Stress in interactive applications: analysis of the valence-arousal space based on physiological signals and self-reported data

Liapis, Alexandros; Katsanos, Christos; Sotiropoulos, D. G.; Καρούσος, Νίκος; Xenos, Michalis

doi:10.1007/s11042-016-3637-2

Cited by 23 publications

(11 citation statements)

References 47 publications

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“…Psychological relaxation was measured using the Affect Grid 40 , which assesses affective state along the two dimensions displeasure/pleasure, and arousal/sleepiness. The instrument has adequate reliability and validity 40 , 41 , and has been used in in different experimental settings, such as longitudinal ecological momentary assessment 42 , or experimental designs 43 – 45 . The score for each dimension ranges from 1 to 9.…”

Section: Methodsmentioning

confidence: 99%

Standardized massage interventions as protocols for the induction of psychophysiological relaxation in the laboratory: a block randomized, controlled trial

Meier¹,

Unternäehrer

Dimitroff³

et al. 2020

Sci Rep

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Health and disease are strongly linked to psychophysiological states. While stress research strongly benefits from standardized stressors, no established protocol focuses on the induction of psychophysiological relaxation. To maintain health, functioning regenerative systems are however likely as important as functioning stress systems. Thus, the identification of validated relaxation paradigms is needed. Here, we investigated whether standardized massages are capable of reliably inducing physiological and psychological states of relaxation. Relaxation was indicated by changes in high frequency heart rate variability (HF-HRV), a vagally-mediated heart rate variability component, and repeated ratings of subjective relaxation, and stress levels. Sixty healthy women were randomly assigned to a vagus nerve massage (n = 19), a soft shoulder massage (n = 22), or a resting control group (n = 19). During the intervention, HF-HRV and subjective relaxation increased, while subjective stress decreased significantly in all groups. Both massage interventions elicited significantly higher HF-HRV compared to the control group. Accordingly, both massage protocols increased psychophysiological relaxation, and may serve as useful tools in future research. However, future work will have to determine which of several protocols might be used as a gold standard to induce a psychophysiological state of relaxation in the laboratory.

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Section: Methodsmentioning

confidence: 99%

Standardized massage interventions as protocols for the induction of psychophysiological relaxation in the laboratory: a block randomized, controlled trial

Meier¹,

Unternäehrer

Dimitroff³

et al. 2020

Sci Rep

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show abstract

“…Moreover, Pavlidis et al proposed quantifying stress through thermal IR imaging [54]. Stress in the valence-arousal space is identified as negative valence and high arousal [66]. Pavlidis et al found that high stressful situations resulting in the cooling of the area around the nose tip [54].…”

Section: Affective States Recognition Through Thermal Ir Imagingmentioning

confidence: 99%

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

et al. 2020

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Over recent years, robots are increasingly being employed in several aspects of modern society. Among others, social robots have the potential to benefit education, healthcare, and tourism. To achieve this purpose, robots should be able to engage humans, recognize users’ emotions, and to some extent properly react and "behave" in a natural interaction. Most robotics applications primarily use visual information for emotion recognition, which is often based on facial expressions. However, the display of emotional states through facial expression is inherently a voluntary controlled process that is typical of human–human interaction. In fact, humans have not yet learned to use this channel when communicating with a robotic technology. Hence, there is an urgent need to exploit emotion information channels not directly controlled by humans, such as those that can be ascribed to physiological modulations. Thermal infrared imaging-based affective computing has the potential to be the solution to such an issue. It is a validated technology that allows the non-obtrusive monitoring of physiological parameters and from which it might be possible to infer affective states. This review is aimed to outline the advantages and the current research challenges of thermal imaging-based affective computing for human–robot interaction.

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“…For example, Catherine et al [49] found that increased stress reactivity was associated with a stronger negativity bias of valence by measuring the salivary cortisol. Alexandros et al [50] utilized the self-report and found a high correlation (85%) between stress and negative valence. Therefore, the valence from the DEAP dataset was used for the labels.…”

Section: Resultsmentioning

confidence: 99%

A Transductive Model-based Stress Recognition Method Using Peripheral Physiological Signals

Xie

Wang

2019

Sensors

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Existing research on stress recognition focuses on the extraction of physiological features and uses a classifier that is based on global optimization. There are still challenges relating to the differences in individual physiological signals for stress recognition, including dispersed distribution and sample imbalance. In this work, we proposed a framework for real-time stress recognition using peripheral physiological signals, which aimed to reduce the errors caused by individual differences and to improve the regressive performance of stress recognition. The proposed framework was presented as a transductive model based on transductive learning, which considered local learning as a virtue of the neighborhood knowledge of training examples. The degree of dispersion of the continuous labels in the y space was also one of the influencing factors of the transductive model. For prediction, we selected the epsilon-support vector regression (e-SVR) to construct the transductive model. The non-linear real-time features were extracted using a combination of wavelet packet decomposition and bi-spectrum analysis. The performance of the proposed approach was evaluated using the DEAP dataset and Stroop training. The results indicated the effectiveness of the transductive model, which had a better prediction performance compared to traditional methods. Furthermore, the real-time interactive experiment was conducted in field studies to explore the usability of the proposed framework.

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Stress in interactive applications: analysis of the valence-arousal space based on physiological signals and self-reported data

Cited by 23 publications

References 47 publications

Standardized massage interventions as protocols for the induction of psychophysiological relaxation in the laboratory: a block randomized, controlled trial

Standardized massage interventions as protocols for the induction of psychophysiological relaxation in the laboratory: a block randomized, controlled trial

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

A Transductive Model-based Stress Recognition Method Using Peripheral Physiological Signals

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