Method, device, and system for diagnosing and monitoring frailty

• US 10,299,736 B2
• Filed: 03/27/2015
• Issued: 05/28/2019
• Est. Priority Date: 03/27/2014
• Status: Active Grant

• Current Assignee: Arizona Board of Regents (University of Arizona)
• Original Assignee: Arizona Board of Regents (University of Arizona)
• Inventors: Najafi, Bijan, Parvaneh, Saman, Mohler, Martha Jane, Armstrong, David G., Fain, Mindy Joy, Slepian, Marvin J.
• Primary Examiner(s): Koharski, Christopher
• Assistant Examiner(s): So, Elizabeth K
• Application Number:
  US14/671,980
• Publication Number:
  US 20150272511A1
• Time in Patent Office: 1,523 Days
• Field of Search: None
• 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 5/02405 Determining heart rate variability
• 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 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 40/63 for local operation

Abstract

Methods, devices, and systems according to present principles provide ways to diagnose frailty and assess the severity of its clinical status—e.g., non-frail, pre-frail, and frail, especially as measured and quantified during activities of daily living. Systems and methods according to present principles objectively quantify physical activity behaviors and identify specific motor tasks, which indicate clinical frailty syndrome behaviors such as flopping, cautious-sitting, non-uniform walking fluctuations, cognitive decline, slowness, weakness, and exhaustion. Additionally, the systems and methods allow improved sensitivity and specificity of frailty identification by further assessing physiological parameters such as heart rate, respiration rate, and skin temperature in response to, or recovery from, specific activities.

Claims

1. An ambulatory system to identify the presence and degree of frailty comprising:

a wearable sensor, configured to be attached to or worn by a person, the sensor configured to be attached to an upper body of a person, the sensor including at least an accelerometer configured to generate signals in response to motion or movements of the person, the accelerometer configured to measure at least a frontal acceleration pattern; and

one or more processor circuits configured to receive and analyze one or more signals from the accelerometer as a result of spontaneous daily activity, the processor circuits configured to determine information about frailty status including at least a determination that assists in the classification of the person as non-frail, pre-frail, or frail, the one or more processor circuits performing at least the following steps;

determining a score for one or more frailty related biomarkers selected from the group consisting of;

flopping, cautious sitting, slowness, weakness, cognitive decline, cautious sit to walk, or exhaustion, the score determined based at least on the measured frontal acceleration pattern measured by the accelerometer, the score further determined based on identifying activities measured by the accelerometer as being dynamic or static;

determining a score for one or more physiological responses to the identified dynamic or static activities, the responses selected from the group consisting of;

heart rate, heart rate variability, respiration rate, or skin temperature, the determined score for one or more physiological responses to the identified dynamic or static activities based at least in part on abnormal physiological responses to the identified dynamic or static activities, and

using the determined score for the one or more frailty related biomarkers as determined by the one or more processor circuits analyzing the signals from the accelerometer and the determined score for the one or more physiological responses to calculate an overall score, and from the overall score classifying the person into one of a plurality of predetermined classifications, the predetermined classifications including at least non-frail, pre-frail, or frail, wherein the classifying provides an early identification of early markers of frailty to allow early intervention and rehabilitation as compared to non-ambulatory systems that do not use signals resulting from spontaneous daily activity.

2. The system of claim 1, wherein the information about frailty status is transmitted wireless in real time or at predefined periods of time to a receiver.

3. The system of claim 1, wherein the accelerometer is configured to measure a frontal acceleration pattern, and wherein said one or more processor circuits are further programmed to identify a sit to stand or stand to sit postural transfer based on identifying a dynamic pattern before or after a peak detected in the frontal acceleration pattern.

4. The system of claim 1, wherein the accelerometer is configured to measure vertical accelerations, and wherein said one or more processor circuits are further programmed to:

identify the dynamic or the static activity based on a standard deviation of a vertical or a frontal acceleration in a pre-defined interval, including a predefined interval before and after a postural transfer.

5. The system of claim 4, wherein said one or more processor circuits are further programmed to identify a standing posture if a dynamic activity and a static activity are identified immediately after and before a postural transfer, respectively.

6. The system of claim 4, wherein said one or more processor circuits are further programmed to identify a sitting posture if a static activity and a dynamic activity are identified immediately after and before a postural transfer, respectively.

7. The system of claim 4, wherein said one or more processor circuits are further programmed to measure a speed of low intensity movement based on an integration of acceleration during a static activity followed by a removal of drift of integration.

8. The system of claim 4, wherein said one or more processor circuits are further programmed to measure a speed of a high intensity movement based on an integration of acceleration during a dynamic activity followed by a removal of drift of integration.

9. The system of claim 4, wherein said one or more processor circuits are further programmed to identify frailty status by measuring a number of flopping events occurring within a pre-defined interval by identifying a number of immediate transfers from a dynamic activity to a static activity with a transfer speed of greater than a pre-defined threshold.

10. The system of claim 4, wherein said one or more processor circuits are further programmed to identify frailty status by measuring a number of cautious-sitting events occurring within a pre-defined interval by identifying a sequence of a dynamic activity followed by a static activity longer than a pre-defined threshold followed by a postural transfer to sitting or lying.

11. The system of claim 4, wherein said one or more processor circuits are further programmed to identify frailty status by measuring slowness of movement as characterized by a duration or magnitude of acceleration, or a magnitude of velocity, during a postural transfer or a dynamic activity.

12. The system of claim 4, wherein said one or more processor circuits are further programmed to identify frailty status by measuring weakness as characterized by a standard deviation of a frontal or a vertical acceleration or a magnitude of speed during a dynamic activity.

13. The system of claim 1, wherein said one or more processor circuits are further programmed to identify frailty status by measuring exhaustion based on measurement of a rate of change and a total change in speed or acceleration of movement during cyclic activities, consecutive sit to stand postural transfers, or consecutive body joint flexions and extensions.

14. The system of claim 1, wherein said one or more processor circuits are further programmed to identify frailty status by measuring non-uniformity of step-to-step walking speed.

15. The system of claim 1, further comprising a sensor to measure heart rate or an electrocardiogram.

16. The system of claim 15, wherein said one or more processor circuits are further programmed to identify, confirm and define frailty status based on measuring one or more of a rate of change of heart rate or heart rate variability, and a magnitude of change in heart rate or heart rate variability during a transition from a static activity to a dynamic activity.

17. The system of claim 15, wherein said one or more processor circuits are further programmed to identify frailty status based on measuring one or more of a rate of change of heart rate, a magnitude of change in heart rate, and a change of heart rate variability during a transition from a dynamic activity to a static activity.

18. The system of claim 15, wherein said one or more processor circuits are further programmed to identify frailty status based on measuring a duration or a number or premature junctional contractions (PJC) episodes during a predefined time interval.

19. The system of claim 1, further comprising a sensor to measure respiration rate.

20. The system of claim 19, wherein said one or more processor circuits are further programmed to identify frailty status based on measuring one or more of a rate and magnitude of change in respiration rate from a static activity to a dynamic activity.

21. The system of claim 19, wherein said one or more processor circuits are further programmed to identify frailty status based on measuring one or more of a rate and magnitude of change in respiration rate from a dynamic activity to a static activity.

22. The system of claim 1, further comprising a sensor to measure audio.

23. The system of claim 22, wherein said one or more processor circuits are further programmed to identify whether the person is talking based on measuring one or more of a frequency of audio, a magnitude of audio, a change in upper body acceleration, or a change in respiration rate.

24. The system of claim 22, wherein said one or more processor circuits are further programmed to measure a difference in one or more of the following parameters of gait between when the person is talking and when the person is not talking:

speed, cadence, or step-to-step variation in step duration.

25. The system of claim 22, wherein said one or more processor circuits are further programmed to identify frailty status based said differences in one or more parameters of gait between when the user is talking and when the user is not talking.

26. The system of claim 1, wherein said one or more processor circuits are further programmed to measure body sway based on measurements of acceleration and speed during a standing posture.

27. The system of claim 26, wherein said one or more processor circuits are further programmed to identify frailty status by characterization of body sway during open-loop and closed-loop conditions.

28. The system of claim 26, wherein said one or more processor circuits are further programmed to identify open-loop and closed-loop conditions by measuring a body sway.

29. The system of claim 1, wherein said one or more processor circuits are further programmed to identify frailty status by a linear or non-linear combination of two or more parameters.

30. The system of claim 1, wherein the sensor is further configured to measure a vertical acceleration signal.

31. The method of claim 1, wherein the spontaneous daily physical activity is unsupervised activity.

32. An ambulatory method for categorizing frailty status of a person, comprising:

receiving one or more signals from an accelerometer, the accelerometer attached to an upper body of a person, the one or more signals including at least one acceleration signal in response to motion or movements of a person as a result of spontaneous daily activity, the signals measuring at least a frontal acceleration pattern; and

determining information about frailty status including at least a determination that classifies the person as non-frail, pre-frail, or frail, wherein the determining information is performed by the following steps;

determining a score for one or more frailty related biomarkers selected from the group consisting of;

flopping, cautious sitting, slowness, weakness, cognitive decline, cautious sit to walk, or exhaustion, the score determined based at least on the measured frontal acceleration pattern measured by the accelerometer, the score further determined based on identifying activities measured by the accelerometer as being dynamic or static;

determining a score for one or more physiological responses to the identified dynamic or static activities, the responses selected from the group consisting of;

heart rate, heart rate variability, respiration rate, or skin temperature, the determined score for one or more physiological responses to the identified dynamic or static activities based at least in part on abnormal physiological responses to the identified dynamic or static activities, and

using the determined score for the one or more frailty related biomarkers and the score for the one or more physiological responses to the identified dynamic or static activities to calculate an overall score, and from the overall score classifying the person into one of a plurality of predetermined classifications, the predetermined classifications including at least non-frail, pre-frail, or frail, wherein the classifying provides an early identification of early markers of frailty to allow early intervention and rehabilitation as compared to non-ambulatory systems that do not use signals resulting from spontaneous daily activity.

33. The method of claim 32, wherein the acceleration signal is a frontal acceleration signal, and further comprising identifying a sit to stand or stand to sit postural transfer based on identifying a dynamic pattern before or after a peak detected in the frontal acceleration pattern.

34. The method of claim 33, wherein the acceleration signal is a vertical acceleration signal, and further comprising identifying the dynamic and a static activity based on a standard deviation of a vertical or a frontal acceleration in a predefined interval, including a predefined interval before or after a postural transfer.

35. The method of claim 34, further comprising identifying frailty status by measuring weakness as characterized by a standard deviation of a frontal or a vertical acceleration or a magnitude of speed during a dynamic activity.

36. The method of claim 32, further comprising identifying frailty status by measuring exhaustion based on measurement of a rate of change and a total change in speed or acceleration of movement during cyclic activities, consecutive sit to stand postural transfers, or consecutive body joint flexions and extensions.

37. The method of claim 32, further comprising identifying frailty status by measuring non-uniformity of step-to-step walking speed.

38. The method of claim 32, further comprising identifying, confirming and defining frailty status based on measuring one or more of a rate of change of heart rate or heart rate variability, and a magnitude of change in heart rate or heart rate variability during a transition between a static activity and a dynamic activity.

39. The method of claim 32, further comprising identifying frailty status based on measuring one or more of a rate and magnitude of change in respiration rate between a static activity and a dynamic activity.