BODY-WORN MONITOR FOR MEASURING RESPIRATION RATE

• US 20110066007A1
• Filed: 09/14/2009
• Published: 03/17/2011
• Est. Priority Date: 09/14/2009
• Status: Active Grant

• Current Assignee: Sotera Wireless Incorporated
• Original Assignee: Sotera Wireless Incorporated
• Inventors: Dhillon, Marshal, McCombie, Devin, Banet, Matt
• Granted Patent: US 10,123,722 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0535 Impedance plethysmography for measuring blood flow A61B5/0295
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B

Abstract

The invention provides a multi-sensor system that uses an algorithm based on adaptive filtering to monitor a patient'"'"'s respiratory rate. The system features a first sensor selected from the following group: i) an impedance pneumography sensor featuring at least two electrodes and a processing circuit configured to measure an impedance pneumography signal; ii) an ECG sensor featuring at least two electrodes and an ECG processing circuit configured to measure an ECG signal; and iii) a PPG sensor featuring a light source, photodetector, and PPG processing circuit configured to measure a PPG signal. Each of these sensors measures a time-dependent signal which is sensitive to respiratory rate and, during operation, is processed to determine an initial respiratory rate value. An adaptive digital filter is determined from the initial respiratory rate. The system features a second sensor (e.g. a digital 3-axis accelerometer) that attaches to the patient'"'"'s torso and measures an ACC signal indicating movement of the chest or abdomen that is also sensitive to respiratory rate. This second signal is processed with the adaptive filter to determine a final value for respiratory rate.

Claims

1. A method for determining a respiration rate value from a patient, comprising the following steps:

(a) measuring a first time-dependent signal by detecting a modulated electrical current passing through the patient'"'"'s torso;

(b) measuring a second time-dependent signal by detecting respiration-induced movements in the patient'"'"'s torso with at least one motion sensor;

(c) determining a motion-related event not related to the patient'"'"'s respiration rate value by processing signals from at least one motion sensor; and

(d) collectively processing both the first and second time-dependent signals to determine a value for respiration rate corresponding to a period when at the motion-related event is below a pre-determined threshold.

4. The method of claim 1, wherein step (c) further comprises processing signals from the motion sensor to determine a motion-related event selected from the patient'"'"'s posture, activity level, and degree of motion.

5. The method of claim 4, wherein the motion-related event is posture, and step (c) further comprises determining a parameter corresponding to orientation of the patient'"'"'s torso.

6. The method of claim 5, wherein the parameter corresponding to orientation of the patient'"'"'s torso is a vector.

7. The method of claim 6, wherein step (c) further comprises processing signals corresponding to three axes of the motion sensor to determine the vector.

8. The method of claim 1, wherein the at least one motion sensor is an accelerometer.

9. The method of claim 7, wherein step (c) further comprises comparing the vector to a pre-determined coordinate system to determine an angle.

10. The method of claim 9, wherein step (c) further comprises comparing the angle to a set of pre-determined values, each corresponding to a different posture, to determine the patient'"'"'s posture.

11. The method of claim 4, wherein the motion-related event is activity level, and step (c) further comprises processing time-dependent variations in signals from the motion sensor to determine the activity level.

12. The method of claim 11, wherein the activity level corresponds to one of moving, walking, falling, convulsing.

13. The method of claim 11, wherein step (c) further comprises performing a mathematical transform of the time-dependent variations to determine a frequency-domain spectrum.

14. The method of claim 13, wherein step (c) further comprises comparing portions of the frequency-domain spectrum to pre-determined frequency parameters to determine the activity level.

15. The method of claim 11, wherein step (c) further comprises comparing magnitudes of the time-dependent variations to pre-determined magnitude parameters to determine the activity level.

16. The method of claim 11, wherein step (c) further comprises taking a mathematical derivative of the signals from the motion sensor to determine the time-dependent variations.

17. The method of claim 4, wherein the motion-related event is a degree of motion, and step (c) further comprises determining an amplitude of a portion of the signals from the motion sensor to determine the degree of motion.

18. The method of claim 17, wherein step (c) further comprises performing a mathematical transform of the time-dependent variations to determine a frequency-domain spectrum.

19. The method of claim 18, wherein step (c) further comprises determining a power of the frequency-domain spectrum to determine the degree of motion.

20. The method of claim 1, wherein step (d) further comprises determining an initial respiration rate vale from one of the first and second time-dependent signals, and then adaptively filtering one of the first and second time-dependent signals with a mathematical filter determined from the initial respiration rate value.

21. The method of claim 1, wherein step (d) further comprises determining the initial respiration rate value from the first time-dependent signal, and then adaptively filtering the second time-dependent signal with a mathematical filter determined from the initial respiration rate value.

2. A method for determining a respiration rate value from a patient, comprising the following steps:

(a) measuring a first time-dependent signal by detecting a modulated electrical current passing through the patient'"'"'s torso;

(b) measuring a second time-dependent signal by detecting respiration-induced movements in the patient'"'"'s torso with at least one motion sensor;

(c) measuring a third time-dependent signal by analyzing an envelope of an ECG waveform measured from the patient;

(d) determining one of the patient'"'"'s activity level, posture, and degree of motion by processing signals from at least one motion sensor;

(e) determining when one of the patient'"'"'s activity level, posture, and degree of motion exceeds a pre-determined threshold limit; and

(f) displaying a respiration rate value calculated from the third time-dependent signal, or a parameter calculated therefrom, when one of the patient'"'"'s activity level, posture, and degree of motion exceeds a pre-determined threshold limit.

3. A method for determining a respiration rate value from a patient, comprising:

(a) measuring at least one electrical signal affected by respiration rate with a first sensor;

(b) measuring a first motion signal affected by respiration rate with a second sensor;

(c) measuring a second motion signal affected by the patient'"'"'s posture with a motion sensor; and

(d) collectively processing the electrical signal, first motion signal, and second motion signal to determine a respiration rate value for the patient.