Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-gsr
A comprehensive collection of GSR-related resources, including libraries, datasets, tutorials, papers, and more, for researchers and developers in the Galvanic Skin Response field.
https://github.com/mintisan/awesome-gsr
- BIOBSS - axis acceleration (ACC).
- NeuroKit2
- eda-explorer
- cvxEDA
- Data Preprocessing- Sentiment Analysis of Electrodermal Activity Data for Personalized Interventions in Mental Health
- pyEDA - Source Python Library for Electrodermal Activity (Galvanic Skin Response) Analysis | [pdf](https://pdf.sciencedirectassets.com/280203/1-s2.0-S1877050921X00075/1-s2.0-S1877050921006438/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBsaCXVzLWVhc3QtMSJHMEUCIGEvAu4IUHnUUXV3R6KrYXZaaCwpRdj%2B0zNBxN%2F53swpAiEA6IDGBHGPFfidArVdWhLuD5dBTAYu8QJW1ogM%2BTgF7aAquwUIhP%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FARAFGgwwNTkwMDM1NDY4NjUiDAaxbKQusBegJzkydiqPBYI1GWqEYi%2BZBpxncVdXVojBYu70CndrhJ5IOPsXfk68d3FxqJZh%2FGuvRywDvSiflHJm1XlyvMtdYK0%2BsS4wU%2Fo0MTvwMCXmSarIsVYNqm6lNuIgC8Lja7UivY3xX6qoHk1M73sHK%2FY3L2d5SZ7RyWGc%2ByHqEYnfU3yn1jQk9OdA1ZYdRk%2Be5W9VabiH6mbZ40SAYxHqtIxYT9ewYNR1uUaT4yX%2F5JAzsAB%2FdKfRCywanWTXpZOBuuZ%2FgMOQcV4sAal90RpGk6HJEbIZiWODdKIRuHRwveffQkjiXBsaZp2eDzgfATPFb3SlzUYvd48fmsaqjXRmIVkJ3UbzN0o2WMooSKofeXs6mlrkoyGLPsHy3R2A3ex2IUXYqys%2Fbq3RVTX1RnLabE4CDzeSDMbJOJlNCEypurYbg34rYuUPkp49gAVT4MU90ujpQVY8WFJlcAdAKw0qwMWzMYqLESWZfFJRVgeO7l%2BYaa1NQgfIY%2FFdCZpY2vSKTtXU7bD9AymjFijXcsDgK8wnZtXAGl1amsk34LSUjULCg6KH9ckug9zFn6L%2F9TXFpGfKqsAPWcuUF7YyTQw07K0y5BRg1S1PYhWr51suWzpKph1z714RcRTmSaFaQiHjdtFGv6nN1HL8TZsDSui3dD4PVRVhKLJGAcl5VA9YXSYzaJNIohN0TApOD%2FeNe5BLdIZFSEnjGf%2B%2FntTUM2%2FPfQZYlZZZ0fS1cG2tm6mJ6cJDojuSmtz4AoBtyYXt%2FqKIWLRBA4s%2B0Z3VVBMG712Hf5vDwUG6ZcmeyPpoBt1P9sTeQ2%2FJ0SDkf%2BQebMdwRDlCb4f7uRW5G3Jowys11fHWSYzYsckvdKDS8gQJqlS%2BnHSvhwiUMrXiPyUwtMO%2FqwY6sQGTDW0y7NHBiJ9U6NlOKDf1d2heE3zyzm08nAV5J37sq0BFSXvxKWan%2FWGkJ7TaBM4eazpshie9%2BRyPUxxSnng2iOTtjVnBbnuqt%2FxZWu9Ro9OG%2FfRq7Itq7vdsi5SCMa9H6dOMN54qSjuIk9NZNCbbtNvwFBXqeeyK%2B5GWsV6tVbGMORbyB29i65gfYpONu7fujFsQmFbNaErkhSSXSsmbQoS%2FdE67iNo113wIHQ85Ox8%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20231206T035457Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTY3JLTWFO5%2F20231206%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=aca1b61d8384ee888418c2abcc703c355297165ad926dcdcc5556b14b4729942&hash=547ebeef9deaf044150ed13bc89a8a1a18ed2b75d1c9f3a485fc1e9f288c9f6a&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S1877050921006438&tid=spdf-a81a8431-182b-493f-9dd5-14ecc2f5e213&sid=02333f2d9ccc16405f8a822029972f24677agxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=10165f5c56545a52550202&rr=8311972badcc1a14&cc=jp)
- LEDALAB
- Ledalab
- Detecting stress during real-world driving tasks using physiological sensors - 2368
- A continuous measure of phasic electrodermal activity - 1582
- A stress sensor based on Galvanic Skin Response (GSR) controlled by ZigBee - 405
- Analysis of the quality of electrodermal activity and heart rate data recorded in daily life over a period of one week with an E4 wristband - 14
- A Guide for Analysing Electrodermal Activity (EDA) & Skin Conductance Responses (SCRs) for Psychological Experiments - 891
- EDA Positive Change: A Simple Algorithm for Electrodermal Activity to Measure General Audience Arousal During Media Exposure - 85
- cvxEDA: a Convex Optimization Approach to Electrodermal Activity Processing - 452 | [code](https://github.com/lciti/cvxEDA)
- Automatic Identification of Artifacts in Electrodermal Activity Data - 272 | [code](https://github.com/MITMediaLabAffectiveComputing/eda-explorer) | [code-EDArtifact](https://github.com/shkurtagashi/EDArtifact)
- Feature extraction of galvanic skin responses by nonnegative sparse deconvolution - 17 | [code](https://github.com/yskong224/SprasEDA-Python)
- Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data - 38 | [code](https://github.com/IdeasLabUT/EDA-Artifact-Detection)
- A wearable system for stress detection through physiological data analysis - 27
- Design and Implementation of an Ultra-Low Resource Electrodermal Activity Sensor for Wearable Applications - 23
- Wearables and location tracking technologies for mental-state sensing in outdoor environments - 86
- A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors - 97
- Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review - 227
- Validating Measures of Electrodermal Activity and Heart Rate Variability Derived From the Empatica E4 Utilized in Research Settings That Involve Interactive Dyadic States - 102
- Electrodermal activity - a beginner’s guide - 20
- Detection of Artifacts in Ambulatory Electrodermal Activity Data - 29
- A Preliminary Study on Automatic Motion Artifact Detection in Electrodermal Activity Data Using Machine Learning - 8
- Correlation Analysis of Different Measurement Places of Galvanic Skin Response in Test Groups Facing Pleasant and Unpleasant Stimuli - 19
- PREDICTING HUMAN STRESS EMOTIONS USING MACHINE LEARNING MODELS - driver-stress-using-deep-learning)
- Automatic motion artifact detection in electrodermal activity data using machine learning - 12
- Human Emotion Recognition Based On Galvanic Skin Response signal Feature Selection and SVM - 75
- Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance - 2
- Wearable Technologies for Electrodermal and Cardiac Activity Measurements: A Comparison between Fitbit Sense, Empatica E4 and Shimmer GSR3+ - 3
- A Method for Stress Detection Using Empatica E4 Bracelet and Machine-Learning Techniques
- Electrodermal Activity(2nd).pdf
- Handbook of Psychophysiology, Fourth Edition
- Galvanic Skin Response Devices The Ultimate Step-By-Step Guide
- All You Need To Know: Galvanic Skin Response (GSR)
- Galvanic Skin Response (GSR): The Complete Pocket Guide
- Tobii Galvanic skin response (GSR)
- Electrodermal Activity Data Collection
- Physiology of Auditory Attention (PhyAAt) - channel Emotiv Epoc device. Two signal streams of Galvanic Skin Response (GSR) were recorded, instantnious sample and moving averaged signal. From photoplethysmogram (PPG) sensor (pulse sensor), a raw signal, inter-beat interval (IBI), and pulse rate were recorded.
- ECG and GSR Data for Emotion Recognition during Covid-19 Epidemic
- Electrodermal Activity artifact correction BEnchmark (EDABE)
- Continuously Annotated Signals of Emotion (CASE) - paper](https://www.nature.com/articles/s41597-019-0209-0)
- WESAD (Wearable Stress and Affect Detection) - paper](https://arxiv.org/ftp/arxiv/papers/2005/2005.01834.pdf)
- DEAPdataset - paper](https://www.eecs.qmul.ac.uk/mmv/datasets/deap/doc/tac_special_issue_2011.pdf)-3904
- MAHNOB-HCI : A Multimodal Database for Affect Recognition and Implicit Tagging
- Stress Recognition in Automobile Drivers
- The SWELL Knowledge Work Dataset for Stress and User Modeling Research
- Creative Commons Attribution 4.0 International License
Programming Languages
Keywords
ecg
2
eda
2
hrv
2
ppg
2
signal-processing
2
acceleration
1
electrocardiography
1
electrodermal-activity
1
feature-extraction
1
galvanic-skin-response
1
heart-rate-variability
1
photoplethysmography
1
biosignals
1
cardiac
1
eeg
1
emg
1
entropy
1
eog
1
heart-rate
1
physiology
1
python
1
scr
1
signal
1
skin-conductance
1
software
1
tutorial
1
affective computing
1
continuous annotation
1
dataset
1
physiological signals
1