The suitability of the Galvanic Skin Response (GSR) as a measure of emotions and the possibility of using the scapula as an alternative recording site of GSR

Eesee, Abdulrahman K.

doi:10.1109/iceccpce46549.2019.203752

Cited by 6 publications

(7 citation statements)

References 10 publications

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“…The results were taken by displaying groups of images to monitor feelings (sad, happy, neutral). This paper confirmed that using images only as a trigger for emotion monitoring was not a satisfactory result [ 2 ]. S. Karanchery and S. Palaniswamy found a way to help people with autism spectrum disorders communicate their emotions to healthcare providers.…”

Section: Introductionsupporting

confidence: 68%

New Method to Implement and Analysis of Medical System in Real Time

et al. 2022

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The use of information technology and technological medical devices has contributed significantly to the transformation of healthcare. Despite that, many problems have arisen in diagnosing or predicting diseases, either as a result of human errors or lack of accuracy of measurements. Therefore, this paper aims to provide an integrated health monitoring system to measure vital parameters and diagnose or predict disease. Through this work, the percentage of various gases in the blood through breathing is determined, vital parameters are measured and their effect on feelings is analyzed. A supervised learning model is configured to predict and diagnose based on biometric measurements. All results were compared with the results of the Omron device as a reference device. The results proved that the proposed design overcame many problems as it contributed to expanding the database of vital parameters and providing analysis on the effect of emotions on vital indicators. The accuracy of the measurements also reached 98.8% and the accuracy of diagnosing COVID-19 was 64%. The work also presents a user interface model for clinicians as well as for smartphones using the Internet of things.

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Section: Introductionsupporting

confidence: 68%

New Method to Implement and Analysis of Medical System in Real Time

et al. 2022

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“…The (1) depicts the connection between the voltage flowing through the resistance of the human body (Va) and the input voltage (Vi). The connection between the output voltage (Vo) and the reference voltage (Vref) is depicted in (2). Table 4 demonstrates how the resistance value (R6) and voltage values (Va) and (Vo) alter depending on the person's emotional state.…”

Section: Effect Of Emotions On Gsr Measurementsmentioning

confidence: 99%

“…The researchers also confirmed that the system can be used in remote places that are difficult for doctors to reach due to its portable design. Eesee [2] conducted a galvanic skin response (GSR) study to monitor the agitation and tension of a group of volunteers and analyze the GSR signal while performing a walking exercise on the treadmill. The results and statistical analyzes showed that using pictures only as an emotional stimulus did not give the desired results [2].…”

Section: Introductionmentioning

confidence: 99%

“…Eesee [2] conducted a galvanic skin response (GSR) study to monitor the agitation and tension of a group of volunteers and analyze the GSR signal while performing a walking exercise on the treadmill. The results and statistical analyzes showed that using pictures only as an emotional stimulus did not give the desired results [2]. Karanchery and Palaniswamy [3] have worked to provide a solution using machine learning technology to help healthcare providers deal with individuals with autism spectrum disorders.…”

Section: Introductionmentioning

confidence: 99%

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New methodology to detect the effects of emotions on different biometrics in real time

Elgawad

Youssef²,

Nasser

2023

IJECE

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<span lang="EN-US">Recently, some problems have appeared among medical workers during the diagnosis of some diseases due to human errors or the lack of sufficient information for the diagnosis. In medical diagnosis, doctors always resort to separating human emotions and their impact on vital parameters. In this paper, a methodology is presented to measure vital parameters more accurately while studying the effect of different human emotions on vital signs. Two designs were implemented based on the microcontroller and National Instruments (NI) myRIO. Measurements of four different vital parameters are measured and recorded in real time. At the same time, the effects of different emotions on those vital parameters are recorded and stored for use in analysis and early diagnosis. The results proved that the proposed methodology can contribute to the prediction and diagnosis of the initial symptoms of some diseases such as the seventh nerve and Parkinson’s disease. The two proposed designs are compared with the reference device (beurer) results. The design using NI myRIO achieved more accurate results and a response time of 1.4 seconds for real-time measurements compared to its counterpart based on microcontrollers, which qualifies it to work in intensive care units.</span>

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“…GSR monitors emotions and stress due to the change of sweat glands activities; compared with EEG and fMRI, GSR does not require bulky instruments and only needs sensors to be placed on the hands or feet. Nevertheless, even mild exercise can significantly alter the GSR signal and make it unreliable for driver emotion recognition, since drivers frequently move their hands and feet while controlling a vehicle [6,7]. External response requires simple instruments to collect.…”

Section: Introductionmentioning

confidence: 99%

On-Road Driver Emotion Recognition Using Facial Expression

Xiao

Zeng

et al. 2022

Applied Sciences

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With the development of intelligent automotive human-machine systems, driver emotion detection and recognition has become an emerging research topic. Facial expression-based emotion recognition approaches have achieved outstanding results on laboratory-controlled data. However, these studies cannot represent the environment of real driving situations. In order to address this, this paper proposes a facial expression-based on-road driver emotion recognition network called FERDERnet. This method divides the on-road driver facial expression recognition task into three modules: a face detection module that detects the driver’s face, an augmentation-based resampling module that performs data augmentation and resampling, and an emotion recognition module that adopts a deep convolutional neural network pre-trained on FER and CK+ datasets and then fine-tuned as a backbone for driver emotion recognition. This method adopts five different backbone networks as well as an ensemble method. Furthermore, to evaluate the proposed method, this paper collected an on-road driver facial expression dataset, which contains various road scenarios and the corresponding driver’s facial expression during the driving task. Experiments were performed on the on-road driver facial expression dataset that this paper collected. Based on efficiency and accuracy, the proposed FERDERnet with Xception backbone was effective in identifying on-road driver facial expressions and obtained superior performance compared to the baseline networks and some state-of-the-art networks.

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The suitability of the Galvanic Skin Response (GSR) as a measure of emotions and the possibility of using the scapula as an alternative recording site of GSR

Cited by 6 publications

References 10 publications

New Method to Implement and Analysis of Medical System in Real Time

New Method to Implement and Analysis of Medical System in Real Time

New methodology to detect the effects of emotions on different biometrics in real time

On-Road Driver Emotion Recognition Using Facial Expression

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