A.M.B.E.R. Shark-Fin: An Unobtrusive Affective Mouse

Analysing, measuring, recognising and exploiting emotion is an attractive agenda in designing computer games. The current devices for imputing physiological modalities are usually awkward to wear or handle. Here we propose a Shark-fin Mouse which streams three signals in real-time: pulse, electrodermal activity (EDA, also known as galvanic skin response or GSR) and skin temperature. All sensors are embedded into a fully functional computer mouse and positioned so as to ensure maximum robustness of the signals. No restriction of the mouse operation is imposed apart from the user having to place the tip of their middle finger into the Shark-fin hub. Boundary tests and experiments with a simple bespoke computer game demonstrate that the Shark-fin Mouse is capable of streaming clean and useful signals. Keywords-Interaction device; Affective gaming; Physiological sensors; Biometric feedback; Emotion I. I NTRODUCTION The video game industry, formally known as the interactive entertainment industry, has enjoyed perpetual growth since its foundation [8]. Video games are now experiencing the same level of financial-investment as seen in the film industry. The video game industry is among the largest entertainment industry worldwide, taking an estimated global income exceeding $50 billion in 2011 [15]. As computer systems have developed more processing power, video games have become more realistic and accompanied by the ever growing use of complex interactive devices, ranging from vibrating controllers [22] to fully tactile ha ptic feedback [23]. However, video games require more than representational graphics and tactility to be engagingly realistic. Video game environments also require greater humanlike emotive attributes or interactions between players and video game characters. Artificial intelligence (AI) attempts to bring the individuality of emotive human characteristics to human computer interactions (HCI). It has long been asserted that emotions are an important part of the human psyche and play a vital role in human communications [6]. The field Affective Computing (AC) has seen a dramatic rise in popularity over the past decade [24] [4] [25] permeating variou s disciplines such as computer science, electronic engineer ing and psychology. Growing on this trend, Affective Gaming (AG) is receiving significant consideration from academic and industrial fields [20] [3] [2] [12]. However, there is sti ll no consensus on the best modalities and methods to use to collect emotional data. Many modes have been considered for use in gaming environments, see table I. Table I AFFECTIVE GAMING MODALITIES AND THE CURRENT CONTRIBUTORS. Reference Modalities Game [2] Ambinder HR, eye movement, EDA, Left4Dead2 EEG, pupil dilation, EOG, Portal2 posture, gesture, voice, face expression, respiration [3] Bonarini EDA, HR, pressure, Racing game temperature, gyroscope [5] Chanel HR, EOG, GSR, EEG, Tetris respiration, temperature [7] Drachen EDA, HR Prey, Doom3, Bioshock [9] Gilleade HR Action based [10] Hoogen Control tilt, pressure Racing game [11] Jannett Time, eye movement HalfLife [12] Jones Vocal cue/pitch/intonation, HalfLife Mod speech rate/volume [16] McQuiggan HR, EDA Treasure Hunt (Source) [21] Nacke EDA, EMG HalfLife2 Mod [26] Rani HR, EDA Pong [27] Saari User control knobs Generic [29] Sykes Game pad pressure Space Invaders [30] Tijs HR, EDA, respiration Pacman [31] Tognetti EDA Racing game Abbreviated terms: Heart Rate (HR), Electrodermal Activity (EDA), Electrooculography (EOG), Electroencephalography (EEG), Electromyography (EMG). Emotions can be detected using a myriad of sensors. These sensors can be broadly divided into two distinct groups: behavioural and physiological, see figure 1. Behavioural recognition systems typically use cameras, microphones, Human Computer Interaction (HCI), and re488 Copyright (c) IARIA, 2013. ISBN: 978-1-61208-250-9 ACHI 2013 : The Sixth International Conference on Advances in Computer-Human Interactions