METHOD FOR PREDICTING RISK OF RELAPSE OR ONSET OF A PSYCHIATRIC CONDITION

    公开(公告)号:US20240371398A1

    公开(公告)日:2024-11-07

    申请号:US18610154

    申请日:2024-03-19

    Abstract: A method includes, for each user in a population: audio recording the user reciting a story configured to elicit an emotion associated with a psychiatric condition; concurrently recording a set of biosignals of the user; generating a set of psychophysiological markers correlating instances of the emotion and the set of biosignals; assessing a clinical assessment for the condition in the user; correlating the set of psychophysiological markers and the clinical assessment; and compiling the correlations into a model configured to predict risk of condition onset in a user. The method also includes: accessing a series of biosignals of a first user; identifying a series of psychophysiological markers in the series of biosignals; based on the series of psychophysiological markers and the model, calculating a risk of onset of the condition in the first user; and, in response to the risk exceeding a threshold, serving the notification to the first user.

    Method for detecting and recognizing an emotional state of a user

    公开(公告)号:US11967339B2

    公开(公告)日:2024-04-23

    申请号:US17861158

    申请日:2022-07-08

    CPC classification number: G10L25/63 G06F11/327 G06V40/20

    Abstract: A method includes: prompting a user to recite a story associated with a first target emotion; recording the user reciting the story and recording a first timeseries of biosignal data via a set of sensors integrated into a wearable device worn by the user; accessing a first timeseries of emotion markers extracted from the voice recording; labeling the first timeseries of biosignal data according to the first timeseries of emotion markers; generating an emotion model linking biosignals to emotion markers for the user based on the first emotion-labeled timeseries of biosignal data; detecting a second instance of the first target emotion exhibited by the user based on a second timeseries of biosignal data and the emotion model; and notifying the user of the second instance of the first target emotion.

    SYSTEM AND METHOD FOR CHARACTERIZING, DETECTING AND MONITORING SLEEP DISTURBANCES AND INSOMNIA SYMPTOMS

    公开(公告)号:US20230301586A1

    公开(公告)日:2023-09-28

    申请号:US18126100

    申请日:2023-03-24

    CPC classification number: A61B5/4809 G16H50/50 A61B5/0205 A61B5/4815

    Abstract: One variation of a method includes: accessing a first timeseries of biosignal data collected by a wearable device worn by a user during a first time period; deriving a first insomnia profile, representative of a set of health indicators exhibited by the user during the first time period, based on the first timeseries of biosignal data; and selecting a treatment pathway for implementation by the user based on the first insomnia profile. The method further includes: accessing a second timeseries of biosignal data collected for the user by the wearable device during a second time period; deriving a second insomnia profile, representative of the set of health indicators exhibited by the user during the second time period, based on the second timeseries of biosignal data; and characterizing effectiveness of the treatment pathway based on a difference between the first insomnia profile and the second insomnia profile.

    METHOD FOR DETECTING AND RECOGNIZING AN EMOTIONAL STATE OF A USER

    公开(公告)号:US20220343941A1

    公开(公告)日:2022-10-27

    申请号:US17861158

    申请日:2022-07-08

    Abstract: A method includes: prompting a user to recite a story associated with a first target emotion; recording the user reciting the story and recording a first timeseries of biosignal data via a set of sensors integrated into a wearable device worn by the user; accessing a first timeseries of emotion markers extracted from the voice recording; labeling the first timeseries of biosignal data according to the first timeseries of emotion markers; generating an emotion model linking biosignals to emotion markers for the user based on the first emotion-labeled timeseries of biosignal data; detecting a second instance of the first target emotion exhibited by the user based on a second timeseries of biosignal data and the emotion model; and notifying the user of the second instance of the first target emotion.

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