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Systematic comparison between a research-grade EEG device and a consumer-grade BCI device for predicting consumer preference using an ML framework

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Multimedia Tools and Applications 2025年 1-19页

作者： Ishtiaque, Farhan Miya, Mohammad Tohidul Islam Mashrur, Fazla Rabbi Rahman, Khandoker Mahmudur Vaidyanathan, Ravi Anwar, Syed Ferhat Sarker, Farhana Tat, Huam Hon Hamid, Abu Bakar Abdul Mamun, Khondaker A. AIMS Lab IIRIC UIU Dhaka Bangladesh School of Business and Economics United International University Dhaka Bangladesh Department of Biomedical Engineering University of Rochester RochesterNY United States Department of Mechanical Engineering Imperial College London London United Kingdom Office of the Vice Chancellor BRAC University Dhaka Bangladesh and Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Faculty of Business City University of Macau Taipa China Faculty of Business Information & Human Sciences Infrastructure University Kuala Lumpur Kuala Lumpur Malaysia Department of CSE United International University Dhaka Bangladesh

Evaluation of marketing stimuli such as static advertisements, video advertisements, promotions, etc. is an important part of marketing research. Traditionally, the evaluation is done through large surveys, focus group discussions, questioner-based surveys, etc. However, these methods are time-consuming and expensive. Here, neuromarketing offers a solution that can improve marketing research. Recently, several EEG-based neuromarketing studies proved the potential of neuromarketing as a marketing research tool. However, most of these researchers used research-grade EEG devices. Research-grade EEG devices are bulky and require high setup time. This is why, despite much successful research, the technology is yet to be implemented on a day-to-day basis. On the other hand, consumer-grade BCI devices are cheap, wearable, and offer little to no setup time. So, it is ideal for day-to-day implementation. However, consumer-grade BCI lacks in terms of signal quality and available channel number, and it has not been widely tested in neuromarketing. So, in this study, we compared a research-grade EEG device and a consumer-grade BCI device for consumers’ preference prediction using a machine learning framework. We designed an experiment to record participants' EEG data while they were shown marketing stimuli. Their response has been taken as affective attitude (AA) purchase intention (PI). After that, binary classification was performed. We achieved 80.71% and 82.07% accuracy for predicting purchase intention and affective attitude using the research-grade EEG device, whereas it was 78.31% and 81.23% using the consumer-grade BCI device. These findings prove that consumer-grade BCI can be a viable option for day-to-day usage in neuromarketing. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Sales

AnyTSR: Any-Scale Thermal Super-Resolution for UAV

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arXiv 2025年

作者： Li, Mengyuan Fu, Changhong Lu, Ziyu Zhang, Zijie Zuo, Haobo Yao, Liangliang School of Mechanical Engineering Tongji University Shanghai201804 China Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Tongji University Shanghai201804 China Department of Computer Science University of Hong Kong Hong Kong999077 Hong Kong

Thermal imaging can greatly enhance the application of intelligent unmanned aerial vehicles (UAV) in challenging environments. However, the inherent low resolution of thermal sensors leads to insufficient details and blurred boundaries. Super-resolution (SR) offers a promising solution to address this issue, while most existing SR methods are designed for fixed-scale SR. They are computationally expensive and inflexible in practical applications. To address above issues, this work proposes a novel any-scale thermal SR method (AnyTSR) for UAV within a single model. Specifically, a new image encoder is proposed to explicitly assign specific feature code to enable more accurate and flexible representation. Additionally, by effectively embedding coordinate offset information into the local feature ensemble, an innovative any-scale upsampler is proposed to better understand spatial relationships and reduce artifacts. Moreover, a novel dataset (UAV-TSR), covering both land and water scenes, is constructed for thermal SR tasks. Experimental results demonstrate that the proposed method consistently outperforms state-of-the-art methods across all scaling factors as well as generates more accurate and detailed high-resolution images. The code is located at https:// ***/vision4robotics/AnyTSR. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

Evaluating the Benefits of the Immersive Space to Think

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Evaluating the Benefits of the Immersive Space to Think

2020 IEEE Conference on Virtual Reality and 3D User Interfaces, VRW 2020

作者： Lisle, Lee Chen, Xiaoyu Edward Gitre, J.K. North, Chris Bowman, Doug A. Center for Human-Computer Interaction Department of Computer Science Virginia Tech United States Virginia Tech Grado Department of Industrial and Systems Engineering United States Center for Human-Computer Interaction Department of History Virginia Tech United States

ISBN: (纸本)9781728165325

Sensemaking with large multimedia dataset is a cognitively intensive task that requires analysts to understand the underlying stories that the dataset tells. Often, analysts use tools in order to offload cognition as well as convey their new understanding of the dataset;however, existing tools are limited by their underlying technologies. We have proposed a novel virtual reality tool to support sensemaking called the Immersive Space to Think (IST). IST can aid the process of analyzing multimedia data, but it remains unproven whether IST improves sensemaking performance over a traditional desktop setting. In a study performed over six weeks, one participant used both IST and traditional methods of sensemaking with a dataset of 100 text documents of transcribed survey responses from World War 2 soldiers to perform historical analysis. The participant was asked guided questions that produced three essays with their understanding of the data. After conducting a blind evaluation of the participant's interpretation of the data, a team of three experts in historical analysis concluded that the essays written with IST displayed a better understanding of the dataset. Furthermore, the participant gave positive feedback on IST, and also suggested possible improvements. © 2020 IEEE.

关键词： Surveys

Virtual Reality for Health and Wellbeing 22

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Virtual Reality for Health and Wellbeing

21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022

作者： Ferreira-Brito, Filipa Gjoreski, Hristijan Mayora, Oscar Luštrek, Mitja Kizhevska, Emilija Guerreiro, João Gerling, Kathrin Bermúdez I Badia, Sergi Guerreiro, Tiago LASIGE Faculdade de Ciências da Universidade de Lisboa Portugal Ss. Cyril and Methodius University in Skopje Skopje Macedonia Center for Health and Wellbeing Fondazione Bruno Kessler Trento Italy Department of Intelligent Systems Jožef Stefan Institute Slovenia Slovenia Ss. Cyril and Methodius University in Skopje Macedonia KU Leuven Department of Computer Science Human-Computer Interaction Belgium Departamento de Engenharia Informatica and NOVA Laboratory for Computer Science and Informatics Universidade da Madeira Portugal and ARDITI Portugal

ISBN: (纸本)9781450398213

Virtual Reality (VR) has become a mainstream opportunity to develop immersive environments where people are exposed to relevant stimuli in a systematic but safe way. Besides the controlled exposure to stimuli, VR systems enable a more efficient and unbiased gathering of information with practical applications in diagnosis, intervention, and health monitoring processes. Nonetheless, scientific literature has demonstrated that interacting with VR technology and its peripherals can be challenging, especially in populations less familiar with technology (e.g., older adults) or with clinical conditions that are not adequately accommodated by the technology, such as cognitive (e.g., dementia) or physical impairments (e.g., blindness). This workshop will focus on systems, technological approaches, and theoretical frameworks to develop user/patient-centred VR tools for diagnosis, intervention, and monitoring of health and wellbeing outcomes. Moreover, we welcome work focused on accessibility issues, aiming to promote equal access and opportunity to use VR tools by people with diverse abilities. © 2022 ACM.

关键词： Virtual reality

PI-VIMO: PHYSIOLOGY-INSPIRED ROBUST VITAL SIGN MONITORING USING MMWAVE RADARS

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arXiv 2023年

作者： Zhang, Bo Jiang, Boyu Zheng, Rong Zhang, Xiaoping Li, Jun Xu, Qiang Dept. of Computing and Software McMaster University HamiltonON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Huawei Human Machine Interaction Lab MarkhamON Canada

Continuous monitoring of human vital signs using non-contact mmWave radars is attractive due to their ability to penetrate garments and operate under different lighting conditions. Unfortunately, most prior research requires subjects to stay at a fixed distance from radar sensors and to remain still during monitoring. These restrictions limit the applications of radar vital sign monitoring in real life scenarios. In this paper, we address these limitations and present Pi-ViMo, a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars. We first derive a multi-scattering point model for the human body, and introduce a coherent combining of multiple scatterings to enhance the quality of estimated chest-wall movements. It enables vital sign estimations of subjects at any location in a radar’s field of view (FoV). We then propose a template matching method to extract human vital signs by adopting physical models of respiration and cardiac activities. The proposed method is capable to separate respiration and heartbeat in the presence of micro-level random body movements (RBM) when a subject is at any location within the field of view of a radar. Experiments in a radar testbed show average respiration rate errors of 6% and heart rate errors of 11.9% for the stationary subjects, and average errors of 13.5% for respiration rate and 13.6% for heart rate for subjects under different RBMs. © 2023, CC BY.

关键词： Errors

Let's Influence Algorithms Together: How Millions of Fans Build Collective Understanding of Algorithms and Organize Coordinated Algorithmic Actions

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arXiv 2024年

作者： Xiao, Qing Zheng, Yuhang Fan, Xianzhe Zhang, Bingbing Lu, Zhicong Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States University of Amsterdam Amsterdam Netherlands Tsinghua University Beijing China School of Journalism and Mass Communication University of Iowa Iowa CityIA United States Department of Computer Science George Mason University FairfaxVA United States

Previous research pays attention to how users strategically understand and consciously interact with algorithms but mainly focuses on an individual level, making it difficult to explore how users within communities could develop a collective understanding of algorithms and organize collective algorithmic actions. Through a two-year ethnography of online fan activities, this study investigates 43 core fans who always organize large-scale fans collective actions and their corresponding general fan groups. This study aims to reveal how these core fans mobilize millions of general fans through collective algorithmic actions. These core fans reported the rhetorical strategies used to persuade general fans, the steps taken to build a collective understanding of algorithms, and the collaborative processes that adapt collective actions across platforms and cultures. Our findings highlight the key factors that enable computer-supported collective algorithmic actions and extend collective action research into the large-scale domain targeting algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Consensus algorithm

What Makes Im Users (Un)Responsive: An Empirical Investigation for Understanding Im Responsiveness

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SSRN

SSRN 2022年

作者： Lee, Hao-Ping Chiang, Yi-Shyuan Chou, Yu-Ling Lin, Kung-Pai Chang, Yung-Ju Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States Department of Computer Science University of Illinois Urbana-Champaign UrbanaIL United States

Instant messaging (IM) communication has been widely studied due to its prevalence in our everyday communication. Numerous factors that contribute to (un)responsiveness have been identified. Yet an integrated view of the factors that influence IM responsiveness remains absent. This paper reports qualitative findings from interviews with 46 IM users, and identifies five main elements underlying IM users’ response decisions: response habits, need fulfillment, perceived obligation, perceived readiness/suitability, and pace/rhythm coordination. To the best of our knowledge, this is the first integrated view of the key elements underlying IM responsiveness. Among these elements, we particularly highlight that regarding the influence of contextual factors on IM responsiveness, what may matters more is IM users’ perceptions of their readiness and suitability of the contexts, rather than the contexts’ objective properties. We also uncovered pace/rhythm coordination as a crucial factor behind IM responsiveness, which has been little discussed in the literature. Responsiveness, as our findings show, was often not a consequence, but a manifestation, of users’ pursuit of specific responsiveness-related aims such as ongoing shaping and sustaining of a dyad’s pace and rhythm. © 2022, The Authors. All rights reserved.

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Learning Co-Speech Gesture for Multimodal Aphasia Type Detection

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arXiv 2023年

作者： Lee, Daeun Son, Sejung Jeon, Hyolim Kim, Seungbae Han, Jinyoung Department of Applied Artificial Intelligence Sungkyunkwan University Seoul Korea Republic of Department of Human-AI Interaction Sungkyunkwan University Seoul Korea Republic of Department of Computer Science & Engineering University of South Florida TampaFL United States

Aphasia, a language disorder resulting from brain damage, requires accurate identification of specific aphasia types, such as Broca’s and Wernicke’s aphasia, for effective treatment. However, little attention has been paid to developing methods to detect different types of aphasia. Recognizing the importance of analyzing co-speech gestures for distinguish aphasia types, we propose a multimodal graph neural network for aphasia type detection using speech and corresponding gesture patterns. By learning the correlation between the speech and gesture modalities for each aphasia type, our model can generate textual representations sensitive to gesture information, leading to accurate aphasia type detection. Extensive experiments demonstrate the superiority of our approach over existing methods, achieving state-of-the-art results (F1 84.2%). We also show that gesture features outperform acoustic features, highlighting the significance of gesture expression in detecting aphasia types. We provide the codes for reproducibility purposes1 Copyright © 2023, The Authors. All rights reserved.

关键词： Damage detection

Designing Online Multiplayer Games with Haptically and Virtually Linked Tangible Robots to Enhance Social interaction in Therapy

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Designing Online Multiplayer Games with Haptically and Virtu...

IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Arzu Guneysu Ozgur Hala Khodr Mehdi Akeddar Michael Roust Pierre Dillenbourg Computer Human Interaction in Learning and Instruction Lab (CHILI) EPFL Lausanne Switzerland Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

The social aspects of therapy and training are important for patients to avoid social isolation and must be considered when designing a platform, especially for home-based rehabilitation. We proposed an online version of the previously proposed tangible Pacman game for upper limb training with haptic-enabled tangible Cellulo robots. Our main objective is to enhance motivation and engagement through social integration and also to form a gamified multiplayer rehabilitation at a distance. Thus, allowing relatives, children, and friends to connect and play with their loved ones while also helping them with their training from anywhere in the world. As well as connecting therapists to their patients through haptically linking capabilities. This is especially relevant when there are social distancing measures which might isolate the elderly population, a majority of all rehabilitation patients.

关键词： Training Pediatrics Sociology Medical treatment Games human factors Social factors