Google Inc.

Yojan Patel

Melissa Frank

Justin Phillips

SeongHwan Cho

A cardiovascular monitoring system includes a first monitoring device configured to couple to a first body part of a subject and a second monitoring device configured to couple to a second body part of the subject. The first monitoring device is configured to measure a first cardiovascular signal and a first motion signal at the first body part, and the second monitoring device is configured to measure a second cardiovascular signal and a second motion signal at the second body part. A controller of the system receives the first and second cardiovascular signals and the first and second motion signals and filters the first and second cardiovascular signals by removing spectral components that correspond to spectral components of the first and second motion signals. Based on a correlated spectral component that is present in both the filtered first and second cardiovascular signals, the system determines cardiovascular information of the subject.

Cardiovascular monitoring using multiple sensors

Methods, systems, and method for predicting sensor measurement quality. In some implementations, the method comprises: measuring, using a wearable computing device that includes a processor and a sensor, information indicating motion of the wearable computing device during a current time period; identifying one or more parameters associated with a determination of a likelihood that one or more measurements from the sensor configured within the wearable computing device is of sufficient quality for calculating a physiological metric using the one or more measurements from the sensor, wherein the one or more parameters include contextual parameters associated with the wearable computing device; determining the likelihood that the measurement from the sensor associated with the user device is of sufficient quality at a second time period for calculating the physiological metric using the measurement from the sensor based on the identified one or more parameters and based on the information indicating the motion of the user device during the current time period; in response to determining that the likelihood exceeds a predetermined threshold, activating the processor and the sensor and collecting a measurement from the sensor at the second time period; and updating the identified one or more parameters based on the motion of the user device during the current time period and based on the measurement from the sensor at the second time period.

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London, United Kingdom

Yojan Patel