Yedukondala Rao Veeranki
Orcid: 0000-0002-7904-7543
According to our database1,
Yedukondala Rao Veeranki
authored at least 14 papers
between 2020 and 2024.
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Bibliography
2024
EDA-Graph: Graph Signal Processing of Electrodermal Activity for Emotional States Detection.
IEEE J. Biomed. Health Informatics, August, 2024
Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors.
Sensors, March, 2024
Recent Studies on Smart Textile-Based Wearable Sweat Sensors for Medical Monitoring: A Systematic Review.
J. Sens. Actuator Networks, 2024
Comparison of Electrodermal Activity Signal Decomposition Techniques for Emotion Recognition.
IEEE Access, 2024
Autoencoder Based Nonlinear Feature Extraction from EDA Signals for Emotion Recognition.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2024
Analyzing Emotional Dynamics: Transition Network Insights from Electrodermal Activity.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
Proceedings of the 20th IEEE International Conference on Body Sensor Networks, 2024
2022
Classification of Dichotomous Emotional States Using Electrodermal Activity Signals and Multispectral Analysis.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022
2021
Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network.
J. Medical Syst., 2021
A Systematic Review of Sensing and Differentiating Dichotomous Emotional States Using Audio-Visual Stimuli.
IEEE Access, 2021
Non-Parametric Classifiers Based Emotion Classification Using Electrodermal Activity and Modified Hjorth Features.
Proceedings of the Public Health and Informatics, 2021
2020
Convolutional neural network based emotion classification using electrodermal activity signals and time-frequency features.
Expert Syst. Appl., 2020