or Doppler ultrasound) correlated in time to a fetal movement, and/or fetal heart rate. The apparatus may include a thermometer to aid in automatically providing an indication of a pregnancy complication or ovulation status of the patient, based on the output.
A system for detecting and quantifying deviations from physiological signals normality and methods for making and using same. Each subject physiology follows unique patterns. The physiological signals can be affected by one or more factors such as circadian rhythm, disease and/or external stressors. Deviations of physiological signals from the normality of a subject can be indicative of external events that might require proper lifestyle management or just in time interventions, such as being exposed to high stress or the progress/onset of specific disease conditions. The disclosed system advantageously can quantify such deviations.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
12.
SYSTEM AND METHOD FOR PROVIDING BIOMETRIC AND CONTEXT BASED MESSAGING
A system suitable for generating messages based on biometric and contextual data and methods for making and using the same. One or more sensors can be used to measure biometric and/or contextual data. The measured data are analyzed using behavior analytics to capture behavior of a selected user. The behavior is analyzed with messaging analytics to generate personalized messages related to the behavior. The message preferably is personalized at least one level, such as time, place and format of message delivery, content of the message, and tone of the message. The message personalization can further adapt to changes in the user's behavior and/or preferences. Thereby, the method and system advantageously can provide biometric and context based messaging for motivating healthy behavior.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
Described herein are systems and methods for contraction monitoring. For example, a system for contraction monitoring includes an electrode patch including at least two electrodes, and a sensor module configured to be connected to the electrode patch. In some embodiments, the sensor module includes a signal acquisition module, a signal processing module, a power management module, a sensor control module, and a memory module and/or a data transmission module. In some embodiments, a method for contraction monitoring includes measuring, using the signal acquisition module, biopotential signals by providing at least two electrodes on the abdomen of a pregnant woman. In some embodiments, a method for contraction monitoring includes processing, using the signal processing module, the bio-potential signal to extract electrohysterogram signals, maternal electrocardiogram signals and fetus electrocardiogram signals, and processing, using the signal processing module, the individual signals to extract uterine contraction.
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