APPARATUS, SYSTEM AND METHOD FOR CHRONIC DISEASE MONITORING

• US 20100204550A1
• Filed: 02/06/2009
• Published: 08/12/2010
• Est. Priority Date: 02/06/2009
• Status: Active Grant

• Current Assignee: ResMed Sensor Technologies Limited (ResMed Incorporated)
• Original Assignee: BiancaMed Limited (ResMed Incorporated)
• Inventors: DE CHAZAL, Philip, SHOULDICE, Redmond, ZAFFARONI, Alberto, HENEGHAN, Conor
• Granted Patent: US 9,526,429 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• 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 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: G01S 13/50 Systems of measurement based on relative movement of target
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

An apparatus, system, and method for monitoring a person suffering from a chronic medical condition predicts and assesses physiological changes which could affect the care of that subject. Examples of such chronic diseases include (but are not limited to) heart failure, chronic obstructive pulmonary disease, asthma, and diabetes. Monitoring includes measurements of respiratory movements, which can then be analyzed for evidence of changes in respiratory rate, or for events such as hypoponeas, apneas and periodic breathing. Monitoring may be augmented by the measurement of nocturnal heart rate in conjunction with respiratory monitoring. Additional physiological measurements can also be taken such as subjective symptom data, blood pressure, blood oxygen levels, and various molecular markers. Embodiments for detection of respiratory patterns and heart rate are disclosed, together with exemplar implementations of decision processes based on these measurements.

Claims

1. A system for monitoring a subject, the system comprising:

a sensor configured to output a signal comprising a measured respiratory parameter of the subject;

an analyzer configured to receive the signal and to store, in a memory, at least a plurality of respiratory features derived from the respiratory parameter,

wherein the analyzer is configured to selectively combine the plurality of respiratory features to determine an output that provides a health assessment of the subject.

2. The system of claim 1, further comprising a cardiac sensor operatively coupled to the analyzer, wherein the analyzer is further configured to store a plurality of cardiac features derived from a detected cardiac parameter, wherein the analyzer is configured to selectively combine the plurality of cardiac features with the plurality of respiratory features to determine the output that provides a health assessment of the subject.

3. The system of claim 1, further comprising an input signal supplied to the analyzer that provides a measure of a body weight of the subject.

4. The system of claim 1, further comprising an input signal supplied to the analyzer that provides subjective symptom data from the subject.

5. The system of claim 1, further comprising an input signal supplied to the analyzer that provides one or more physiological measurements selected from the group consisting of a blood pressure, a forced expiratory volume, a peak expiratory flow, a blood oxygen level, a blood glucose level, a measurement of B natriuretic peptides, and a measurement of C-reactive protein.

6. The system of claim 1, wherein the sensor comprises a radio frequency (RF) sensor configured to receive reflected RF signals off the subject;

7. The system of claim 1, further comprising a data hub configured to exchange data at least between the sensor and the analyzer.

8. The system of claim 1, wherein a derived movement signal is calculated through a combination of two quadrature movement signals using a phase demodulation technique.

9. The system of claim 1, wherein the analyzer calculates a respiratory effort envelope that indicates a relative amplitude of respiratory effort.

10. The system of claim 9, wherein the analyzer determines a respiratory pattern by analyzing the respiratory effort envelope.

11. The system of claim 1, wherein the analyzer is configured to determine an occurrence of apneas and hypoponeas using the measured respiratory parameter.

12. The system of claim 1, wherein the analyzer is configured to determine an occurrence of periodic breathing using the measured respiratory parameter.

13. The system of claim 1, wherein the analyzer is configured to determine a characteristic time period of periodic breathing using the measured respiratory parameter.

14. The system of claim 1, wherein the measured respiratory parameter comprises a respiration rate of the subject.

15. The system of claim 1, wherein the analyzer is configured to apply a set of automated rules stored in the memory that propose and output a clinical intervention step at least based on the measured respiratory parameter.

16. The system of claim 1, wherein the analyzer is configured to calculate a likelihood of a significant clinical deterioration having occurred based at least on the measured respiratory parameter.

17. The system of claim 1 further comprising a display operatively coupled to the analyzer such that a trend in the measured respiratory parameter may be visualized.

18. The system of claim 1, wherein the signal output by the sensor comprises a composite signal that includes a respiratory feature, a cardiac feature, and a bodily motion feature, and wherein the analyzer is configured to selectively combine the respiratory feature, the cardiac feature, and the bodily motion feature to determine the output that provides the health assessment of the subject.

19. A computer-implemented method for monitoring a subject, the method comprising:

measuring a respiratory parameter of the subject using a sensor;

generating, with a processor, a plurality of respiratory features derived from the respiratory parameter,

combining the plurality of respiratory features to calculate an output that provides a health assessment of the subject.

20. The method of claim 19, further comprising combining one or more of the plurality of respiratory features with a plurality of features based on cardiac measurements to derive the output.

21. The method of claim 19, further comprising combining one or more of the plurality of respiratory features with a plurality of features based on subjective symptom data indicated by the subject to derive the output.

22. The method of claim 19, further comprising combining one or more of the plurality of respiratory features with one or more physiological measurements selected from the group consisting of body weight, a blood pressure, a forced expiratory volume, a peak expiratory flow, a blood oxygen level, a blood glucose level, a measurement of B natriuretic peptides, and a measurement of C-reactive protein to derive the output.

23. A computer-implemented method for assessing changes in the health of a subject, the method comprising:

calculating for a first time period, one or more parameters selected from the group consisting of a respiratory rate of a subject;

a incidence of apneas and hypoponeas, and an amplitude and period of periodic breathing;

calculating, for a second time period after the first time period, said one or more parameters selected from said group;

comparing said calculated one or more parameters from the first time period with said calculated one or more parameters from the second time period to obtain a comparison result; and

determining a change in health status based on the comparison result.