Spindle Detection (A7)

Description

A spindle is “a train of distinct waves with frequency 11–16 Hz (most commonly 12–14 Hz) with a duration ≥0.5 s, usually maximal in amplitude using central derivations” [1]

This tool allows for the detection of spindles in specific sleep stages using the algorithms from (Lacourse et al. 2019) [2].

The spindle events detected are added into the accessory file (.tsv, .STS or .ent).

The event information is :

  • group : the group of the event.

  • name : the name of the event.

  • start_sec : the onset of the event in seconds (time elapsed from the lights off).

  • duration_sec : The duration of the event in seconds.

  • channels : The list of channels on which the events occurs.

Two additional output reports are available :

1. Spindle characteristics by event level

Files with the signal characteristic of each spindle event. One file per recording, one row per event.

The characteristics included are :

  • Duration (s)

  • Dominent frequency (Hz), where spectral energy is maximum

  • Average frequency (Hz) counting peaks

  • Peak-to-peak amplitude (µV)

  • Root Mean Square (rms) amplitude (µV)

2. Spindle characteristics averaged by subject level

A file with the spindle characteristics averaged per subject. One file for the cohort, one row per channel.

The characteristics included are :

  • spindle count

  • the average spindle characteristics listed above

    • total (all selected stages)

    • per sleep stage

    • per sleep cycle

See Spindle cohort report (A7) for the variable definition.

Steps

1 - Input Files

Start by opening your PSG files (.edf, .eeg or .sts).

  • The .tsv file is also needed for the EDF format.

  • The .sig file is also needed for Stellate format.

  • The whole NATUS subject folder is also needed for the .eeg format.

2 - Non valid events

Select events to disable the spindle detection.

Warning

Artefacts must be previously detected and saved in the accessory file.

3 - Spindle Detector

Define the minimum and maximum duration of kept spindles. Define in which sleep stage you want to detect spindles. You can also choose to detect spindle in the sleep cycles only or to exclude sleep periods from the analysis.

4 - Output Files

Select which reports to generate.

Report

References

[1] Iber, C., American Academy of Sleep Medicine, 2007. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. American Academy of Sleep Medicine.

[2] Lacourse, K., Delfrate, J., Beaudry, J., Peppard, P., Warby, S.C., 2019. A sleep spindle detection algorithm that emulates human expert spindle scoring. Journal of Neuroscience Methods 316, 3–11. https://doi.org/10.1016/j.jneumeth.2018.08.014