Spindle Detector Sumo

Module name: SpindleDetectorSumo

Package: CEAMSModules 7.4.0

Version: 3.0.0

Overview

Class to detect spindles based on the SUMO deep learning algorithm

Inputs

Input

Format

Default

Description

signals

List of SignalModel

—
List of signal with dictionary of channels with SignalModel with
properties :
name: The name of the channel
samples: The samples of the signal
alias: The alias of the channel
sample_rate: The sample rate of the signal
start_time: The start time of the recording
montage_index: The index of the montage used for this signal
is_modified: Value caracterizing if the signal as been modify
from the original

event_group

String

—

List of Event group to filter separated by comma (discard too long, short)

event_name

String

—

List of Event name to filter separated by comma (discard too long, short)

Outputs

Output

Format

Description

events

Pandas DataFrame (columns=[‘group’,’name’,’start_sec’,’duration_sec’,’channels’])

Events list for spindle detections.

Usage in a process

  1. Open Dev Tools -> New process in Snooz.

  2. In the Module Library, find Spindle Detector Sumo under the Detectors category.

  3. Drag the module onto the process canvas.

  4. Connect the required inputs from upstream modules (or set values in the Settings tab).

  5. Connect outputs to downstream modules as needed.

  6. Double-click the module to configure parameters in the Settings tab.

  7. Run the process and inspect results in the Results tab.

Note

For general guidance on building processes with modules, see Explore examples.