Sleep Spindles as Biomarker for Early Detection of Neurodegenerative Disorders
First Claim
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1. A method for identifying a subject having an increased risk of developing a synucleinopathy comprising detection of sleep spindles.
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Abstract
The present invention relates to the use of sleep spindles as a novel biomarker for early diagnosis of synucleinopathies, in particular Parkinson'"'"'s disease (PD). The method is based on automatic detection of sleep spindles. The method may be combined with measurements of one or more further biomarkers derived from polysomnographic recordings.
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18 Claims
- 1. A method for identifying a subject having an increased risk of developing a synucleinopathy comprising detection of sleep spindles.
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18. A computer implemented method for detecting sleep spindles in one or more EEG derivations acquired from a sleeping subject, the method comprising
a) dividing each electroencephalographic (EEG) derivation into a plurality of time segments; -
b) processing each time segment by means of a matching pursuit algorithm, providing Gabor atoms and the energy density of each time segment; and c) calculating a plurality of predefined features for each time segment, said features selected from; energy features representing the energy density in each of a plurality of frequency bands, energy contribution features representing the energy contribution of at least one Gabor atom, preferably the first Gabor atom, in one or more of said frequency bands, a maximum energy feature representing the maximum energy point in the energy density, and the frequency corresponding to the maximum energy point in the energy density, and based on said features classifying each time segment as
1) comprising a sleep spindle or at least a part of a sleep spindles, or
2) a background signal.
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Specification