ledalab matlab toolbox (MathWorks Inc)

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MathWorks Inc ledalab matlab toolbox
Ledalab Matlab Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2342 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab+ledalab+toolbox/Database+Toolbox/pmc12748724-227-7-8
Average 96 stars, based on 2342 article reviews

ledalab matlab toolbox - by Bioz Stars, 2026-11

96/100 stars

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Article Title: A New Perspective on Stress Detection: An Automated Approach for Detecting Eustress and Distress
Article Snippet: For EDA data, we utilized the MATLAB Ledalab toolbox [ 31 ], which provides various functions to clean and process EDA data.

Article Title: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding.
Article Snippet: 9Scientific Data | (2025) 12:1142 | https://doi.org/10.1038/s41597-025-05349-2 the Matlab Ledalab toolbox37 was used to extract the phasic and tonic components, known as skin conductance response (SCR) and skin conductance level (SCL).

Article Title: Predicting Office Workers' Productivity: A Machine Learning Approach Integrating Physiological, Behavioral, and Psychological Indicators.
Article Snippet: For processing the EDA signal, we employed the MATLAB Ledalab toolbox [39].

Article Title: Stress appraisal in the workplace and its associations with productivity and mood: Insights from a multimodal machine learning analysis.
Article Snippet: We used the MATLAB Ledalab toolbox [36] to clean and process the EDA data using a Butterworth low-pass filter, Hanning smoothing with a window size of 4 adjacent datapoints, and manual artifact correction to remove any noise that might have been caused by movement or other sources of interference.

Article Title: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding
Article Snippet: For GSR data, the Continuous Decomposition Analysis (CDA) in the Matlab Ledalab toolbox was used to extract the phasic and tonic components, known as skin conductance response (SCR) and skin conductance level (SCL).

Article Title: Stress appraisal in the workplace and its associations with productivity and mood: Insights from a multimodal machine learning analysis
Article Snippet: We used the MATLAB Ledalab toolbox [ ] to clean and process the EDA data using a Butterworth low-pass filter, Hanning smoothing with a window size of 4 adjacent datapoints, and manual artifact correction to remove any noise that might have been caused by movement or other sources of interference.

Article Title: Predicting Office Workers’ Productivity: A Machine Learning Approach Integrating Physiological, Behavioral, and Psychological Indicators
Article Snippet: For processing the EDA signal, we employed the MATLAB Ledalab toolbox [ ].

Article Title: Cognitive arousal-based measures quantify insights from self-ratings in response to sensory stimuli
Article Snippet: The dataset consisted of preprocessed skin conductance data: the raw skin conductance data was preprocessed using the MATLAB Ledalab toolbox, as outlined in [ ].

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ledalab matlab toolbox (MathWorks Inc)

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