An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements

Martin Karl Moser; Maximilian Ehrhart; Bernd Resch

doi:10.3390/s24165085

An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements

Martin Karl Moser, Maximilian Ehrhart, Bernd Resch

Geoinformatics

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	5085
Number of pages	15
Journal	Sensors
Volume	24
Issue number	16
DOIs	https://doi.org/10.3390/s24165085
Publication status	Published - 6 Aug 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

Deep Generative Ensemble
Lstm
Deep learning
explainable AI
Generative adversarial network
Integrated gradients
Physiological sensor data
Stress detection
Wearable sensors

Fields of Science and Technology Classification 2012

211 Other Technical Sciences
303 Health Sciences

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10.3390/s24165085

Cite this

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title = "An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements",

keywords = "Deep Generative Ensemble, Lstm, Deep learning, explainable AI, Generative adversarial network, Integrated gradients, Physiological sensor data, Stress detection, Wearable sensors",

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An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements

Bibliographical note

Keywords

Fields of Science and Technology Classification 2012

Access to Document

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