Oura Health Oy

Kaisa Helena Tarvainen

Hannu Olavi Kinnunen

Harri Laakkonen

Heli Koskimäki

Mari Karsikas

Janne Kukka

Matias Kukka

Alec Singleton

Johanna Still

Dmitry Sergeev

Petteri Lajunen

Tomi Liiten

Johanna Leena Kyllikki Still

Mats Kyyrö

Miska Valkonen

Methods, systems, and devices for physiological pattern recognition are described. A device may receive physiological data associated with a user from a wearable device. The device may determine that at least one physiological parameter associated with the received physiological data satisfies a physiological threshold associated with a pattern between the physiological threshold and a taggable event or a set of taggable events defined within an application associated with the wearable device. The device may then identify, based on the pattern, the taggable event or the set of taggable events indicating an activity the user engaged in that contributed to the at least one physiological parameter satisfying the physiological threshold, and cause a graphical user interface (GUI) of the device running the application to prompt the user to provide feedback associated with the identified taggable event or the identified set of taggable events.

Techniques for providing insights according to tags and physiological data

A method and system for supplemental sleep detection is described. A system may receive data associated with a user from a wearable device worn by the user, and may detect a primary sleep period for the user based on the received data. The system may additionally detect a supplemental sleep period including a duration that exceeds a threshold duration based on the received data. In some implementations, the system may cause a graphical user interface (GUI) of a user device to display an indication of the detected supplemental sleep period, and may receive a confirmation of the supplemental sleep period via the user device and in response to the indication of the detected supplemental sleep period. The system may subsequently generate one or more insights associated with the user based on the primary sleep period and the supplemental sleep period and, in some implementations, in response to the confirmation.

Method and system for supplemental sleep detection

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Oulu, Finland

Kaisa Helena Tarvainen