Dataset Information

EDA-gram: designing electrodermal activity fingerprints for visualization and feature extraction.

ABSTRACT: Wearable technology permeates every aspect of our daily life increasing the need of reliable and interpretable models for processing the large amount of biomedical data. We propose the EDA-Gram, a multidimensional fingerprint of the electrodermal activity (EDA) signal, inspired by the widely-used notion of spectrogram. The EDA-Gram is based on the sparse decomposition of EDA from a knowledge-driven set of dictionary atoms. The time axis reflects the analysis frames, the spectral dimension depicts the width of selected dictionary atoms, while intensity values are computed from the atom coefficients. In this way, EDA-Gram incorporates the amplitude and shape of Skin Conductance Responses (SCR), which comprise an essential part of the signal. EDA-Gram is further used as a foundation for signal-specific feature design. Our results indicate that the proposed representation can accentuate fine-grain signal fluctuations, which might not always be apparent through simple visual inspection. Statistical analysis and classification/regression experiments further suggest that the derived features can differentiate between multiple arousal levels and stress-eliciting environments for two datasets.

SUBMITTER: Chaspari T

PROVIDER: S-EPMC7285921 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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EDA-gram: designing electrodermal activity fingerprints for visualization and feature extraction.

Chaspari Theodora T Tsiartas Andreas A Stein Duker Leah I LI Cermak Sharon A SA Narayanan Shrikanth S SS

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 20160801

Wearable technology permeates every aspect of our daily life increasing the need of reliable and interpretable models for processing the large amount of biomedical data. We propose the EDA-Gram, a multidimensional fingerprint of the electrodermal activity (EDA) signal, inspired by the widely-used notion of spectrogram. The EDA-Gram is based on the sparse decomposition of EDA from a knowledge-driven set of dictionary atoms. The time axis reflects the analysis frames, the spectral dimension depict ...[more]

PMID: 28268358

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Dataset Information

EDA-gram: designing electrodermal activity fingerprints for visualization and feature extraction.

Publications

EDA-gram: designing electrodermal activity fingerprints for visualization and feature extraction.

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