Hemodynamic risk severity based upon detection and quantification of cardiac dysrhythmia behavior using a pulse volume waveform
First Claim
1. A method for identifying a cardiac dysrhythmia condition, the method comprising:
- receiving, by a computing device, a biological signal emulating an arterial pulse wave from a sensor in data communication with a human body;
identifying, by the computing device, a plurality of signal peaks within the biological signal;
identifying, by the computing device, a peak amplitude for each of the plurality of signal peaks;
identifying, by the computing device, a time occurrence for each of the plurality of signal peaks;
calculating, by the computing device, a plurality of amplitude differences, wherein each amplitude difference of the plurality of amplitude differences is calculated from a first peak amplitude of a first peak and a second peak amplitude of a second peak;
calculating, by the computing device, a plurality of time differences, wherein each time difference of the plurality of time differences is calculated from a first time occurrence of the first peak and a second time occurrence of the second peak;
composing, with the computing device, a histogram reflective of at least the plurality of time differences, the histogram including at least one peak around a primary time difference of the plurality of time differences;
comparing, with the computing device, a plurality of amplitude differences with an amplitude threshold and a plurality of time differences with a time threshold to find at least one an anomalous amplitude difference that exceeds an amplitude threshold and at least one anomalous time difference that exceeds a time threshold;
determining at least one time difference dispersion metric associated with the time difference histogram, the time difference dispersion metric including at least one of a peak width of the primary time difference peak, a secondary time difference peak in addition to the primary time difference peak, or an asymmetric primary time difference peak; and
identifying a cardiac dysrhythmia condition based upon at least one of the time difference dispersion metrics associated with the time difference histogram during the occurrence of the at least one anomalous amplitude difference and the at least one anomalous time difference.
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Abstract
A method for identifying cardiac dysrhythmia behavior may include acquiring pulse volume wave data from a sensor associated with a patient, and calculating metrics associated with peaks detected therein. The metrics may include differences in amplitudes of successive pulse volume peaks and differences in the times of occurrence of successive pulse volume peaks. A dispersion analysis of the time differences, obtained during a defined time window, may result in one or more time difference dispersion metrics. Amplitude differences may be compared to an amplitude baseline, and time differences may be compared to a time baseline. Cardiac dysrhythmia behavior may be identified by a combination of an amplitude difference outside of the amplitude baseline, a corresponding time difference outside of the time baseline, and the values of one or more time difference dispersion metrics.
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Citations
30 Claims
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1. A method for identifying a cardiac dysrhythmia condition, the method comprising:
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receiving, by a computing device, a biological signal emulating an arterial pulse wave from a sensor in data communication with a human body; identifying, by the computing device, a plurality of signal peaks within the biological signal; identifying, by the computing device, a peak amplitude for each of the plurality of signal peaks; identifying, by the computing device, a time occurrence for each of the plurality of signal peaks; calculating, by the computing device, a plurality of amplitude differences, wherein each amplitude difference of the plurality of amplitude differences is calculated from a first peak amplitude of a first peak and a second peak amplitude of a second peak; calculating, by the computing device, a plurality of time differences, wherein each time difference of the plurality of time differences is calculated from a first time occurrence of the first peak and a second time occurrence of the second peak; composing, with the computing device, a histogram reflective of at least the plurality of time differences, the histogram including at least one peak around a primary time difference of the plurality of time differences; comparing, with the computing device, a plurality of amplitude differences with an amplitude threshold and a plurality of time differences with a time threshold to find at least one an anomalous amplitude difference that exceeds an amplitude threshold and at least one anomalous time difference that exceeds a time threshold; determining at least one time difference dispersion metric associated with the time difference histogram, the time difference dispersion metric including at least one of a peak width of the primary time difference peak, a secondary time difference peak in addition to the primary time difference peak, or an asymmetric primary time difference peak; and identifying a cardiac dysrhythmia condition based upon at least one of the time difference dispersion metrics associated with the time difference histogram during the occurrence of the at least one anomalous amplitude difference and the at least one anomalous time difference. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification