Computerized Systems and Methods for Stability-Theoretic Prediction and Prevention of Falls

• US 20140100487A1
• Filed: 09/09/2013
• Published: 04/10/2014
• Est. Priority Date: 12/31/2009
• Status: Abandoned Application

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: McNair, Douglas S.
• Application Number:
  US14/021,321
• Publication Number:
  US 20140100487A1
• Time in Patent Office: Days
• US Class Current: 600/595
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/6891 Furniture
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• 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 5/7267 involving training the classification device
• 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: 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 5/7405 using sound
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• 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
• CPC Class Codes: A61B 5/747 in case of emergency, i.e. alerting emergency services
• 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
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A system, methods, A system, methods and computer-readable media are provided for the automatic identification of patients according to near-term risk of sudden kinematic injury (falling). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent falling in humans, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support.

Claims

1. Computer-readable media having computer-executable instructions embodied thereon that when executed, facilitate a method for predicting a sudden kinematic event (falling) in humans, the method comprising:

receiving motion information representative of motion of an individual;

determining a level of instability of motion dispersion or other measurements based on the motion information; and

determining that the individual has an increased risk for falling based on the determined level of instability of motion dispersion or other measurements;

wherein the motion information comprises information about the individual'"'"'s motion over one or a plurality of previous time intervals.

2. The computer-readable media of claim 1, wherein determining the level of instability involves detecting the presence of chaos or trajectory divergence instability.

3. The computer-readable media of claim 1, wherein determining a level of instability of motion dispersion or other measurements comprises determining a motion dispersion stability index (MdSI) based on the received motion information.

4. The computer-readable media of claim 3, wherein the motion dispersion stability index (MdSI) is determined utilizing an objective function.

5. The computer-readable media of claim 4, wherein the objective function evaluates digitized kinematic waveforms from the one or a plurality of previous time intervals to classify the likelihood of a cascade of events leading to falling within a future time interval.

6. The computer-readable media of claim 4, wherein the objective function comprises a timeseries calculated from serially-acquired waveform data embodying the Lyapunov exponent.

7. The computer-readable media of claim 4, wherein the results of the objective function are used by a decision-support algorithm to determine a quantitative risk for falling.

8. The computer-readable media of claim 1, wherein the motion information is received at a mobile communication device carried by the individual.

9. A method to prevent injury from a sudden kinematic event (falling) in a population of humans, the method comprising providing an electronic notification to a caregiver of a member of the population, or a member of the population, who exhibits an above-reference value of a predicted risk for falling calculated from a timeseries of motion information acquired from the member over one or a plurality of previous time intervals.

10. The method of claim 9 wherein the motion information comprises translational or rotational kinematics from accelerometer or gyroscopic signals representative of movements of an individual.

11. The method of claim 9 wherein the electronic notification comprises a visual display, audible alarm, call, email, http, SMS text-message, or other form of radiofrequency communication, that the user has an increased likelihood of a near-term future abnormality or fall occurrence.

12. The method of claim 9 wherein the reference value is determined based on parameters associated with the individual including at least one or age, mobility, and falling history.

13. The method of claim 9 wherein the predicted risk for falling calculation involves utilizing an objective function for evaluating digitized kinematic waveforms from the one or a plurality of previous time intervals to classify the likelihood of a cascade of events leading to falling within a future time interval.

14. The method of claim 9 wherein the predicted risk for falling calculation involves utilizing an objective function comprising a timeseries calculated from serially-acquired waveform data embodying a Lyapunov exponent.

15. The method of claim 14, wherein the results of the objective function are used by a decision-support algorithm to determine a quantitative risk for falling.

16. Computer-readable media having computer-executable instructions embodied thereon that when executed, facilitate a method for determining a motion dispersion stability index for an individual, the method comprising:

identifying translational or rotational kinematics from accelerometer or gyroscopic signals representative of movements of an individual; and

determining a level of motion dispersion instability based on the kinematics from one or a plurality of previous time intervals, for determining a likelihood of falling within a future time interval.

17. The computer-readable media of claim 16, wherein the accelerometer or gyroscopic signals are derived from a mobile communication device carried by the individual.

18. The computer-readable media of claim 16, wherein determining the level of motion dispersion instability involves calculating and storing Lyapunov exponents.

19. The computer-readable media of claim 16, further comprising determining that the level of motion dispersion instability exceeds a reference value, and based on the determination, providing an electronic notification that the individual has an increased risk for falling.

20. The computer-readable media of claim 19 wherein the reference value is determined based on parameters associated with the individual including at least one or age, mobility, and falling history, and wherein the electronic notification comprises a call, email, http, or SMS text-message, visual display, or audible alarm.