Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"

Aleš Holobar (Author), Nina Murks (Author)

Abstract

This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.

Keywords

material za poučevanje;elektromiogrami;HybridNeuro;webinar;teaching materials;statistical models;regression analysis;motor unit identification;HDEMG;surface high density electromyogram;

Data

Language:	English
Year of publishing:	2024
Typology:	2.20 - Research Data
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	s. n.
UDC:	004.6
COBISS:	197835267
Views:	221
Downloads:	19
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary keywords:	material za poučevanje;elektromiogrami;
Type (COBISS):	Not categorized
Pages:	1 spletni vir (datoteka PDF obsega 4 str.))
ID:	23890429