Novel expert system to study human stress based on thermographic images

Resendiz-Ochoa, Emmanuel; Cruz-Albarran, Irving A.; Garduño-Ramón, Marco Antonio; Rodríguez-Medina, David Alberto; Osornio-Ríos, Roque Alfredo; Morales-Hernandez, Luis A.

doi:10.1016/j.eswa.2021.115024

Cited by 15 publications

(10 citation statements)

References 54 publications

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“…For example, the thermal variation of the nose tip has been used to discriminate stimuli with positive and negative valence [ 24 ], as well as in response to startling stimulus [ 25 ], but also to fear or stress [ 26 , 27 , 28 , 29 ]. Furthermore, thermal features from several facial regions have been used for statistical comparisons among different psychological states [ 1 , 30 ], and to classify emotional states [ 31 , 32 ]. In the stress-assessment context, stress elicited by the Stroop test was observed to induce an enhancement of blood flow in the forehead, supraorbital and frontal vessels, as indicated by different slopes of the blood volume signal obtained from the thermograms in baseline and stress condition [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Towards a Contactless Stress Classification Using Thermal Imaging

Gioia

Greco

Callara

et al. 2022

Sensors

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Thermal cameras capture the infrared radiation emitted from a body in a contactless manner and can provide an indirect estimation of the autonomic nervous system (ANS) dynamics through the regulation of the skin temperature. This study investigates the contribution given by thermal imaging for an effective automatic stress detection with the perspective of a contactless stress recognition system. To this aim, we recorded both ANS correlates (cardiac, electrodermal, and respiratory activity) and thermal images from 25 volunteers under acute stress induced by the Stroop test. We conducted a statistical analysis on the features extracted from each signal, and we implemented subject-independent classifications based on the support vector machine model with an embedded recursive feature elimination algorithm. Particularly, we trained three classifiers using different feature sets: the full set of features, only those derived from the peripheral autonomic correlates, and only those derived from the thermal images. Classification accuracy and feature selection results confirmed the relevant contribution provided by the thermal features in the acute stress detection task. Indeed, a combination of ANS correlates and thermal features achieved 97.37% of accuracy. Moreover, using only thermal features we could still successfully detect stress with an accuracy of 86.84% in a contact-free manner.

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Section: Introductionmentioning

confidence: 99%

Towards a Contactless Stress Classification Using Thermal Imaging

Gioia

Greco

Callara

et al. 2022

Sensors

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“…Interference analysis of thermographic images was used before for estimation of error or multivariant distributions of input data in medicine [16,17], geological science [18,19], and some other fields, but it has never been used in building management systems anomaly estimation.…”

Section: Full-reference (Fr)mentioning

confidence: 99%

Real-Time Building Management System Visual Anomaly Detection Using Heat Points Motion Analysis Machine Learning Algorithm

Avcı

Michael

2023

Teh. vjesn.

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The multiplicity of design, construction, and use of IoT devices in homes has made it crucial to provide secure and manageable building management systems and platforms. Increasing security requires increasing the complexity of the user interface and the access verification steps in the system. Today, multi-step verification methods are used via SMS, call, or e-mail to do this. Another topic mentioned here is physical home security and energy management. Artificial intelligence and machine learning-based tools and algorithms are used to analyze images and data from sensors and security cameras. However, these tools are not always available due to the increase in data volume over time and the need for large processing resources. In this study, a new method is proposed to reduce the usage of process resources and the percentage of system error in anomaly detection by reducing visual data to critical points by using thermal cameras. This method can also be used in energy management using home and ambient temperature and user activity measurements. The statistical results of the visual comparison between the proposed method and the legacy CCTVbased visual and sensory surveillance shown in the results section demonstrate its reliability and accuracy.

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“…La aplicación de los SE ha sido extendida por diversos campos del conocimiento, desde controlar procesos industriales, detección y predicción de fallas en máquinas, hasta el campo de la medicina y sus subcampos; por ejemplo, la capacidad de medir el estrés de las personas basados en imágenes térmicas; por medio de tratamiento de dichas imágenes se pude determinar si una persona se encuentra frustrada o nerviosa; lo anterior, luego de realizar Página 8 | 27 un tratamiento de los datos recolectados, análisis estadístico, clasificación de imágenes aplicados a un SE y validación de los datos para la muestra de resultados [13]. Aunque los principales desarrollos de SE fueron en los años sesenta, la definición de SE ha evolucionado con los avances de las soluciones de tecnologías de la información a lo largo del tiempo, teniendo en cuenta sus principios y características como:…”

Section: Sistemas Expertosunclassified

Horno cementero rotatorio: una revisión al control mediante sistemas expertos

Tirado

Alarcón

Valencia

2022

TecnoL.

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Este artículo presenta una revisión de investigaciones realizadas mediante diferentes estrategias de control aplicadas en hornos cementeros rotatorios, sistema donde se da la fabricación de clínker, material indispensable para la elaboración del cemento. Esta exploración menciona estudios que se han desarrollado desde los años ochenta hasta el presente, destacando en cada una la metodología de control utilizada, los beneficios obtenidos en el proceso y sus futuras aplicaciones, esto con el fin de brindar al lector una visión global del uso de técnicas de control para hornos cementeros rotatorios y de cómo los avances científicos, con el paso de los años, han contribuido a esta industria en la eficiencia y mejora de sus procesos productivos; por tanto, se mencionan aportes y métodos de control como sistemas expertos (SE), control predictivo basado en modelo (MPC), redes neuronales artificiales y lógica difusa. Al finalizar la mencionada revisión se infiere que tecnologías de inteligencia artificial y de la industria 4.0 que se tienen actualmente como la computación en la nube, el procesamiento de grandes volúmenes de datos, el uso de los gemelos digitales, la ejecución de algoritmos de aprendizaje automático (machine learning) y sus herramientas de predicción, junto con la aplicación de SE y demás técnicas de control mencionadas, permitirían realizar un control avanzado, que pueda responder de forma satisfactoria a las necesidades de producción actuales y ofrecer múltiples beneficios como el tiempo de respuesta del control, la estabilidad, y mejoras en producción y calidad del material en un horno rotatorio.

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Novel expert system to study human stress based on thermographic images

Cited by 15 publications

References 54 publications

Towards a Contactless Stress Classification Using Thermal Imaging

Towards a Contactless Stress Classification Using Thermal Imaging

Real-Time Building Management System Visual Anomaly Detection Using Heat Points Motion Analysis Machine Learning Algorithm

Horno cementero rotatorio: una revisión al control mediante sistemas expertos

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