Detection of waveform artifact
First Claim
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1. A medical device system for monitoring a physiological signal in a patient and detecting artifact in the physiological signal, the system comprising:
- an implantable physiological sensor for sensing the physiological signal;
a display for displaying the physiological signal to enable an expert to classify individual waveforms of the physiological signal based on visual observation, the individual waveforms classified into at least two classes comprising an artifact class;
a user interface for receiving user input to establish the classification of each of the individual waveforms;
a memory for storing the user input classifications of the individual waveforms;
a processor configured to;
receive the implantable physiological sensor signal;
separate the signal into a plurality of individual waveforms;
extract a plurality of features from each individual waveform;
determine a distribution range for the plurality of features for each of the classes, andestablish waveform classification criteria in response to the determined distribution ranges; and
an implantable processor adapted to be coupled to an implantable physiological sensor, the implantable processor configured to;
acquire unknown waveforms from the implantable physiological sensor,extract the plurality of features from the unknown waveforms,classify the unknown waveforms according to the established waveform classification criteria, anddetect signal artifact in response to a waveform being classified in the artifact class, wherein the at least two classes further comprise an atypical class and a typical class, the implantable processor further configured to;
determine a percentage of the unknown waveforms classified as each of the artifact class, atypical class, and typical class;
compute a monitoring metric using the unknown waveforms; and
report the monitoring metric with the percentage of one of the artifact, atypical and typical classes to establish a confidence level of the reported metric.
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Abstract
An implantable medical device system including a physiological sensor detects signal artifact in a signal waveform acquired by the sensor. Features of individual waveforms in the sensor signal are extracted. Sample waveforms are classified by expert observation into at least two classes including an artifact class. A distribution range for each of the extracted features from the sample waveforms is determined for each of the classes. Waveform classification criteria are established in response to the determined distribution ranges.
20 Citations
13 Claims
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1. A medical device system for monitoring a physiological signal in a patient and detecting artifact in the physiological signal, the system comprising:
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an implantable physiological sensor for sensing the physiological signal; a display for displaying the physiological signal to enable an expert to classify individual waveforms of the physiological signal based on visual observation, the individual waveforms classified into at least two classes comprising an artifact class; a user interface for receiving user input to establish the classification of each of the individual waveforms; a memory for storing the user input classifications of the individual waveforms; a processor configured to; receive the implantable physiological sensor signal; separate the signal into a plurality of individual waveforms; extract a plurality of features from each individual waveform; determine a distribution range for the plurality of features for each of the classes, and establish waveform classification criteria in response to the determined distribution ranges; and an implantable processor adapted to be coupled to an implantable physiological sensor, the implantable processor configured to; acquire unknown waveforms from the implantable physiological sensor, extract the plurality of features from the unknown waveforms, classify the unknown waveforms according to the established waveform classification criteria, and detect signal artifact in response to a waveform being classified in the artifact class, wherein the at least two classes further comprise an atypical class and a typical class, the implantable processor further configured to; determine a percentage of the unknown waveforms classified as each of the artifact class, atypical class, and typical class; compute a monitoring metric using the unknown waveforms; and report the monitoring metric with the percentage of one of the artifact, atypical and typical classes to establish a confidence level of the reported metric. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A medical device system for monitoring a physiological signal in a patient and detecting artifact in the physiological signal, the system comprising:
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an implantable physiological sensor for sensing the physiological signal; a display for displaying the physiological signal to enable an expert to classify individual waveforms of the physiological signal based on visual observation, the individual waveforms classified into at least two classes comprising an artifact class; a user interface for receiving user input to establish the classification of each of the individual waveforms; a memory for storing the user input classifications of the individual waveforms; a processor configured to; receive the implantable physiological sensor signal; separate the signal into a plurality of individual waveforms; extract a plurality of features from each individual waveform; determine a distribution range for the plurality of features for each of the classes, and establish waveform classification criteria in response to the determined distribution ranges; and an implantable processor adapted to be coupled to an implantable physiological sensor, the implantable processor configured to; acquire unknown waveforms from the implantable physiological sensor, extract the plurality of features from the unknown waveforms, classify the unknown waveforms according to the established waveform classification criteria, and detect signal artifact in response to a waveform being classified in the artifact class, wherein the plurality of features extracted comprises a non-physiological feature of the waveform, the non-physiological feature used for classifying the unknown waveforms; and the implantable processor further configured to extract a physiological feature from an unknown waveform in response to the unknown waveform not being classified in the artifact class, and compute a metric as a function of the physiological feature for monitoring a physiological condition of a patient, and wherein the non-physiological feature comprises one of a notch amplitude, a notch width, and a notch area.
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13. A medical device system for monitoring a physiological signal in a patient and detecting artifact in the physiological signal, the system comprising:
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an implantable physiological sensor for sensing the physiological signal; a display for displaying the physiological signal to enable an expert to classify individual waveforms of the physiological signal based on visual observation, the individual waveforms classified into at least two classes comprising an artifact class; a user interface for receiving user input to establish the classification of each of the individual waveforms; a memory for storing the user input classifications of the individual waveforms; a processor configured to; receive the implantable physiological sensor signal; separate the signal into a plurality of individual waveforms; extract a plurality of features from each individual waveform; determine a distribution range for the plurality of features for each of the classes, and establish waveform classification criteria in response to the determined distribution ranges; and an implantable processor adapted to be coupled to an implantable physiological sensor, the implantable processor configured to; acquire unknown waveforms from the implantable physiological sensor, extract the plurality of features from the unknown waveforms, classify the unknown waveforms according to the established waveform classification criteria, and detect signal artifact in response to a waveform being classified in the artifact class, wherein the plurality of features extracted comprises a non-physiological feature of the waveform, the non-physiological feature used for classifying the unknown waveforms; and the implantable processor further configured to extract a physiological feature from an unknown waveform in response to the unknown waveform not being classified in the artifact class, and compute a metric as a function of the physiological feature for monitoring a physiological condition of a patient, and wherein extracting the non-physiological feature comprises dividing the waveform into a plurality of segments and searching within one of the plurality of segments for the non-physiological feature.
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Specification