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Devising a High-Level Command Language for the Teleoperation of Autonomous Vehicles

INTERNATIONAL JOURNAL OF human-COMPUTER INTERACTION 2025年第9期41卷 5299-5315页

作者： Tener, Felix Lanir, Joel Univ Haifa Informat Syst Haifa Israel

Autonomous vehicles (AVs) are rapidly evolving as a novel way of transportation. Nevertheless, there is a consensus that AVs cannot address all traffic scenarios independently. Consequently, there arises a need for remote human intervention. To pave the way for large-scale deployment of AVs onto public roadways, innovative models of remote operation must evolve. Such a paradigm is Tele-assistance, which posits that the low-level control of AVs should be delegated through high-level commands. Our work explores how such a command language should be constructed as a first step in designing a Tele-assistance user interface. Through interviews with 17 experienced teleoperators, we elicit a set of discrete commands that a remote operator can use to resolve various road scenarios. Subsequently, we create a scenario-command mapping and a thematic classification of the defined commands. Finally, we present an initial Tele-assistance interface design based on these commands.

关键词： human-centered computing human-computer interaction interaction design automobile empirical study elicitation study qualitative methods user interface design tele-driving tele-assistance

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mmTAA: A Contact-Less Thoracoabdominal Asynchrony Measurement System Based on mmWave Sensing

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IEEE TRANSACTIONS ON MOBILE computing 2025年第2期24卷 627-641页

作者： Zhang, Fenglin Zhang, Zhebin Kang, Le Zhou, Anfu Ma, Huadong Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Telecommun Software & Beijing 100876 Peoples R China

Thoracoabdominal Asynchrony (TAA) is a key metric in respiration monitoring, which characterizes the non-parallel periodical motion of human's rib cage (RC) and abdomen (AB) during each breath. Long-term measurement of TAA plays a significant role in respiration health tracking. Existing TAA measurement methods including Respiratory Inductive Plethysmography (RIP) and Optoelectronic Plethysmography (OEP) all intrusive to subjects and have certain requirements on operation conditions, which limit their usage to hospital scenario. To address this gap, we propose mmTAA, the first mmWave-based, non-intrusive TAA measurement system ready for ubiquitous usage in daily-life. In mmTAA, we design a Two-stage RC-AB centroid finding module, aiming to identify the most probable location of RC-AB centroid, which can best represent RC and AB in mmWave sensing scenario. Subsequently, we design TAANet, a novel Convolutional Neural Network (CNN)-based architecture with residual modules, tailored for TAA measurement. Meanwhile, in order to address the imbalance of continuous data, we add imbalance information equalizer including feature and label equalizer during network training. We implement mmTAA on a commonly used multi-antenna mmWave radar. We prototype, deploy and evaluate mmTAA on 25 subjects and 25.7h data in total. mmTAA achieves 4.01 degrees MAE and 1.56 degrees average error, close to OEP method.

关键词： Radar Millimeter wave communication Sensors Oscillators Mobile computing Equalizers Training Receivers Monitoring Cameras mmWave sensing thoracoabdominal asynchrony(TAA) human-centered computing

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A Survey on Deep Learning for Design and Generation of Virtual Architecture

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ACM computing SURVEYS 2025年第2期57卷 1-41页

作者： Wang, Anqi Dong, Jiahua Lee, Lik-hang Shen, Jiachuan Hui, Pan Hong Kong Univ Sci & Technol Hong Kong Peoples R China Hong Kong Univ Sci & Technol Guangzhou Campus Guangzhou Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China Hong Kong Polytech Univ Hong Kong Peoples R China UCL London England

Three-dimensional (3D) shape generation techniques leveraging deep learning have garnered significant interest from both computer vision and architectural design communities, promising to enrich the content in the virtual environment. However, research on virtual architectural design remains limited, particularly regarding designer-AI collaboration and deep learning-assisted design. In our survey, we reviewed 149 related articles (81.2% of articles published between 2019 and 2023) covering architectural design, 3D shape techniques, and virtual environments. Through scrutinizing the literature, we first identify the principles of virtual architecture and illuminate its current production challenges, including datasets, multimodality, design intuition, and generative frameworks. We then introduce the latest approaches to designing and generating virtual buildings leveraging 3D shape generation and summarize four characteristics of various approaches to virtual architecture. Based on our analysis, we expound on four research agendas, including agency, communication, user consideration, and integrating tools. Additionally, we highlight four important enablers of ubiquitous interaction with immersive systems in deep learning-assisted architectural generation. Our work contributes to fostering understanding between designers and deep learning techniques, broadening access to designer-AI collaboration. We advocate for interdisciplinary efforts to address this timely research topic, facilitating content designing and generation in the virtual environment.

关键词： human-centered computing Interaction design process and methods Virtual reality computing methodologies Machine learning Applied computing Architecture buildings

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Towards Better Utilization of Haptic Interaction in Visualization: Design Space and Knob Prototype

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INTERNATIONAL JOURNAL OF human-COMPUTER INTERACTION 2025年第9期41卷 5384-5405页

作者： Zhang, Gefei Sun, Guodao Sun, Zifeng Tang, Jingwei Jiang, Li Liang, Ronghua Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou Peoples R China

humans encounter a vast array of sensory stimuli in their everyday lives. However, many visualization techniques primarily utilize visual feedback, which may disregard certain intricate details. Relying on a single visual channel may overlook complex layouts. However, how haptic force feedback can be used to assist visualization remained under-explored. In this work, we initially conducted a literature review to identify potential problems in the visualization of large datasets and engaged in discussions with domain experts to explore the potential of haptic force feedback and visual collision representation. Subsequently, we designed an innovative haptic force feedback knob, which included 3 primary modules and 29 elements. To evaluate the clarity and usefulness of this design space, we conducted a workshop and devised "recommended solutions" for the identified visualization problems. Finally, we implemented a prototype of the haptic force feedback knob and assessed its performance on scatterplot and parallel coordinate plot tasks using large datasets. The results indicated that the knob prototype could reduce visual strain and enhance the efficiency of visualization tasks.

关键词： human-centered computing human-computer interaction User studies

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Synergistic grasp analysis: A cross-sectional exploration using a multi-sensory data glove

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WEARABLE TECHNOLOGIES 2025年 6卷 e2-e2页

作者： Pratap, Subhash Ito, Kazuaki Hazarika, Shyamanta M. IIT Guwahati Biomimet Robot & AI Lab Mech Engn Gauhati Assam India Gifu Univ Dept Intelligent Mech Engn Gifu Japan

This paper investigates hand grasping, a fundamental activity in daily living, by examining the forces and postures involved in the lift-and-hold phases of grasping. We introduce a novel multi-sensory data glove, integrated with resistive flex sensors and capacitive force sensors, to measure the intricate dynamics of hand movement. The study engaged five subjects to capture a comprehensive dataset that includes contact forces at the fingertips and joint angles, furnishing a detailed portrayal of grasp mechanics. Focusing on grasp synergies, our analysis delved into the quantitative relationships between the correlated forces among the fingers. By manipulating one variable at a time-either the object or the subject-our cross-sectional approach yields rich insights into the nature of grasp forces and angles. The correlation coefficients for finger pairs presented median values ranging from 0.5 to nearly 0.9, indicating varying degrees of inter-finger coordination, with the thumb-index and index-middle pairs exhibiting particularly high synergy. The findings, depicted through spider charts and correlation coefficients, reveal significant patterns of cooperative finger behavior. These insights are crucial for the advancement of hand mechanics understanding and have profound implications for the development of assistive technologies and rehabilitation devices.

关键词： grasp synergies multi-sensory data glove human-centered computing

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Trust dynamics in human interaction with an industrial robot

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BEHAVIOUR & INFORMATION TECHNOLOGY 2025年第2期44卷 266-288页

作者： Alhaji, Basel Buettner, Sebastian Sanjay Kumar, Shushanth Prilla, Michael Univ Duisburg Essen Fac Comp Sci Dept Human Centered Comp & Cognit Sci HCCS Interact Syst Duisburg Germany Tech Univ Clausthal Human Centered Informat Syst Clausthal Zellerfeld Germany Univ Duisburg Essen Fac Comp Sci Dept Human Centered Comp & Cognit Sci HCCS Interact Syst D-47057 Duisburg Germany

Trust is important for collaboration. In hybrid teams of humans and robots, trust enables smooth collaboration and reduces risks. Just as collaboration between humans and robots differs from interpersonal collaboration, so does the nature of trust in human-robot interaction (HRI). Therefore, further investigations on trust formation and dissolution in HRI, factors affecting it, and means for keeping trust on an appropriate level are needed. However, our knowledge of interpersonal trust and trust in autonomous agents cannot be transferred directly to HRI. In this paper, we present a study with 32 participants on trust formation and dissolution as well as forecasting to influence trust in an industry robot. Results show differences in dynamics and factors of trust formation and dissolution. Additionally, we find that the effect of forecasting on trust depends on task success. These findings support the design of trustful human-robot interaction and corresponding robotic team members.

关键词： human-centered computing human computer interaction (HCI) Empirical studies in HCI human-Robot Interaction Industrial Robot Trust Trust Dynamics Collaboration

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Heuristics for evaluating narrative visualization: a validation study

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JOURNAL OF VISUALIZATION 2025年 1-15页

作者： Errey, Nina Zowghi, Didar Leong, Tuck Wah Wu, Yadong Yuan, Xiaoru Huang, Weidong Liang, Christy Jie UTS Sch Comp Sci Sydney NSW Australia CSIRO Data61 Sydney Australia RMIT Sch Comp Technol Melbourne Australia Sichuan Univ Sci & Engn Comp Sci & Engn Yibin Peoples R China Peking Univ Sch Intelligence Sci & Technol Beijing Peoples R China UTS Transdisciplinary Sch Sydney Australia

Narrative visualization integrates data visualization and narrative techniques to convey a compelling story. Narrative visualization is notoriously difficult to evaluate. One solution is heuristic evaluation, using a domain-specific set of heuristics. This paper validates a set of heuristics proposed specifically for evaluating narrative visualization. We conducted studies with experienced narrative visualization practitioners in both summative and formative settings. We found that the set of heuristics showed promise in a summative setting, where similar responses evidenced that the set of heuristics could provide reliable evaluation metrics. Furthermore, in a formative setting, implementing the set of heuristics was reported to be useful in the design process;however, due to their limited focus, we recommend that it be implemented in conjunction with other evaluation guidelines.

关键词： human-centered computing Information visualization Visualization Visualization application domains Empirical studies in visualization

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Layout-Agnostic human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2025年第1期9卷 1-38页

作者： Thukral, Megha Dhekane, Sourish gunesh Hiremath, Shruthi k. Haresamudram, Harish Ploetz, Thomas Georgia Inst Technol Sch Interact Comp Atlanta GA 30332 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA USA

human activity recognition (HAR) using ambient sensors in smart homes has numerous applications for human healthcare and wellness. However, building general-purpose HAR models that can be deployed to new smart home environments requires a significant amount of annotated sensor data and training overhead. Most smart homes vary significantly in their layouts, i.e., floor plans and the specifics of sensors embedded, resulting in low generalizability of HAR models trained for specific homes. We address this limitation by introducing a novel, layout-agnostic modeling approach for HAR systems in smart homes that utilizes the transferrable representational capacity of natural language descriptions of raw sensor data. To this end, we generate Textual Descriptions Of Sensor Triggers (TDOST) that encapsulate the surrounding trigger conditions and provide cues for underlying activities to the activity recognition models. Leveraging textual embeddings, rather than raw sensor data, we create activity recognition systems that predict standard activities across homes without (re-)training or adaptation to target homes. Through an extensive evaluation, we demonstrate the effectiveness of TDOST-based models in unseen smart homes through experiments on benchmark Orange4Home and CASAS datasets. Furthermore, we conduct a detailed analysis of how the individual components of our approach affect downstream activity recognition performance.

关键词： human-centered computing Ubiquitous and mobile computing Empirical studies in ubiquitous and mobile computing computing methodologies Machine learning

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ARive: Assisting Drivers with In-Car Augmented Reality for Risk Zone Detection

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2025年第1期9卷 1-27页

作者： Wang, Chao Chu, Derck Martens, Marieke Honda Res Insititue EU Offenbach Germany Eindhoven Univ Technol Eindhoven Netherlands

human factors such as fatigue and distraction often impair drivers' ability to gauge traffic dynamics, leading to collisions, especially at unsignalized intersections. Augmented reality (AR) technology, particularly through advanced 3D projections and wearable head-mounted displays (HMDs), offers a promising enhancement by integrating comprehensive environmental awareness directly into the driver's field of view. This paper presents "ARive," an innovative AR driver-assistance system designed to improve road safety by projecting dynamic risk zones beneath other traffic participants, thus providing real-time kinematic information to promote safer driving distances and informed decision-making. The research involved developing two distinct AR designs and testing them using a fixed-base driving simulator with integrated real-time data communication. A user study with 17 participants revealed that while AR projections significantly improve distance maintenance, particularly in abrupt braking scenarios, they do not markedly affect brake response times or enhance safety during critical events. These findings suggest the need for further optimization of AR design elements to maximize effectiveness, highlighting the potential of AR in enhancing driver awareness and safety.

关键词： human-centered computing Mixed / augmented reality

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MagKey: Empowering Wearables with Ballistocardiography-based Key Generation through Magnetic Field Vibration Sensing

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2025年第1期9卷 1-28页

作者： Huang, Junying Guo, Xiuzhen Gu, Chaojie Miao, Yuchen He, Shibo Shu, Yuanchao Chen, Jiming Zhejiang Univ Hangzhou Peoples R China

JIMING Zhejiang University, Symmetric key generation based on biometrics has emerged as a promising solution for wearables pairing. Among various biometrics, heartbeats offer significant potential owing to their inherent randomness and spontaneity. Ballistocardiography (BCG), in particular, stands out for its accessibility and inclusivity, as it measures the body's recoil forces in response to cardiac blood ejection into the vasculature. However, traditional approaches to BCG suffer from challenges in sensing on wearables and limited key generation rates. To this end, this paper presents MagKey, a system that enables wearables with BCG-based key generation. MagKey overcomes the difficulties in effective BCG sensing by translating skin vibration caused by recoil forces into magnetic field vibration (MFV). Moreover, MagKey demonstrates that the peak-to-peak trend (PPT) of MFV signals can reliably extract keys, and thus improve the key generation rate. To mitigate the impact of noise and motion artifacts on key generation, MagKey employs analog filters and a peak screening method for signal processing. We implement MagKey on a one-layer flexible printed circuit (FPC) and a two-layer printed circuit board (PCB). Extensive experiments show the usability and effectiveness of MagKey. Furthermore, our security analyses illustrate the scheme's resilience against potential attacks.

关键词： human-centered computing Ubiquitous and mobile computing systems and tools Security and privacy Authentication Computer systems organization Embedded and cyber-physical systems

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