Towards emotion recognition for virtual environments: an evaluation of eeg features on benchmark dataset

One of the challenges in virtual environments is the difficulty users have in interacting with these increasingly complex systems. Ultimately, endowing machines with the ability to perceive users emotions will enable a more intuitive and reliable interaction. Consequently, using the electroencephalogram as a bio-signal sensor, the affective state of a user can be modelled and subsequently utilised in order to achieve a system that can recognise and react to the user’s emotions. This paper investigates features extracted from electroencephalogram signals for the purpose of affective state modelling based on Russell’s Circumplex Model. Investigations are presented that aim to provide the foundation for future work in modelling user affect to enhance interaction experience in virtual environments. The DEAP dataset was used within this work, along with a Support Vector Machine and Random Forest, which yielded reasonable classification accuracies for Valence and Arousal using feature vectors based on statistical measurements and band power from the and waves and High Order Crossing of the EEG signal

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

The reliability and validity of the Chinese version of Abbreviated PAD Emotion Scales

The study aimed at testing the reliabilityand validity of the Chinese version of Abbreviated PAD Emotion Scales using a Chinese sample. 297 Chinese undergraduate students were tested with the Chinese version of Abbreviated PAD Emotion Scales; 98 of them were retested with the same scales after seven days in order to assess thetest-retest reliability; and 102 of them were tested with SCL-90 at the same time which was intended as criteria for validity to assess the criterion validity. The results showedthat the Chinese version of Abbreviated PAD Emotion Scales displayed satisfying reliability and validity on P (pleasure-displeasure), only moderate reliability and validityon D (dominance-submissiveness), but quite low reliability and validity on A(arousal-nonarousal)The study aimed at testing the reliability and validity of the Chinese version of Abbreviated PAD Emotion Scales using a Chinese sample. 297 Chinese undergraduate students were tested with the Chinese version of Abbreviated PAD Emotion Scales; 98 of them were retested with the same scales after seven days in order to assess the test-retest reliability; and 102 of them were tested with SCL-90 at the same time which was intended as criteria for validity to assess the criterion validity. The results showed that the Chinese version of Abbreviated PAD Emotion Scales displayed satisfying reliability and validity on P (pleasure-displeasure), only moderate reliability and validity on D (dominance-submissiveness), but quite low reliability and validity on A (arousal-nonarousal)

Recognising facial expressions in video sequences

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

Affective recognition from EEG signals: an integrated data-mining approach

Emotions play an important role in human communication, interaction, and decision making processes. Therefore, considerable efforts have been made towards the automatic identification of human emotions, in particular electroencephalogram (EEG) signals and Data Mining (DM) techniques have been then used to create models recognizing the affective states of users. However, most previous works have used clinical grade EEG systems with at least 32 electrodes. These systems are expensive and cumbersome, and therefore unsuitable for usage during normal daily activities. Smaller EEG headsets such as the Emotiv are now available and can be used during daily activities. This paper investigates the accuracy and applicability of previous affective recognition methods on data collected with an Emotiv headset while participants used a personal computer to fulfill several tasks. Several features were extracted from four channels only (AF3, AF4, F3 and F4 in accordance with the 10–20 system). Both Support Vector Machine and Naïve Bayes were used for emotion classification. Results demonstrate that such methods can be used to accurately detect emotions using a small EEG headset during a normal daily activity

Cross validation of bi-modal health-related stress assessment

This study explores the feasibility of objective and ubiquitous stress assessment. 25 post-traumatic stress disorder patients participated in a controlled storytelling (ST) study and an ecologically valid reliving (RL) study. The two studies were meant to represent an early and a late therapy session, and each consisted of a "happy" and a "stress triggering" part. Two instruments were chosen to assess the stress level of the patients at various point in time during therapy: (i) speech, used as an objective and ubiquitous stress indicator and (ii) the subjective unit of distress (SUD), a clinically validated Likert scale. In total, 13 statistical parameters were derived from each of five speech features: amplitude, zero-crossings, power, high-frequency power, and pitch. To model the emotional state of the patients, 28 parameters were selected from this set by means of a linear regression model and, subsequently, compressed into 11 principal components. The SUD and speech model were cross-validated, using 3 machine learning algorithms. Between 90% (2 SUD levels) and 39% (10 SUD levels) correct classification was achieved. The two sessions could be discriminated in 89% (for ST) and 77% (for RL) of the cases. This report fills a gap between laboratory and clinical studies, and its results emphasize the usefulness of Computer Aided Diagnostics (CAD) for mental health care

Emotional design and human-robot interaction

Recent years have shown an increase in the importance of emotions applied to the Design field - Emotional Design. In this sense, the emotional design aims to elicit (e.g., pleasure) or prevent (e.g., displeasure) determined emotions, during human product interaction. That is, the emotional design regulates the emotional interaction between the individual and the product (e.g., robot). Robot design has been a growing area whereby robots are interacting directly with humans in which emotions are essential in the interaction. Therefore, this paper aims, through a non-systematic literature review, to explore the application of emotional design, particularly on Human-Robot Interaction. Robot design features (e.g., appearance, expressing emotions and spatial distance) that affect emotional design are introduced. The chapter ends with a discussion and a conclusion.info:eu-repo/semantics/acceptedVersio

Psychophysiology in games

Psychophysiology is the study of the relationship between psychology and its physiological manifestations. That relationship is of particular importance for both game design and ultimately gameplaying. Players’ psychophysiology offers a gateway towards a better understanding of playing behavior and experience. That knowledge can, in turn, be beneficial for the player as it allows designers to make better games for them; either explicitly by altering the game during play or implicitly during the game design process. This chapter argues for the importance of physiology for the investigation of player affect in games, reviews the current state of the art in sensor technology and outlines the key phases for the application of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject (project no: 318803).peer-reviewe

Declining Burden of Malaria Over two Decades in a Rural Community of Muheza District, North-Eastern Tanzania.

The recently reported declining burden of malaria in some African countries has been attributed to scaling-up of different interventions although in some areas, these changes started before implementation of major interventions. This study assessed the long-term trends of malaria burden for 20 years (1992--2012) in Magoda and for 15 years in Mpapayu village of Muheza district, north-eastern Tanzania, in relation to different interventions as well as changing national malaria control policies.\ud Repeated cross-sectional surveys recruited individuals aged 0 -- 19 years from the two villages whereby blood smears were collected for detection of malaria parasites by microscopy. Prevalence of Plasmodium falciparum infections and other indices of malaria burden (prevalence of anaemia, splenomegaly and gametocytes) were compared across the years and between the study villages. Major interventions deployed including mobile clinic, bed nets and other research activities, and changes in national malaria control policies were also marked. In Magoda, the prevalence of P. falciparum infections initially decreased between 1992 and 1996 (from 83.5 to 62.0%), stabilized between 1996 and 1997, and further declined to 34.4% in 2004. A temporary increase between 2004 and 2008 was followed by a progressive decline to 7.2% in 2012, which is more than 10-fold decrease since 1992. In Mpapayu (from 1998), the highest prevalence was 81.5% in 1999 and it decreased to 25% in 2004. After a slight increase in 2008, a steady decline followed, reaching <5% from 2011 onwards. Bed net usage was high in both villages from 1999 to 2004 (>=88%) but it decreased between 2008 and 2012 (range, 28% - 68%). After adjusting for the effects of bed nets, age, fever and year of study, the risk of P. falciparum infections decreased significantly by >=97% in both villages between 1999 and 2012 (p < 0.001). The prevalence of splenomegaly (>40% to <1%) and gametocytes (23% to <1%) also decreased in both villages.Discussion and conclusionsA remarkable decline in the burden of malaria occurred between 1992 and 2012 and the initial decline (1992 -- 2004) was most likely due to deployment of interventions, such as bed nets, and better services through research activities. Apart from changes of drug policies, the steady decline observed from 2008 occurred when bed net coverage was low suggesting that other factors contributed to the most recent pattern. These results suggest that continued monitoring is required to determine causes of the changing malaria epidemiology and also to monitor the progress towards maintaining low malaria transmission and reaching related millennium development goals