Processing for multi-channel signals
First Claim
1. A method for detecting anomalies in a multi-channel signal, the method comprising:
- sampling the multi-channel signal over a time window, said multi-channel signal representing physiological signals derived from outputs of a plurality of electrodes positioned to acquire physiological signals from a patient, wherein each channel of the multi-channel signal corresponds to a different one of the plurality of electrodes;
computing with a processor an anomaly metric for the multi-channel signal over the time window, wherein said computing an anomaly metric comprises;
computing a condition number of the multi-channel signal over the time window; and
adiusting the condition number based on a parameter of the multi-channel signal to generate a data condition number (DCN); and
identifying the presence of an anomaly based on a magnitude of the anomaly metric, wherein said identifying the presence of an anomaly comprises comparing the magnitude of the DCN to at least one threshold.
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Abstract
Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.
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Citations
44 Claims
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1. A method for detecting anomalies in a multi-channel signal, the method comprising:
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sampling the multi-channel signal over a time window, said multi-channel signal representing physiological signals derived from outputs of a plurality of electrodes positioned to acquire physiological signals from a patient, wherein each channel of the multi-channel signal corresponds to a different one of the plurality of electrodes; computing with a processor an anomaly metric for the multi-channel signal over the time window, wherein said computing an anomaly metric comprises; computing a condition number of the multi-channel signal over the time window; and adiusting the condition number based on a parameter of the multi-channel signal to generate a data condition number (DCN); and identifying the presence of an anomaly based on a magnitude of the anomaly metric, wherein said identifying the presence of an anomaly comprises comparing the magnitude of the DCN to at least one threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. An apparatus for processing a multi-channel signal, the apparatus comprising:
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an anomaly metric computation module configured to compute with a computer an anomaly metric for the multi-channel signal over a time window, said multi-channel signal representing physiological signals derived from outputs of a plurality of electrodes positioned to acquire physiological signals from a patient, wherein each channel of the multi-channel signal corresponds to a different one of the plurality of electrodes, wherein the anomaly metric computation module is further configured to; compute the anomaly metric by computing a condition number of the multi-channel signal over the time window; and adjust the condition number by a parameter of the multi-channel signal to generate a data condition number (DCN); and an anomaly identification module configured to identify the presence of an anomaly in the multi-channel signal based on a magnitude of the anomaly metric, wherein the anomaly identification module is further configured to identify the presence of the anomaly by comparing the magnitude of the DCN to at least one threshold. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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35. An apparatus for processing a multi-channel signal, the apparatus comprising:
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means for sampling the multi-channel signal over a time window; means for computing with a computer an anomaly metric for the multi-channel signal over the time window; and means for identifying the presence of an anomaly based on the magnitude of the anomaly metric. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42, 43, 44)
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Specification