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Babu et al., 2022 - Google Patents

Depression analysis using electroencephalography signals and machine learning algorithms

Babu et al., 2022

Document ID
1895768839462817450
Author
Babu N
Kanaga E
Publication year
Publication venue
2022 Third international conference on intelligent computing instrumentation and control technologies (ICICICT)

External Links

Snippet

Depression has been defined as a silent disease that affects everyone regardless of physical or biological state. More than 40% of the population is openly afflicted by the disease. Depression has become a troubling trend, affecting not just a person's …
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Classifications

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    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/726Details of waveform analysis characterised by using transforms using Wavelet transforms
    • AHUMAN NECESSITIES
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    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/7257Details of waveform analysis characterised by using transforms using Fourier transforms
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    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402Electrocardiography, i.e. ECG
    • A61B5/0452Detecting specific parameters of the electrocardiograph cycle
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    • A61B5/0476Electroencephalography
    • A61B5/0484Electroencephalography using evoked response
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