Data for: SPiQE: an automated analytical tool for detecting and characterising fasciculations in amyotrophic lateral sclerosis

Published: 26 April 2021| Version 1 | DOI: 10.17632/tnxt77tf9g.1
Contributor:
James Bashford

Description

Four files: 1. Mean noise bands and optimal amplitude inclusion thresholds for 599 one-minute recordings. 2. Sensitivity, specificity and classification accuracy scores for 80 one-minute recordings across multiple thresholds for each model (1 and 2). 3. Sensitivity, specificity and classification accuracy scores for 80 one-minute recordings for different thresholds of amplitude exclusion threshold 4. Comparison of manual and automated fasciculation counts using optimal model.

Files

Categories

Testing and Validation, Model Validation

Licence