Apparatus, system, and method for physiological sensing in vehicles

    公开(公告)号:US11707197B2

    公开(公告)日:2023-07-25

    申请号:US15733174

    申请日:2018-12-21

    Abstract: Methods and apparatus provide physiological movement detection, such as gesture, breathing, cardiac and/or gross motion, such as with sound, radio frequency and/or infrared generation, by electronic devices such as vehicular processing devices. The electronic device in a vehicle may, for example, be any of an audio entertainment system, a vehicle navigation system, and a semi-autonomous or autonomous vehicle operations control system. One or more processors of the device, may detect physiological movement by controlling producing sensing signal(s) in a cabin of a vehicle housing the electronic device. The processor(s) control sensing, with a sensor, reflected signal(s) from the cabin. The processor(s) derive a physiological movement signal with the sensing signal and reflected signal and generate an output based on an evaluation of the derived physiological movement signal. The output may control operations or provide an input to any of the entertainment system, navigation system, and vehicle operations control system.

    SYSTEMS AND METHODS FOR INSOMNIA SCREENING AND MANAGEMENT

    公开(公告)号:US20230191057A1

    公开(公告)日:2023-06-22

    申请号:US18069750

    申请日:2022-12-21

    Abstract: A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related parameters.

    SYSTEMS AND METHODS FOR DETECTING AN INTENTIONAL LEAK CHARACTERISTIC CURVE FOR A RESPIRATORY THERAPY SYSTEM

    公开(公告)号:US20230085305A1

    公开(公告)日:2023-03-16

    申请号:US17801096

    申请日:2021-03-05

    Abstract: A plurality of flow rate values associated with pressurized air directed to an airway of a user of a respiratory therapy system is received. A plurality of pressure values associated with the pressurized air directed to the airway of the user is received. A first time associated with a first breath of the user and a second time associated with a second breath of the user are identified. The plurality of flow rate values is filtered based at least in part on the identified first time and the identified second time. The filtering produces a subset of the plurality of flow rate values. An intentional leak characteristic curve for the respiratory therapy system is determined using at least two of the subset of the plurality of flow rate values and the corresponding pressure values for said at least two of the subset of the plurality of flow rate values.

    Apparatus, system and method for chronic disease monitoring

    公开(公告)号:US10799126B2

    公开(公告)日:2020-10-13

    申请号:US15343994

    申请日:2016-11-04

    Abstract: An apparatus, system, and method for monitoring a person suffering from a chronic medical condition predicts and assesses physiological changes which could affect the care of that subject. Examples of such chronic diseases include (but are not limited to) heart failure, chronic obstructive pulmonary disease, asthma, and diabetes. Monitoring includes measurements of respiratory movements, which can then be analyzed for evidence of changes in respiratory rate, or for events such as hypopneas, apneas and periodic breathing. Monitoring may be augmented by the measurement of nocturnal heart rate in conjunction with respiratory monitoring. Additional physiological measurements can also be taken such as subjective symptom data, blood pressure, blood oxygen levels, and various molecular markers. Embodiments for detection of respiratory patterns and heart rate are disclosed, together with exemplar implementations of decision processes based on these measurements.

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