Research Article
CS-Based Decomposition of Acoustic Stimuli-Driven GSR Peaks Sensed by an IoT-Enabled Wearable Device
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@INPROCEEDINGS{10.1007/978-3-030-99197-5_14, author={Federico Casaccia and Grazia Iadarola and Angelica Poli and Susanna Spinsante}, title={CS-Based Decomposition of Acoustic Stimuli-Driven GSR Peaks Sensed by an IoT-Enabled Wearable Device}, proceedings={IoT Technologies for Health Care. 8th EAI International Conference, HealthyIoT 2021, Virtual Event, November 24-26, 2021, Proceedings}, proceedings_a={HEALTHYIOT}, year={2022}, month={3}, keywords={Galvanic Skin Response Compressed sensing IoT-Wearable device Acoustic stimuli}, doi={10.1007/978-3-030-99197-5_14} }- Federico Casaccia
Grazia Iadarola
Angelica Poli
Susanna Spinsante
Year: 2022
CS-Based Decomposition of Acoustic Stimuli-Driven GSR Peaks Sensed by an IoT-Enabled Wearable Device
HEALTHYIOT
Springer
DOI: 10.1007/978-3-030-99197-5_14
Abstract
The Galvanic Skin Response (GSR) signal, measured as the electrical conductance between a pair of electrodes placed over a person’s skin, consists of a tonic component superposed by a phasic component. In the GSR phasic component several peaks appear corresponding to specific events. Therefore, the information content of peaks is very useful in a wide range of applications. This work investigates the effectiveness of a decomposition-based Compressed Sensing (CS) approach for extraction of peaks from GSR signals acquired with an IoT-enabled wrist-worn device, during unpleasant sound stimulation. Then, once the sparse peaks are detected, the overall GSR phasic component is reconstructed, too.
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