Using deep convolutional neural network for emotion detection on a physiological signals dataset (AMIGOS)
Recommender systems have been based on context and content, and now the
technological challenge of making personalized recommendations based on the user …
technological challenge of making personalized recommendations based on the user …
Machine learning and end-to-end deep learning for the detection of chronic heart failure from heart sounds
Chronic heart failure (CHF) affects over 26 million of people worldwide, and its incidence is
increasing by 2% annually. Despite the significant burden that CHF poses and despite the …
increasing by 2% annually. Despite the significant burden that CHF poses and despite the …
Unsupervised multi-modal representation learning for affective computing with multi-corpus wearable data
There has been a growing focus on the use of artificial intelligence and machine learning for
affective computing to further enhance user experience through emotion recognition …
affective computing to further enhance user experience through emotion recognition …
A convolution neural network based emotion recognition system using multimodal physiological signals
CJ Yang, N Fahier, WC Li… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The detection and recognition of human emotional states have raised recent research
interests for various applications from e-learning to chronic health conditions prevention. In …
interests for various applications from e-learning to chronic health conditions prevention. In …
Calibrating the classifier: Siamese neural network architecture for end-to-end arousal recognition from ECG
Affective analysis of physiological signals enables emotion recognition in mobile wearable
devices. In this paper, we present a deep learning framework for arousal recognition from …
devices. In this paper, we present a deep learning framework for arousal recognition from …
Biosignal-based user-independent recognition of emotion and personality with importance weighting
For modeling human intelligence, understanding emotional intelligence as well as verbal
and mathematical intelligence is an important and challenging issue. In affective and …
and mathematical intelligence is an important and challenging issue. In affective and …
Emotion Detection and Classification Using Machine Learning Techniques
This chapter analyzes 57 articles published from 2012 on emotion classification using bio
signals such as ECG and GSR. This study would be valuable for future researchers to gain …
signals such as ECG and GSR. This study would be valuable for future researchers to gain …
Using Mobile Data and Deep Models to Assess Auditory Verbal Hallucinations
Hallucination is an apparent perception in the absence of real external sensory stimuli. An
auditory hallucination is a perception of hearing sounds that are not real. A common form of …
auditory hallucination is a perception of hearing sounds that are not real. A common form of …
Emotion classification using physiological signals: A recent survey
The diverse forms of emotions practiced by human beings such as happiness, sadness,
anger, fear point to the state of mental, and social welfare of an individual. The sentiments …
anger, fear point to the state of mental, and social welfare of an individual. The sentiments …
A heart rate driven kalman filter for continuous arousal trend monitoring
This paper proposes a continuous and unsupervised approach of monitoring the arousal
trend of an individual from his heart rate using Kalman Filter. The state-space model of the …
trend of an individual from his heart rate using Kalman Filter. The state-space model of the …