Computerized systems and methods for stability—theoretic prediction and prevention of falls
First Claim
1. Computer-readable media having computer-executable instructions embodied thereon that when executed, facilitate a method for automatically predicting life-threatening ventricular arrhythmias that are likely to result in sudden kinematic death (falling) in humans, the method comprising:
- obtaining motion signals representative of motion of an individual;
detecting the presence of instability (chaos or trajectory-divergence) of motion dispersion or other measurements in said signals;
determining, utilizing an objective function, a motion dispersion stability index (MdSI) from said signals based on one or a plurality of previous time intervals; and
determining a difference between the index and a reference value to classify the likelihood of events leading to falling within a future time interval,wherein a significant difference is indicative of an increased risk for falling.
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Abstract
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. Thus the aim of embodiments of the present invention relates to automatically identifying persons who are at risk for falls through the use of an inexpensive, noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital accelerometer and gyroscope timeseries acquired by the device. The measurements and predictive algorithms embedded within the device provide for unsupervised use in the home or in general acute-care and chronic-care venues and afford a degree of robustness against variations in individual anatomy and sensor placement. In some embodiments, the present invention provides a leading indicator of near-term future abnormalities, proactively alerting the user, for example, 2 hours or more in advance, and providing the wearer and/or care providers with sufficient advance notice to enable effective preventive maneuvers to be undertaken. In one exemplary embodiment, the device is equipped with radiofrequency telecommunication capabilities that enable integration with case-management software, electronic health record decision-support systems, and consumer personal health record systems.
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Citations
20 Claims
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1. Computer-readable media having computer-executable instructions embodied thereon that when executed, facilitate a method for automatically predicting life-threatening ventricular arrhythmias that are likely to result in sudden kinematic death (falling) in humans, the method comprising:
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obtaining motion signals representative of motion of an individual; detecting the presence of instability (chaos or trajectory-divergence) of motion dispersion or other measurements in said signals; determining, utilizing an objective function, a motion dispersion stability index (MdSI) from said signals based on one or a plurality of previous time intervals; and determining a difference between the index and a reference value to classify the likelihood of events leading to falling within a future time interval, wherein a significant difference is indicative of an increased risk for falling. - View Dependent Claims (2, 3, 4, 5, 20)
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6. 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:
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identifying translational or rotational kinematics from accelerometer or gyroscopic signals representative of movements of an individual; and determining a motion dispersion stability index based on the kinematics from one or a plurality of previous time intervals, for determining a likelihood of falling within a future time interval. - View Dependent Claims (7, 8, 9, 10, 11, 12)
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13. A method for automatically predicting sudden kinematic injury (falling) in humans the method comprising:
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obtaining motion signals representative of motion of an individual; determining, utilizing an objective function, a motion dispersion stability index (MdSI) from said signals based on one or a plurality of previous time intervals, to classify a likelihood of events leading to falling within a future time interval; and determining a difference between the index and a reference value, wherein a significant difference is indicative of an increased risk for falling. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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Specification