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Emotional Maps for User Experience Research in the Wild Auteurs Titre: Emotional Maps for User Experience Research in the Wild Title: Auteurs: Vanessa Georges, François Courtemanche, Marc Fredette et Philippe Authors: Doyon-Poulin Date: 2020 Type: Communication de conférence / Conference or workshop item Georges, V., Courtemanche, F., Fredette, M. & Doyon-Poulin, P. (2020, avril). Référence: Emotional Maps for User Experience Research in the Wild. Communication écrite Citation: présentée à CHI Conference on Human Factors in Computing Systems (CHI 2020), Honolulu, Hawaï, États-Unis (8 pages). doi:10.1145/3334480.3383042 Document en libre accès dans PolyPublie Open Access document in PolyPublie URL de PolyPublie: https://publications.polymtl.ca/6656/ PolyPublie URL: Version finale avant publication / Accepted version Version: Révisé par les pairs / Refereed Conditions d’utilisation: Tous droits réservés / All rights reserved Terms of Use: Document publié chez l’éditeur officiel Document issued by the official publisher Nom de la conférence: CHI Conference on Human Factors in Computing Systems (CHI 2020) Conference Name: Date et lieu: 25-30 avril 2020, En ligne / Online Date and Location: Maison d’édition: ACM Publisher: URL officiel: https://doi.org/10.1145/3334480.3383042 Official URL: © 2020 Copyright is held by the owner/author(s) This is the author's version of the Mention légale: work. It is posted here for your personal use. Not for redistribution. The definitive Legal notice: Version of Record was published in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, https://doi.org/10.1145/3334480.3383042 Ce fichier a été téléchargé à partir de PolyPublie, le dépôt institutionnel de Polytechnique Montréal This file has been downloaded from PolyPublie, the institutional repository of Polytechnique Montréal http://publications.polymtl.ca Emotional Maps for User Experience Research in the Wild Abstract Vanessa Georges While most traditional user experience (UX) evaluation Polytechnique Montréal methods (e.g., questionnaires) have made the Montréal, QC H3T 1J4, Canada [email protected] transition to the “wild”, physiological measurements still strongly rely upon controlled lab settings. As part François Courtemanche of an ongoing research agenda, this paper presents a Marc Fredette novel approach for UX research which contributes to HEC Montréal this transition. The proposed method triangulates GPS Montréal, QC H3T 2A7, Canada and physiological data to create emotional maps, which [email protected] outline geographical areas where users experienced [email protected] specific emotional states in outdoor environments. The method is implemented as a small portable recording Philippe Doyon-Poulin device, and a data visualization software. A field study Polytechnique Montréal was conducted in an amusement park to test the Montréal, QC H3T 1J4, Canada proposed approach. Emotional maps highlighting the [email protected] areas where users experienced varying levels of arousal are presented. We also discuss insights uncovered, and how UX practitioners could use the approach to bring their own research into the wild. Permission to make digital or hard copies of part or all of this work for Author Keywords personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that User Experience; Emotion Evaluation; Heat maps; Data copies bear this notice and the full citation on the first page. Copyrights Visualization; Physiological Measures; In the Wild for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Methods. CHI 2020 Extended Abstracts, April 25–30, 2020, Honolulu, HI, USA. © 2020 Copyright is held by the owner/author(s). ACM ISBN 978-1-4503-6819-3/20/04. CSS Concepts DOI: https://doi.org/10.1145/3334480.3383042 • Human-centered computing~Visualization; Visualization systems and tool; Visualization design and evaluation methods; Heat maps. Introduction emotional maps, which outline areas where users In controlled lab settings, physiological signals can be experienced specific emotional states in outdoor used to infer users’ emotional states during system environments. As part of the approach, a recording interaction. Physiological and behavioral signals (e.g., device and data visualization software were electrodermal activity, heart rate, or facial expressions) implemented. can provide UX researchers and practitioners insights as to what users are experiencing without interference Method [11, 13]. These signals can also be used to uncover In the wild studies often entail a balancing act between emotional states which the user himself is unaware of experimental control and ecological validity. As such, or cannot recall when asked using traditional evaluation researchers have argued that the concept of ecological methods, such as questionnaires and interviews [9]. validity should be regarded as a continuum [10]. While traditional UX evaluation methods have made the Therefore, the minimal degree of experimental control transition to the “wild”, physiological measurements that guarantees sufficient data quality should be aimed have yet to do so. This raises the question: How can we for. facilitate the transition of physiological measures from lab to their use “in the wild” for user experience Physiological measures evaluation? To meet this challenge, researchers have To validate the effectiveness of the proposed method developed methods to infer users’ emotional state and arousal, which contrast states of low (e.g., calm) and behavior using various sensors, such as GPS, high (e.g., surprise) intensity [20] was chosen as the accelerometers and facial expressions. For example, physiological state of interest. Therefore, two main the Feel-o-meter project [18] used a digital camera to criteria guided the selection of physiological signals for capture the facial expressions of passersby to produce our field study: 1) psychophysiological relevance with a giant smiley face whose expression would reflect emotion intensity, and 2) readiness for deployment “in users’ aggregated data. Also, using facial recognition the wild” (motion artefacts robustness and software, Hernandez et al. [8] developed the Mood intrusiveness). Respecting those requirements, we Meter, a vision-based computer system which selected two signals that are indicators of the generates affective portraits of various areas around autonomic nervous system response to intense the MIT campus. emotional state; electrodermal activity (EDA) and electrocardiography (ECG) signals [12]. Building on prior research contribution, we present a new approach which aims to facilitate the use of EDA is composed of two different components: tonic physiological measures in field evaluations. While UX skin conductance level (SCL) and phasic skin heatmaps triangulates users’ gaze data with inferred conductance response (SCR). The latter is known to users’ cognitive and emotional states to produce user reflect short-term responses of the autonomic nervous experience (UX) heatmaps [33], the proposed method system and is a reliable indicator of emotional arousal triangulates GPS and physiological data to create [3]. In our experimental setup, EDA was recorded using two electrodes placed on the wrist of participants’ non- display image, a high-resolution satellite view of the dominant hand. Numerous studies showed valid amusement park, was extracted from Google Maps measurements of skin conductance with sensor (http://www.mappuzzle.se) with a resolution of 2956 x placement on the wrists and forearm [14]. To obtain 2585 pixels, corresponding to an actual surface of clean phasic data, signal preprocessing steps were 635m x 559m. We computed the correspondence executed as follows. Data was recorded at 100 Hz and between spherical and planar coordinates using a resampled to 25 Hz, before applying a low-pass 2nd pseudo-Mercator projection order Butterworth filter and a 50 Hz cut-off. Signal was (https://tinyurl.com/yycr85lv). For small areas, such as then decomposed in tonic and phasic components using the amusement park used in this study, linear curve the convex optimization algorithm described in [7]. fitting may have been sufficiently precise for location mapping. However, we used pseudo-Mercator Figure 1: Portable device used to ECG measures the electrical activity associated with projection to ensure that the method is applicable for simultaneously record GPS data, electrodermal activity, and heart contraction of the heart muscles by recording the studies taking place in larger areas (e.g. state or rate. potential difference it generates between two country level). electrodes and a ground reference [2]. In our study, ECG was recorded using three electrodes placed on the In our context, a data point consists of a GPS participants’ torso. ECG r-peaks were identified using coordinate obtained at time t along with the average The device consists of a the Biosppy python library for biosignal processing HR and phasic EDA values around time t (from 500ms Bitalino (r)evolution Freestyle (https://biosppy.readthedocs.io/en/stable/), and before to 500ms after). For each data point, the Kit (PLUX Wireless Biosignals interbeat intervals and heart rate (HR) were computed corresponding matrix cell’s (x, y) value is incremented S.A.) [1] set into a 3D- with pyhrv, an open-source Python toolbox for Heart by the signals’ mean value. printed enclosure box. The Rate Variability (https://pypi.org/project/pyhrv/).
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