What does touch tell us about emotions in touchscreen-based gameplay?

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ACM. It is posted here by permission of ACM for your personal use. Not for redistribution.Nowadays, more and more people play games on touch-screen mobile phones. This phenomenon raises a very interesting question: does touch behaviour reflect the player’s emotional state? If possible, this would not only be a valuable evaluation indicator for game designers, but also for real-time personalization of the game experience. Psychology studies on acted touch behaviour show the existence of discriminative affective profiles. In this paper, finger-stroke features during gameplay on an iPod were extracted and their discriminative power analysed. Based on touch-behaviour, machine learning algorithms were used to build systems for automatically discriminating between four emotional states (Excited, Relaxed, Frustrated, Bored), two levels of arousal and two levels of valence. The results were very interesting reaching between 69% and 77% of correct discrimination between the four emotional states. Higher results (~89%) were obtained for discriminating between two levels of arousal and two levels of valence

Exploring the Use of Wearables to develop Assistive Technology for Visually Impaired People

This thesis explores the usage of two prominent wearable devices to develop assistive technology for users who are visually impaired. Specifically, the work in this thesis aims at improving the quality of life of users who are visually impaired by improving their mobility and ability to socially interact with others. We explore the use of a smart watch for creating low-cost spatial haptic applications. This app explores the use of haptic feedback provided using a smartwatch and smartphone to provide navigation instructions that let visually impaired people safely traverse a large open space. This spatial feedback guides them to walk on a straight path from source to destination by avoiding veering. Exploring the paired interaction between a Smartphone and a Smartwatch, helped to overcome the limitation that smart devices have only single haptic actuator.We explore the use of a head-mounted display to enhance social interaction by helping people with visual impairments align their head towards a conversation partner as well as maintain personal space during a conversation. Audio feedback is provided to the users guiding them to achieve effective face-to-face communication. A qualitative study of this method shows the effectiveness of the application and explains how it helps visually impaired people to perceive non-verbal cues and feel more engaged and assertive in social interactions

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Multisensory Perception and Learning: Linking Pedagogy, Psychophysics, and Human–Computer Interaction

In this review, we discuss how specific sensory channels can mediate the learning of properties of the environment. In recent years, schools have increasingly been using multisensory technology for teaching. However, it still needs to be sufficiently grounded in neuroscientific and pedagogical evidence. Researchers have recently renewed understanding around the role of communication between sensory modalities during development. In the current review, we outline four principles that will aid technological development based on theoretical models of multisensory development and embodiment to foster in-depth, perceptual, and conceptual learning of mathematics. We also discuss how a multidisciplinary approach offers a unique contribution to development of new practical solutions for learning in school. Scientists, engineers, and pedagogical experts offer their interdisciplinary points of view on this topic. At the end of the review, we present our results, showing that one can use multiple sensory inputs and sensorimotor associations in multisensory technology to improve the discrimination of angles, but also possibly for educational purposes. Finally, we present an application, the ‘RobotAngle’ developed for primary (i.e., elementary) school children, which uses sounds and body movements to learn about angles

From presence to consciousness through virtual reality

Immersive virtual environments can break the deep, everyday connection between where our senses tell us we are and where we are actually located and whom we are with. The concept of 'presence' refers to the phenomenon of behaving and feeling as if we are in the virtual world created by computer displays. In this article, we argue that presence is worthy of study by neuroscientists, and that it might aid the study of perception and consciousness

Simulating dynamic facial expressions of pain from visuo-haptic interactions with a robotic patient

Medical training simulators can provide a safe and controlled environment for medical students to practice their physical examination skills. An important source of information for physicians is the visual feedback of involuntary pain facial expressions in response to physical palpation on an affected area of a patient. However, most existing robotic medical training simulators that can capture physical examination behaviours in real-time cannot display facial expressions and comprise a limited range of patient identities in terms of ethnicity and gender. Together, these limitations restrict the utility of medical training simulators because they do not provide medical students with a representative sample of pain facial expressions and face identities, which could result in biased practices. Further, these limitations restrict the utility of such medical simulators to detect and correct early signs of bias in medical training. Here, for the first time, we present a robotic system that can simulate facial expressions of pain in response to palpations, displayed on a range of patient face identities. We use the unique approach of modelling dynamic pain facial expressions using a data-driven perception-based psychophysical method combined with the visuo-haptic inputs of users performing palpations on a robot medical simulator. Specifically, participants performed palpation actions on the abdomen phantom of a simulated patient, which triggered the real-time display of six pain-related facial Action Units (AUs) on a robotic face (MorphFace), each controlled by two pseudo randomly generated transient parameters: rate of change β and activation delay τ. Participants then rated the appropriateness of the facial expression displayed in response to their palpations on a 4-point scale from “strongly disagree” to “strongly agree”. Each participant (n=16, 4 Asian females, 4 Asian males, 4 White females and 4 White males) performed 200 palpation trials on 4 patient identities (Black female, Black male, White female and White male) simulated using MorphFace. Results showed facial expressions rated as most appropriate by all participants comprise a higher rate of change and shorter delay from upper face AUs (around the eyes) to those in the lower face (around the mouth). In contrast, we found that transient parameter values of most appropriate-rated pain facial expressions, palpation forces, and delays between palpation actions varied across participant-simulated patient pairs according to gender and ethnicity. These findings suggest that gender and ethnicity biases affect palpation strategies and the perception of pain facial expressions displayed on MorphFace. We anticipate that our approach will be used to generate physical examination models with diverse patient demographics to reduce erroneous judgments in medical students, and provide focused training to address these errors

Social touch in human–computer interaction

Touch is our primary non-verbal communication channel for conveying intimate emotions and as such essential for our physical and emotional wellbeing. In our digital age, human social interaction is often mediated. However, even though there is increasing evidence that mediated touch affords affective communication, current communication systems (such as videoconferencing) still do not support communication through the sense of touch. As a result, mediated communication does not provide the intense affective experience of co-located communication. The need for ICT mediated or generated touch as an intuitive way of social communication is even further emphasized by the growing interest in the use of touch-enabled agents and robots for healthcare, teaching, and telepresence applications. Here, we review the important role of social touch in our daily life and the available evidence that affective touch can be mediated reliably between humans and between humans and digital agents. We base our observations on evidence from psychology, computer science, sociology, and neuroscience with focus on the first two. Our review shows that mediated affective touch can modulate physiological responses, increase trust and affection, help to establish bonds between humans and avatars or robots, and initiate pro-social behavior. We argue that ICT mediated or generated social touch can (a) intensify the perceived social presence of remote communication partners and (b) enable computer systems to more effectively convey affective information. However, this research field on the crossroads of ICT and psychology is still embryonic and we identify several topics that can help to mature the field in the following areas: establishing an overarching theoretical framework, employing better research methodologies, developing basic social touch building blocks, and solving specific ICT challenges

Robust Modeling of Epistemic Mental States and Their Applications in Assistive Technology

This dissertation presents the design and implementation of EmoAssist: Emotion-Enabled Assistive Tool to Enhance Dyadic Conversation for the Blind . The key functionalities of the system are to recognize behavioral expressions and to predict 3-D affective dimensions from visual cues and to provide audio feedback to the visually impaired in a natural environment. Prior to describing the EmoAssist, this dissertation identifies and advances research challenges in the analysis of the facial features and their temporal dynamics with Epistemic Mental States in dyadic conversation. A number of statistical analyses and simulations were performed to get the answer of important research questions about the complex interplay between facial features and mental states. It was found that the non-linear relations are mostly prevalent rather than the linear ones. Further, the portable prototype of assistive technology that can aid blind individual to understand his/her interlocutor\u27s mental states has been designed based on the analysis. A number of challenges related to the system, communication protocols, error-free tracking of face and robust modeling of behavioral expressions /affective dimensions were addressed to make the EmoAssist effective in a real world scenario. In addition, orientation-sensor information from the phone was used to correct image alignment to improve the robustness in real life deployment. It was observed that the EmoAssist can predict affective dimensions with acceptable accuracy (Maximum Correlation-Coefficient for valence: 0.76, arousal: 0.78, and dominance: 0.76) in natural conversation. The overall minimum and maximum response-times are (64.61 milliseconds) and (128.22 milliseconds), respectively. The integration of sensor information for correcting the orientation has helped in significant improvement (16% in average) of accuracy in recognizing behavioral expressions. A user study with ten blind people shows that the EmoAssist is highly acceptable to them (Average acceptability rating using Likert: 6.0 where 1 and 7 are the lowest and highest possible ratings, respectively) in social interaction