Masimo Corporation

Anmol Majmudar

Ammar Al-Ali

Walter M Weber

Mohamed Kheir Diab

Sung Uk Lee

Gilberto Sierra

Boris Popov

Marc Pelletier

Valery G Telfort

Michael O'Reilly

Eric Karl Kinast

A plethysmograph variability processor inputs a plethysmograph waveform having pulses corresponding to pulsatile blood flow within a tissue site. The processor derives plethysmograph values based upon selected plethysmograph features, determines variability values, and calculates a plethysmograph variability parameter. The variability values indicate the variability of the plethysmograph features. The plethysmograph variability parameter is representative of the variability values and provides a useful indication of various physiological conditions and the efficacy of treatment for those conditions.

Plethysmograph variability processor

Respiratory rate can be calculated from an acoustic input signal using time domain and frequency domain techniques. Confidence in the calculated respiratory rate can also be calculated using time domain and frequency domain techniques. Overall respiratory rate and confidence values can be obtained from the time and frequency domain calculations. The overall respiratory rate and confidence values can be output for presentation to a clinician.

Respiration processor

A plethysmographic respiration processor is responsive to respiratory effects appearing on a blood volume waveform and the corresponding detected intensity waveform measured with an optical sensor at a blood perfused peripheral tissue site so as to provide a measurement of respiration rate. A preprocessor identifies a windowed pleth corresponding to a physiologically acceptable series of plethysmograph waveform pulses. Multiple processors derive different parameters responsive to particular respiratory effects on the windowed pleth. Decision logic determines a respiration rate based upon at least a portion of these parameters.

Plethysmographic respiration rate detection

Plethysmographic respiration processor

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 for determining confidence in respiratory rate measurements

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Irvine, CA, United States of America

Anmol Majmudar