Mood measurement with Pick-A-Mood: review of current methods and design of a pictorial self-report scale

Desmet, Pieter; Vastenburg, Martijn H.; Romero, Natalia

doi:10.1504/jdr.2016.079751

Cited by 96 publications

(90 citation statements)

References 40 publications

(47 reference statements)

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“…However, the categorization of these instruments is not completely acknowledged. The literature tends to distinguish them from tools and techniques that are to be considered behavioral, see example Katicic et al (2015) and Desmet et al (2016). These include, among others, the analysis of hand gestures, which complements biometric measurements in some of the described experiments, and Facial Expression Recognition, whose use is surfacing in design research as well, e.g.…”

Section: Limitationsmentioning

confidence: 99%

Review of the use of neurophysiological and biometric measures in experimental design research

Borgianni

Maccioni

2020

AIEDAM

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AbstractDesign is inherently affected by human-related factors and it is of no surprise that the fine-tuning of instruments capable of measuring aspects of human behavior has attracted interest in the design field. The recalled instruments include a variety of devices that capture and quantitatively assess people's unintentional and unconscious reactions and that are generally referred as neurophysiological or biometric. The number of experimental applications of these instruments in design was extremely limited as of 2016, when Lohmeyer and Meboldt published a first report on relevant measures and their interpretation in design. In the last few years, the number of relevant publications has increased dramatically and this determines the opportunity to carry out a comprehensive review in the field. The reviewed contributions are analyzed and classified according to, among others, instruments used, the kind of stakeholders involved and the supported design research activities. The role of biometric measures with respect to traditional research methods is emphasized too. The discussed instruments can represent supports or substitutes for traditional approaches, as well as they are capable of exploring phenomena that could not be addressed hitherto. The intensity of research concerning experiments with biometric measurements is discussed too; a particular focus of the final discussion is the individuation of obstacles that prevent them from becoming commonplace in design research.

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Section: Limitationsmentioning

confidence: 99%

Review of the use of neurophysiological and biometric measures in experimental design research

Borgianni

Maccioni

2020

AIEDAM

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“…The film clips for each emotion were randomly chosen for emotion elicitation. After emotion elicitation experiments, we applied Pick-A-Mood (PAM) [5] as a tool of emotional state measure.…”

Section: Experimental Designmentioning

confidence: 99%

Interactive Robot Learning for Multimodal Emotion Recognition

Tapus

2019

Lecture Notes in Computer Science

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Interaction plays a critical role in skills learning for natural communication. In human-robot interaction (HRI), robots can get feedback during the interaction to improve their social abilities. In this context, we propose an interactive robot learning framework using multimodal data from thermal facial images and human gait data for online emotion recognition. We also propose a new decision-level fusion method for the multimodal classification using Random Forest (RF) model. Our hybrid online emotion recognition model focuses on the detection of four human emotions (i.e., neutral, happiness, angry, and sadness). After conducting offline training and testing with the hybrid model, the accuracy of the online emotion recognition system is more than 10% lower than the offline one. In order to improve our system, the human verbal feedback is injected into the robot interactive learning. With the new online emotion recognition system, a 12.5% accuracy increase compared with the online system without interactive robot learning is obtained.

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“…A limited number of pictorial instruments has been developed in the domain of HCI. ese instruments are exclusively dedicated to the measurement of emotion or mood, such as SAM (Self Assessment Manikin; [7]), PREMO (Product Emotion Measurement Tool; [16]), PAM (Pick-A-Mood; [18]), LEMtool (Layered Emotion Measurement Tool; [13]) and AniSAM/AniAvatar [57]. With regard to usability, a pictorial single-item scale has been developed recently [4].…”

Section: Pictorial Usability Estionnairesmentioning

confidence: 99%

Pictorial System Usability Scale (P-SUS)

Baumgartner

Frei

Kleinke

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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We have developed a pictorial multi-item scale, called P-SUS (Pictorial System Usability Scale), which aims to measure the perceived usability of mobile devices. The scale is based on the established verbal usability questionnaire SUS (System Usability Scale). A usercentred design process was employed to develop and refine its 10 pictorial items. The scale was tested in a first validation study (N=60) using student participants. Psychometric properties (convergent validity, criterionrelated validity, sensitivity, and reliability), as well as the motivation to fill in the scale were assessed. The results indicated satisfactory convergent validity for about twothirds of the items. Furthermore, strong correlations were obtained for the sum scores between verbal and pictorial SUS, and the pictorial scale was perceived as more motivating than the verbal questionnaire. The P-SUS represents a first attempt to provide a pictorial usability scale for the evaluation of (mobile) devices.

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Mood measurement with Pick-A-Mood: review of current methods and design of a pictorial self-report scale

Cited by 96 publications

References 40 publications

Review of the use of neurophysiological and biometric measures in experimental design research

Review of the use of neurophysiological and biometric measures in experimental design research

Interactive Robot Learning for Multimodal Emotion Recognition

Pictorial System Usability Scale (P-SUS)

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