Proceedings Article10.1109/icoei56765.2023.10125696
Design and Implementation of Selection Algorithm based Human Emotion Recognition System
11 Apr 2023
3
TL;DR: In this paper , a real-time panic alarm is activated if the emotion exceeds a particular threshold, which sends the message to the concerned user with the live location using a Global Positioning System (GPS).
read more
Abstract: In recent years, many research solutions offered to recognize human emotional states automatically. As per the report of the world healthcare organization, people fell unfortunately on the road and could not provide first aid on time, resulting in death. The proposed research design overcomes the emergency of emotion management system with the help of physiological sensors. The physiological sensors, such as Galvanic Skin Response (GSR) and Blood Volume Pressure (BVP) are used to identify emotion signals. Initially, the ESP32 controller captures the signal from GSR and BVP. Later, it will be converted into a digital data format. These collected sensor data are analyzed using the proposed selection algorithm and web dashboards for real-time emotion detection. The panic alarm is altered in a real-time scenario if the emotion exceeds a particular threshold. It sends the message to the concerned user with the live location using a Global Positioning System (GPS). Experimental results outperform with improved accuracy and less dependability by using physiological signals to measure indirect emotions in complex situations.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Low-cost monitoring for stimulus detection in skin conductance
TL;DR: The paper shows that, despite the simpler design and hardware limitations exhibited by the low-cost system, the collected SC signals provide the same relevant information for stimulus detection of the SC signals acquired by a much more expensive acquisition board.
5
A Unified Approach for Detection of Children Emotion, Physiological and Security Using IoT
Imran Hussain S,A. B.,Harshad K +2 more
- 14 Dec 2023
TL;DR: The inclusion of quantitative measures strengthens the study's contribution to child security, providing concrete evidence of the system's efficacy in safeguarding children from both environmental hazards and unethical behavior.
Hybrid Transfer Learning Approach for Emotion Analysis of Occluded Facial Expressions
Dilshan Pamod,Joseph Charles,Ashen Iranga Hewarathna,Palanisamy Vigneshwaran,Sugeeswari Lekamge,Selvarajah Thuseethan +5 more
TL;DR: This study explores the effectiveness of deep learning models in occluded facial emotion analysis using a transfer learning approach, comparing individual pre-trained models (MobileNetV2 and EfficientNetB3) with a hybrid model, achieving 93.04% accuracy on partially obscured faces.
References
DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices
Stamos Katsigiannis,Naeem Ramzan +1 more
TL;DR: DREAMER, a multimodal database consisting of electroencephalogram (EEG) and ECG) signals recorded during affect elicitation by means of audio-visual stimuli, indicates the prospects of using low-cost devices for affect recognition applications.
867
A Review of Emotion Recognition Using Physiological Signals
TL;DR: A comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods, the published emotional physiological datasets, features, classifiers, and the whole framework for emotion recognition based on the physiological signals is presented.
775
Human Emotion Recognition: Review of Sensors and Methods.
TL;DR: This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity and proposes their classification.
479
Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges.
TL;DR: This survey paper presents a review on emotion recognition using eye- tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-track data, and a categorical summary and taxonomy of the current literature which relates to emotion recognition Using eye- Tracking.
207
An accurate emotion recognition system using ECG and GSR signals and matching pursuit method.
TL;DR: An accurate emotion recognition system was proposed using MP algorithm and wavelet dictionaries and the highest recognition rate of 100% was achieved for sigma = 0.01 in all classification schemes.
175