Biofeedback systems for stress reduction: Towards a Bright Future for a Revitalized Field

Stress has recently been baptized as the black death of the 21st century, which illustrates its threat to current health standards. This article proposes biofeedback systems as a means to reduce stress. A concise state-ofthe-art introduction on biofeedback systems is given. The field of mental health informatics is introduced. A compact state-of-the-art introduction on stress (reduction) is provided. A pragmatic solution for the pressing societal problem of illness due to chronic stress is provided in terms of closed loop biofeedback systems. A concise set of such biofeedback systems for stress reduction is presented. We end with the identification of several development phases and ethical concerns

Come, see and experience affective interactive art

The progress in the field of affective computing enables the realization of affective consumer products, affective games, and affective art. This paper describes the affective interactive art system Mood Swings, which interprets and visualizes affect expressed by a person. Mood Swings is founded on the integration of a framework for affective movements and a color model. This enables Mood Swings to recognize affective movement characteristics as expressed by a person and display a color that matches the expressed emotion. With that, a unique interactive system is introduced, which can be considered as art, a game, or a combination of both

Biometrics for Emotion Detection (BED): Exploring the combination of Speech and ECG

The paradigm Biometrics for Emotion Detection (BED) is introduced, which enables unobtrusive emotion recognition, taking into account varying environments. It uses the electrocardiogram (ECG) and speech, as a powerful but rarely used combination to unravel people’s emotions. BED was applied in two environments (i.e., office and home-like) in which 40 people watched 6 film scenes. It is shown that both heart rate variability (derived from the ECG) and, when people’s gender is taken into account, the standard deviation of the fundamental frequency of speech indicate people’s experienced emotions. As such, these measures validate each other. Moreover, it is found that people’s environment can indeed of influence experienced emotions. These results indicate that BED might become an important paradigm for unobtrusive emotion detection

Prerequisites for Affective Signal Processing (ASP)

Although emotions are embraced by science, their recognition has not reached a satisfying level. Through a concise overview of affect, its signals, features, and classification methods, we provide understanding for the problems encountered. Next, we identify the prerequisites for successful Affective Signal Processing: validation (e.g., mapping of constructs on signals), triangulation, a physiology-driven approach, and contributions of the signal processing community. Using these directives, a critical analysis of a real-world case is provided. This illustrates that the prerequisites can become a valuable guide for Affective Signal Processing (ASP)

On the perception of facial expressions in affective disorders and potential technological uses

Facial expressions are inherently linked to emotions and are a visual tool to communicate emotions to the surrounding world. A number of studies have evaluated the aptitude of different portions of the population in recognizing specific facial expressions. It is known that certain differences in the ability to correctly identify or assess the intensity of a facial expression can be attributed to psychological disorders. In particular, specific disorders seem to affect the processing of a particular emotion and the perception and interpretation of its associated facial expression. This work aims to summarize existing findings in literature on the topic and provide an outlook for potential technological use-cases, which can be applicable in the field of psychotherapy

Biosignals as an Advanced Man-Machine Interface

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such an MMI requires the correct classification of biosignals to emotion classes. This paper explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 24 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for both personalized biosignal-profiles and the recording of multiple biosignals in parallel

Unveiling Affective Signals

The ability to process and, subsequently, understand affective signals is the core of emotional intelligence and empathy. However, more than a decade of research in affective computing has shown that it is hard to develop computational models of this process. We pose that the solution for this problem lays in a better understanding of how to process these affective signals. This article introduces a symposium that brought together various approaches towards unveiling affective signals. As such, it is envisioned to be a springboard for affective computing

Prerequisites for Affective Signal Processing (ASP) - Part III

This is the third part in a series on prerequisites for affective signal processing (ASP). So far, six prerequisites were identified: validation (e.g., mapping of constructs on signals), triangulation, a physiology-driven approach, and contributions of the signal processing community (van den Broek et al., 2009) and identification of users and theoretical specification (van den Broek et al., 2010). Here, two additional prerequisites are identified: integration of biosignals, and physical characteristics

Prerequisites for Affective Signal Processing (ASP) - Part V: A response to comments and suggestions

In four papers, a set of eleven prerequisites for affective signal processing (ASP) were identified (van den Broek et al., 2010): validation, triangulation, a physiology-driven approach, contributions of the signal processing community, identification of users, theoretical specification, integration of biosignals, physical characteristics, historical perspective, temporal construction, and real-world baselines. Additionally, a review (in two parts) of affective computing was provided. Initiated by the reactions on these four papers, we now present: i) an extension of the review, ii) a post-hoc analysis based on the eleven prerequisites of Picard et al.(2001), and iii) a more detailed discussion and illustrations of temporal aspects with ASP