MEDICAL EVALUATION SYSTEM AND METHOD USING SENSORS IN MOBILE DEVICES

• US 20130041290A1
• Filed: 04/21/2011
• Published: 02/14/2013
• Est. Priority Date: 04/21/2010
• Status: Active Grant

• Current Assignee: Northwestern University, Rehabilitation Institute of Chicago (Tenet Healthcare Corporation)
• Original Assignee: Northwestern University, Rehabilitation Institute of Chicago (Tenet Healthcare Corporation)
• Inventors: Kording, Konrad, Albert, Mark, Levien, Andrew
• Granted Patent: US 9,872,637 B2
• Time in Patent Office: Days
• US Class Current: 600/595
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/1126 using a particular sensing technique
• CPC Class Codes: A61B 5/117 Identification of persons methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A medical evaluation system includes an I/O module, a processing module, and an analysis module. The I/O module receives sensory data obtained by a motion sensor disposed in a mobile device carried by a patient at least when the patient is in a non-clinical environment. The processing module extracts medically relevant data from the sensory data received from the sensor in the mobile device. The relevant data includes one or more features of interest in the sensory data. The analysis module derives one or more surrogate biomarkers from the relevant data. The surrogate biomarkers represent at least one of a state or a progression of a medical condition of the patient. The mobile device may be a mobile phone carried by the patient and the sensor may include at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.

Claims

1. A medical evaluation system comprising:

an input/output (I/O) module configured to receive sensory data obtained by a motion sensor disposed in a mobile device carried by a patient at least when the patient is in a non-clinical environment, wherein the sensory data represents motion of the patient;

a processing module configured to extract medically relevant data from the sensory data received from the sensor in the mobile device, the relevant data including one or more features of interest in the sensory data; and

an analysis module configured to derive one or more surrogate biomarkers from the relevant data, the surrogate biomarkers representative of at least one of a state of a medical condition or a progression of a medical condition of the patient.

2. The system of claim 1, wherein the mobile device is a mobile phone carried by the patient and the sensor includes at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.

3. The system of claim 1, wherein the analysis module is configured to employ one or more machine learning algorithms that identify one or more patterns or trends in the relevant data to derive the surrogate biomarkers.

4. The system of claim 1, wherein the surrogate biomarkers include an estimate of a quantitative clinical score in a medical ranking system.

5. The system of claim 4, wherein the one or more estimates of quantitative clinical scores include at least one of an indication of early onset or a probability of early onset of a disease of the patient.

6. The system of claim 1, further comprising an authentication module configured to determine one or more of the features of interest in the sensory data as the relevant data and use the relevant data to identify the patient carrying the mobile device.

7. The system of claim 1, wherein the analysis module is configured to transmit an intervention to the device based on one or more changes in the relevant data, the intervention including a notification communicated to the patient via the device to change a current activity of the patient.

8. The system of claim 1, wherein the medical condition includes at least one of Parkinson'"'"'s disease, spinal cord injury, multiple sclerosis, cerebral palsy, or cerebellar ataxia.

9. The system of claim 1, wherein the surrogate biomarker is representative of at least one of a degree of activity of the patient, gait of the patient, sway of the patient, tremor of the patient, deviation of the patient from steady behavior, recovery from perturbation, exercise, wheelchair management, and motorized transport use.

10. The system of claim 1, wherein the processing module is configured to evaluate a posture of the patient.

11. The system of claim 1, wherein the I/O module is configured to transmit a report including the surrogate biomarker to one or more of a healthcare provider, an insurance company, a family member of the patient, or a friend of the patient.

12. A method for monitoring a medical condition of a patient, the method comprising:

receiving sensory data obtained from a motion sensor in a mobile device carried by a patient in a non-clinical environment;

extracting the medically relevant data from the sensory data by identifying one or more features of interest in the sensory data; and

deriving the surrogate biomarker from the relevant data, wherein the surrogate biomarker represents at least one of a state or a progression of the medical condition of the patient.

13. The method of claim 12, wherein the mobile device is a mobile phone carried by the patient and the sensor includes at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.

14. The method of claim 12, wherein deriving the surrogate biomarker includes employing one or more machine learning algorithms that identify at least one pattern or trend in the relevant data to derive the surrogate biomarker.

15. The method of claim 12, wherein the surrogate biomarker includes at least one of an indication of early onset or a probability of early onset of a disease of the patient.

16. The method of claim 12, further comprising determining one or more of the features of interest in the sensory data as the relevant data and using the relevant data to identify the patient carrying the mobile device.

17. The method of claim 12, further comprising determining a location that the mobile device is carried by the patient based on a comparison between the relevant data and one or more location signatures associated with the patient, the location signatures including one or more of the features of interest of previously acquired sensory data from the sensor when the device is carried in different locations on the patient.

18. The method of claim 12, further comprising transmitting an intervention to the device based on one or more changes in the relevant data, the intervention including a notification communicated to the patient via the device to change a current activity of the patient.

19. The method of claim 12, wherein the medical condition includes at least one of Parkinson'"'"'s disease, spinal cord injury, multiple sclerosis, cerebral palsy, or cerebellar ataxia.

20. The method of claim 12, wherein the surrogate biomarker is representative of at least one of a degree of activity of the patient, gait of the patient, sway of the patient, tremor of the patient, deviation of the patient from steady behavior, recovery from perturbation, exercise, wheelchair management, and motorized transport use.

21. The method of claim 12, wherein the surrogate biomarker includes a posture of the patient.

22. A computer readable storage medium for a medical evaluation system having a processor, the computer readable storage medium including one or more sets of instructions that direct the processor to:

receive sensory data obtained by a motion sensor in a mobile device that is carried by a patient in a non-clinical environment;

extract medically relevant data from the sensory data by identifying one or more features of interest in the sensory data; and

derive a surrogate biomarker from the relevant data, wherein the surrogate biomarker represents of at least one of a disease state, an injury state, or a progression of a disease of the patient.

23. The computer readable storage medium of claim 22, wherein the mobile device is a mobile phone carried by the patient and the sensor includes at least one of an accelerometer or a gyroscope that generates the sensory data to represent movements of the patient.

24. The computer readable storage medium of claim 22, wherein the sets of instructions direct the processor to:

employ one or more machine learning algorithms that identify at least one of a pattern or a trend in the relevant data, and the surrogate biomarker is based on the at least one of the pattern or the trend.

25. The computer readable storage medium of claim 22, wherein the surrogate biomarker includes at least one of an indication of early onset or a probability of early onset of a disease of the patient.

26. The computer readable storage medium of claim 22, wherein the one or more sets of instructions direct the processor to determine one or more of the features of interest in the sensory data as the relevant data and identify the patient carrying the mobile device based on the features of interest.

27. The computer readable storage medium of claim 22, wherein the one or more sets of instructions direct the processor to determine a location that the mobile device is carried by the patient based on a comparison between the relevant data and one or more location signatures associated with the patient, the location signatures including one or more of the features of interest of previously acquired sensory data from the sensor when the device is carried in different locations on the patient.

28. The computer readable storage medium of claim 22, wherein the one or more sets of instructions direct the processor to transmit an intervention to the device based on one or more changes in the relevant data, the intervention including a notification communicated to the patient via the device to change a current activity of the patient.