Seeking a new standard: a novel characterization of sleep spindles through time-frequency peak analysis

2017 ◽  
Vol 40 ◽  
pp. e268-e269
Author(s):  
P. Stokes ◽  
M. Prerau
Keyword(s):  
Sleep Spindles ◽  
Time Frequency ◽  
Frequency Peak

scholarly journals Multitaper Time-frequency Peak-based Longitudinal Sleep Analysis in 5XFAD Mouse Model

2021 ◽  
Author(s):  
Chaeyeon Kim ◽  
Victor James Drew ◽  
Mincheol Park ◽  
Tae Kim
Keyword(s):  
Sleep Disturbance ◽  
Dark Period ◽  
Sleep Spindles ◽  
Sleep Research ◽  
Time Frequency ◽  
Sleep Analysis ◽  
Frequency Peak ◽  
5Xfad Mouse ◽  
Novel Method ◽  
5Xfad Mice

Abstract Background: Sleep disturbance is common in Alzheimer’s disease (AD), but the characteristics of sleep disturbance remain unclear. Multitaper spectral analysis (MSA) is a novel method for investigating sleep. However, MSA-based sleep research in AD is lacking; hence we applied MSA to examine the sleep of AD.Methods: Electroencephalograms were recorded on 3-, 6-, and 10-month-old 5XFAD mice, and the time-frequency (TF) peaks were detected using MSA. We comparatively analyzed the TF peaks between genotypes and age groups.Results: The sigma TF peaks (~80%) were sleep spindles. MSA-based TF plot showed distinct patterns, agreeing with manual scoring. With AD progression, the characteristics of TF peaks coherently changed; shorter sigma TF peaks outnumbered longer ones; dark-period fast spindle TF peak density decreased significantly at both 6 and 10 months.Conclusions: Multitaper TF peaks might provide biomarkers for the progression of AD. Further investigations are warranted.

Suppression of strong random noise in seismic data by using time-frequency peak filtering

2013 ◽  
Vol 56 (7) ◽  
pp. 1200-1208 ◽  
Author(s):  
Yue Li ◽  
BaoJun Yang ◽  
HongBo Lin ◽  
HaiTao Ma ◽  
PengFei Nie
Keyword(s):  
Seismic Data ◽  
Random Noise ◽  
Time Frequency ◽  
Frequency Peak

scholarly journals Combining time-frequency and spatial information for the detection of sleep spindles

2015 ◽  
Vol 9 ◽  
Author(s):  
Christian O'Reilly ◽  
Jonathan Godbout ◽  
Julie Carrier ◽  
Jean-Marc Lina
Keyword(s):  
Spatial Information ◽  
Sleep Spindles ◽  
Time Frequency

scholarly journals Detection and Characterization of Meteotsunamis in the Gulf of Genoa

2019 ◽  
Vol 7 (8) ◽  
pp. 275 ◽  
Author(s):  
Picco ◽  
Schiano ◽  
Incardone ◽  
Repetti ◽  
Demarte ◽  
...  
Keyword(s):  
Sea Level ◽  
Atmospheric Pressure ◽  
Tidal Elevation ◽  
Port Management ◽  
Time Frequency ◽  
Abrupt Jump ◽  
Level Data ◽  
Work Planning

A long-term time series of high-frequency sampled sea-level data collected in the port of Genoa were analyzed to detect the occurrence of meteotsunami events and to characterize them. Time-frequency analysis showed well-developed energy peaks on a 26–30 minute band, which are an almost permanent feature in the analyzed signal. The amplitude of these waves is generally few centimeters but, in some cases, they can reach values comparable or even greater than the local tidal elevation. In the perspective of sea-level rise, their assessment can be relevant for sound coastal work planning and port management. Events having the highest energy were selected for detailed analysis and the main features were identified and characterized by means of wavelet transform. The most important one occurred on 14 October 2016, when the oscillations, generated by an abrupt jump in the atmospheric pressure, achieved a maximum wave height of 50 cm and lasted for about three hours.

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