Apple Inc.

Masimo Corporation

Michael O'reilly

Ammar Al-Ali

Bilal Muhsin

Myra Mary Haggerty

Stephen J Waydo

Ian R Shapiro

Christopher J Brouse

Joseph C McBride

This relates to methods for measuring irregularities in a signal and corresponding devices. The devices can include a PPG sensor unit configured to detect multiple occurrences of a given event in the measured signal(s) over a sampling interval. In some instances, the device can register the occurrences of the events. In some examples, the device can include one or more motion sensors configured to detect whether the device is in a low-motion state. The device may delay initiating measurements when the device is not in a low-motion state to enhance measurement accuracy. Examples of the disclosure further include resetting the sample procedure based on one or more factors such as the number of non-qualifying measurements. In some examples, the device can be configured to perform both primary and secondary measurements, where the primary measurements can include readings using a set of operating conditions different from the secondary measurements.

Detecting conditions using heart rate sensors

This disclosure describes, among other features, systems and methods for using multiple physiological parameter inputs to determine multiparameter confidence in respiratory rate measurements. For example, a patient monitoring system can programmatically determine multiparameter confidence in respiratory rate measurements obtained from an acoustic sensor based at least partly on inputs obtained from other non-acoustic sensors or monitors. The patient monitoring system can output a multiparameter confidence indication reflective of the programmatically-determined multiparameter confidence. The multiparameter confidence indication can assist a clinician in determining whether or how to treat a patient based on the patient's respiratory rate.

System and method for monitoring respiratory rate measurements

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San Jose, CA, United States of America

Michael O'reilly