Integrate and fire pulse train automation for QRS detection
View Patent ↗Various examples are provided for automation of QRS detection. In one example, among others, a system includes an integrate and fire (IF) sampler that can generate an IF pulse train from an analog input signal, and decision logic circuitry that can determine whether a QRS complex waveform is present in a pulse segment of the IF pulse train. In another example, a method includes generating an integrate and fire (IF) pulse train from an analog input signal, identifying a pulse segment of the IF pulse train, and determining whether a QRS waveform is present in the pulse segment based at least in part upon attributes associated with the pulse segment.
1. A system for QRS complex waveform detection, comprising:
an integrate and fire (IF) sampler configured to generate an IF pulse train from an analog input signal; and
decision logic circuitry configured to:
identify a pulse segment based at least in part upon pulse polarities of the IF pulse train; and
determine whether a QRS complex waveform is present in the pulse segment of the IF pulse train.
2. The system of claim 1 , wherein the decision logic circuitry is configured to aggregate pulses of the IF pulse train into a plurality of pulse segments based at least in part upon the pulse polarities and an inter-pulse interval (IPI) between pulses in the plurality of pulse segments.
3. The system of claim 1 , wherein the decision logic circuitry is configured to extract attributes associated with the pulse segment of the IF pulse train, the attributes comprising at least one attribute based upon an inter-pulse interval (IPI) between pulses in the pulse segment.
4. The system of claim 3 , wherein the decision logic circuitry is configured to transform the attributes into logical values.
5. The system of claim 4 , wherein the decision logic circuitry is configured to determine the presence of the QRS complex waveform in the pulse segment based upon at least a portion of the logical values.
6. The system of claim 1 , wherein the presence of the QRS complex waveform in the pulse segment is determined using an automata based decision logic based upon attributes associated with the pulse segment.
7. The system of claim 6 , wherein the automata based decision logic is selected from a group consisting of morphological checking for positive waves, morphological checking for negative waves, physiological blanking and search back.
8. The system of claim 1 , comprising an analog front end configured to preprocess the analog input signal.
9. The system of claim 1 , wherein the decision logic circuitry is configured to determine whether the pulse segment is noisy.
10. A method for QRS complex waveform detection, comprising:
generating an integrate and fire (IF) pulse train from an analog input signal;
identifying a pulse segment of the IF pulse train; and
determining whether a QRS waveform is present in the pulse segment based at least in part upon attributes associated with the pulse segment, the attributes comprising at least one attribute based upon an inter-pulse interval (IPI) between pulses in the pulse segment.
11. The method of claim 10 , wherein identifying the pulse segment comprises aggregating pulses of the IF pulse train into a plurality of pulse segments based at least in part upon pulse polarities and inter-pulse intervals (IPI).
12. The method of claim 11 , wherein the aggregation is based upon pulses of the same polarity with an IPI that is less than a pre-determined value.
13. The method of claim 10 , wherein the presence of the QRS waveform in the pulse segment is determined based upon logical values corresponding to the attributes associated with the pulse segment.
14. The method of claim 10 , wherein the attributes are extracted from the pulse segment, the attributes comprising a minimum IPI value for the IPI in the pulse segment and a time corresponding to the minimum IPI value.
15. The method of claim 13 , wherein the presence of the QRS waveform is determined using one of a plurality of automata based decision logic based at least in part upon the logical values.
16. The method of claim 15 , wherein the automata based decision logic is selected from a group consisting of morphological checking for positive waves, morphological checking for negative waves, physiological blanking and search back.
17. The method of claim 15 , wherein the logical values comprise search and blank status.
18. The method of claim 10 , wherein determining whether the QRS waveform is present in the pulse segment comprises determining whether the pulse segment is noisy.
19. The method of claim 10 , wherein the analog signal is an electrocardiogram (ECG) signal.
20. The system of claim 3 , wherein the attributes comprise a minimum IPI value for the IPI in the pulse segment and a time corresponding to the minimum IPI value.