# US 11,992,342 B2 · Acoustic respiratory monitoring sensor with probe-off detection

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- Number: US 11,992,342 B2
- Document ID: US11992342B2
- Status: Granted
- Kind: B2
- Application number: 15/693,854
- Filed: 2017-09-01
- Published: 2018-03-29
- Granted: 2024-05-28
- Earliest claimed: 2013-01-02
- Assignees: Masimo Corporation
- Applicants: Masimo Corporation
- Inventors: Valery G. Telfort
- Web page: https://patentgrep.com/patent/US11992342B2

## CPC

- A61B 5/7221: {Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217)}
- A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B 5/02416: {using photoplethysmograph signals, e.g. generated by infrared radiation (A61B5/14552 takes precedence)}
- A61B 5/0261: {using optical means, e.g. infrared light}
- A61B 5/0295: using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
- A61B 5/0816: {Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00)}
- A61B 5/33: specially adapted for cooperation with other devices
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A61B 5/725: {using specific filters therefor, e.g. Kalman or adaptive filters (specific diagnostics methods using using bioelectric or biomagnetic signals A61B5/316)}
- A61B 5/7257: {using Fourier transforms}
- A61B 5/726: {using Wavelet transforms}
- A61B 5/7278: {Artificial waveform generation or derivation, e.g. synthesizing signals from measured signals}
- A61B 7/003: {Detecting lung or respiration noise}
- A61B 7/026: {comprising more than one sound collector}
- A61B 7/04: Electric stethoscopes
- A61B 2560/0266: for monitoring or limiting apparatus function
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

Embodiments described herein include sensors and sensor systems having probe-off detection features. For example, sensors and physiological monitors described herein include hardware and/or software capable of providing an indication of the integrity of the connection between the sensor and the patient. In various embodiments, the physiological monitor is configured to output an indication of a probe-off condition for an acoustic sensor (or other type of sensor). For example, in an embodiment, a signal from an acoustic sensor is compared with a signal from a second sensor to determine a probe-off condition.

## Claims

### Claim 1

A method of automating detection of whether a sensor is properly attached to a patient, the method comprising:
receiving an acoustic physiological signal from an acoustic sensor configured to be attached to a neck of the patient;
transforming the acoustic physiological signal into a frequency domain;
extracting energy of low frequency components in the frequency transformed acoustic physiological signal;
determining a first pulse rate from the extracted energy of the low frequency components;
receiving a second pulse rate responsive to processing of photoplethysmograph (PPG) waveform from an optical sensor that is configured to couple with a finger of the patient and is separate from the acoustic sensor;
comparing the first pulse rate with the second pulse rate for a determination of a likelihood of good quality attachment of the acoustic sensor with a skin of the patient; and
in response to said comparison, outputting an indication of automated detection of whether the acoustic sensor is properly attached or detached from the skin of the patient.

### Claim 2 (depends on 1)

The method of claim 1, wherein the extraction of energy comprises adding magnitude of low frequency components of the transformed acoustic physiological signal.

### Claim 3 (depends on 1)

The method of claim 1, wherein the extraction of energy comprises computing a power spectral density of the acoustic physiological signal.

### Claim 4 (depends on 1)

The method of claim 1, wherein the indication comprises an alarm.

### Claim 5 (depends on 1)

The method of claim 1, wherein the transform comprises wherein the transform comprises one or more of the following: a wavelet transform, a short-time Fourier transform, a chirplet transform, and a Gabor transform.

### Claim 6

A system of automating detection of whether a first sensor is properly attached to a patient, the system comprising one or more hardware processors configured to:
receive a first phisiological signal from the first sensor, said first sensor configured to be positioned on a patient's neck or chest;
receive a second physiological signal from a second sensor configured to be positioned on the patient's limb, wherein the second sensor is separate from the first sensor;
transform the first physiological signal into a frequency domain;
extract energy of low frequency components in the frequency transformed first physiological signal;
determine a first pulse rate from the extracted energy of the low frequency components;
determine a second pulse rate from the received second physiological signal;
compare the first pulse rate with the second pulse rate for a determination of a likelihood of good quality attachment of the first sensor with a skin of the patient; and
in response to said comparison, output an indication of automated detection of whether the first sensor or the second sensor is properly attached or detached from the skin of the patient.

### Claim 7 (depends on 6)

The system of claim 6, wherein the low frequency components include frequencies corresponding to a heart rate.

### Claim 8 (depends on 6)

The system of claim 6, wherein the extraction of energy comprises adding magnitude of low frequency components of the transformed first physiological signal.

### Claim 9 (depends on 6)

The system of claim 6, wherein the extraction of energy comprises computing a power spectral density of the first physiological signal.

### Claim 10 (depends on 6)

The system of claim 6, wherein the indication comprises an alarm.

### Claim 11 (depends on 6)

The system of claim 6, wherein the transform comprises wherein the transform comprises one or more of the following: a wavelet transform, a short-time Fourier transform, a chirplet transform, and a Gabor transform.

### Claim 12

A system of automating detection of whether a first sensor is properly attached to a patient, the system comprising one or more hardware processors configured to:
receive a first physiological signal from a rist sensor, said first sensor configured to be positioned on a patient's neck or chest;
receive a second physiological signal from a second sensor, said second sensor configured to be positioned on a limb of the patient, wherein the second sensor is separate from the first sensor;
determine a first pluse rate from the first physiological signal,
determine a second pulse rate from the second physiological signal;
compare the first pulse rate with the second pulse rate; and
in response to said comparison, output an indication of automated detection of whether the first or the second sensor is properly attached or detached from a skin of the patient.

### Claim 13 (depends on 12)

The system of claim 12, wherein the first pulse rate is determined by extracting low frequency components in the first physiological signal.

### Claim 14 (depends on 12)

The system of claim 12, wherein the indication comprises an alarm.

### Claim 15 (depends on 12)

The system of claim 12, wherein the second sensor comprises an optical sensor.

### Claim 16 (depends on 15)

The system of claim 15, wherein the second physiological signal comprises a photoplethysmograph (PPG) signal.