Oura Health Oy

Heli Tuulia Koskimäki

Antti Aleksi Rantanen

Jussi Petteri Järvelä

Hannu Olavi Kinnunen

Tero Vallius

Harri Laakkonen

Jukka Tapani Mäkinen

Olli Petteri Heikkinen

Michael Chapp

Mika Erkkilä

Juha-Pekka Syrjälä

Veli-Pekka Kullervo Halme

Steve Kent

Pauli Juhani Ohukainen

Juha Pekka Pärkkä

Juka-Pekka Syrjälä

Mikko Pellervo Tuohimaa

Robert Alexander Singleton

Hannu Hermanni Koivisto

Methods, systems, and devices for determining blood pressure based on a relative timing of pulses are described. In some implementations, a system may include one or more wearable devices configured to measure heartbeats at different locations on the body of a user. The different locations may be different physiological locations (e.g., chest and finger/wrist), and/or different penetration depths at the same physiological location. The system may use the components of the wearable devices to acquire physiological data and to observe one or more heartbeats of the user over a time period. The system may compare pulse observation times observed at the different locations, and may determine a blood pressure metric for the user based on a relative timing of when heartbeats are observed at the different locations.

Techniques for determining blood pressure based on a relative timing of pulses

Methods, systems, and devices for leveraging data from multiple data sources are described. A method includes receiving physiological data associated with a user from a wearable device and receiving additional data from an external device different from the wearable device, the additional data including at least data associated with characteristics of an environment associated with the user. The method further includes identifying one or more relationships between the collected physiological data and the characteristics of the environment associated with the user, and causing a graphical user interface (GUI) of a user device to display an indication of the one or more relationships, a message associated with the one or more relationships, or both. In some cases, the method includes causing the GUI to display instructions for selectively adjusting the one or more characteristics of the environment associated with the user based on the one or more relationships.

Techniques for leveraging data collected by wearable devices and additional devices

Methods, systems, and devices for determining blood pressure based on morphological features of pulses are described. A system may include a wearable device that uses one or more light emitting components configured to emit light, one or more photodetectors configured to receive light, and a controller that couples the one or more light emitting components to the one or more photodetectors. The wearable device may transmit lights associated with multiple wavelengths, and acquire photoplethysmogram (PPG) data that includes one or more PPG waveforms associated with the respective wavelengths. The system may determine respective sets of morphological features associated with each of the PPG waveforms based on systolic and diastolic peaks corresponding to the heartbeat of the user. The system may determine one or more blood pressure metrics for the user based at least in part on a comparison of the respective sets of morphological features.

Techniques for determining blood pressure based on morphological features of pulses preliminary class

A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

Method and system for monitoring and improving sleep pattern of user

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Oulu, Finland

Heli Tuulia Koskimäki