Analysis of physiological signals for recognition of boredom, pain, and surprise emotions

Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jong Hee

doi:10.1186/s40101-015-0063-5

Cited by 122 publications

(100 citation statements)

References 36 publications

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“…The observed biometric patterns exhibited by our participants are unlikely to be reflective of other processes such as the relief of pain or the onset of sleep. Previous literature on biometric response to pain has demonstrated significant rise in EDA during painful stimuli and to a lesser degree decrease in skin temperature [16,17]. We would expect that if the changes were simply due to relief of pain, a marked decrease in EDA would occur, which was not observed in our study population.…”

Section: Discussionmentioning

confidence: 49%

Wearable Biosensors to Detect Physiologic Change During Opioid Use

et al. 2016

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Introduction Opioid analgesic use is a major cause of morbidity and mortality in the US, yet effective treatment programs have a limited ability to detect relapse. The utility of current drug detection methods is often restricted due to their retrospective and subjective nature. Wearable biosensors have the potential to improve detection of relapse by providing objective, real time physiologic data on opioid use that can be used by treating clinicians to augment behavioral interventions. Methods Thirty emergency department (ED) patients who were prescribed intravenous opioid medication for acute pain were recruited to wear a wristband biosensor. The biosensor measured electrodermal activity, skin temperature and locomotion data, which was recorded before and after intravenous opioid administration. Hilbert transform analyses combined with paired t-tests were used to compare the biosensor data A) within subjects, before and after administration of opioids; B) between subjects, based on hand dominance, gender, and opioid use history. Results Within subjects, a significant decrease in locomotion and increase in skin temperature were consistently detected by the biosensors after opioid administration. A significant change in electrodermal activity was not consistently detected. Between subjects, biometric changes varied with level of opioid use history (heavy vs. nonheavy users), but did not vary with gender or type of opioid. Specifically, heavy users demonstrated a greater decrease in short amplitude movements (i.e. fidgeting movements) compared to non-heavy users. Conclusion A wearable biosensor showed a consistent physiologic pattern after ED opioid administration and differences between patterns of heavy and non-heavy opioid users were noted. Potential applications of biosensors to drug addiction treatment and pain management should be studied further.

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Section: Discussionmentioning

confidence: 49%

Wearable Biosensors to Detect Physiologic Change During Opioid Use

et al. 2016

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“…Previous studies have provided evidence for general recognition rate from 57,77% to 85,46% for different emotional states, that more higher set of analyzed signals and more recognized emotions provides better results [64][65][66]. High-observed recognition accuracy was also in research by Jang et al: 84.7% [58].…”

Section: Accuracymentioning

confidence: 80%

“…Research by Jang et al used ECG, EDA, SKT and more sophistical machine learning (ML) algorithms [58]:…”

Section: Physiological Signalsmentioning

confidence: 99%

Survey on AI-Based Multimodal Methods for Emotion Detection

Maréchal

Mikołajewski

Tyburek

et al. 2019

Lecture Notes in Computer Science

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Automatic emotion recognition constitutes one of the great challenges providing new tools for more objective and quicker diagnosis, communication and research. Quick and accurate emotion recognition may increase possibilities of computers, robots, and integrated environments to recognize human emotions, and response accordingly to them a social rules. The purpose of this paper is to investigate the possibility of automated emotion representation, recognition and prediction its state-of-the-art and main directions for further research. We focus on the impact of emotion analysis and state of the arts of multimodal emotion detection. We present existing works, possibilities and existing methods to analyze emotion in text, sound, image, video and physiological signals. We also emphasize the most important features for all available emotion recognition modes. Finally, we present the available platform and outlines the existing projects, which deal with multimodal emotion analysis.

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“…Desde fines de la década de los 80s y hasta el presente se conoce que la expresión facial incrementa la actividad autonómica (Levenson, Ekman & Friesen, 1990); en el caso del reconocimiento de la expresión facial de dolor también hay cambios psicofisiológicos cardiovasculaes (Jang, Park, Park, Kim & Sohn, 2015). Esto posibilita que, si el personal de salud no cuenta con el entrenamiento en reconocimiento de microexpresiones faciales, se puede optar por una cámara de imagen térmica infrarroja (iTF), una herramienta portátil de registro psicofisiológico, útil para la valoración de actividad autonómica asociada al dolor.…”

Section: Figuraunclassified

Dolor y Termografía

Rodríguez-Medina

2018

RDIPyCS

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RESUMENLa valoración y manejo del dolor representa un desafío para el clínico tratante. Aun cuando las intervenciones psicológicas para el manejo del dolor han mostrado un sólido nivel de evidencia enmarcadas en las guías médicas, no existen guías psicológicas propias con algoritmos para la evaluación y tratamiento del paciente. En un esfuerzo bien conducido por las Dras. Flor y Turk (2011), se propuso el inventario multidimensional del dolor, mostrando cuatro perfiles de pacientes cuya principal diferencia fue la tensión muscular. Desde una perspectiva biopsicosocial puede considerarse el dolor crónico como un trastorno psicofisiológico. La presencia de dolor induce una respuesta nerviosa simpática, la cual influye en la respuesta inflamatoria. El objetivo de esta presentación es introducir al personal sanitario tratante sobre el uso de la imagen térmica infrarroja para la valoración de la actividad autonómica asociada al dolor como parte de un perfil biopsicosocial. Primero se aborda el tema de dolor y termografía, cuyos resultados muestran que, ante la presencia de dolor, la temperatura periférica (manos, nariz) decrementa. Los estudios piloto presentados sugieren que el manejo de estrategias de relajación incrementa la temperatura periférica e inducen la actividad parasimpática asociada al alivio. Finalmente se presenta la integración del perfil biopsicosocial del paciente con el propósito de desarrollar un plan de intervención y pronóstico afectivo con base en evidencia. En suma, se propone el uso de biomarcadores (citoquinas proinflamatorias, termobiomarcadores) como parámetro clínico para la evaluación e intervención psicológica, similar a los presentados por Flor y Turk (2011). Palabras Clave:Termografía, Dolor, Expresión Facial, IL-6 ABSTRACT The assessment and management of pain represents a challenge for the treating clinician. Even though psychological interventions for pain management have shown a solid level of evidence framed in the medical guidelines, there are no psychological guides of their own with algorithms for the evaluation and treatment of the patient. In an effort well conducted by the researchs Flor & Turk (2011), proposed the multidimensional inventory of pain, showing four profiles of patients whose main difference was muscle tension. From a biopsychosocial perspective, chronic pain can be considered a psychophysiological disorder. The presence of pain induces a sympathetic nervous response, which influences the inflammatory response. The objective of this presentation is to introduce the healthcare personnel on the use of infrared thermal image for the assessment of autonomic activity associated with pain as part of a biopsychosocial profile. First, the topic of pain and thermography is addressed, the results of which show that, in the presence of pain, the peripheral temperature (hands, nose) decreases. The pilot studies presented suggest that the management of relaxation strategies increases peripheral temperature and induces parasympathetic activity associated with relief. Finall...

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Analysis of physiological signals for recognition of boredom, pain, and surprise emotions

Cited by 122 publications

References 36 publications

Wearable Biosensors to Detect Physiologic Change During Opioid Use

Wearable Biosensors to Detect Physiologic Change During Opioid Use

Survey on AI-Based Multimodal Methods for Emotion Detection

Dolor y Termografía

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