17 citations · 40 across the 31 of their papers we have counts for
31 papers
LITEWAY: LIghtweight HAR via Temporal Efficient highWAY
Dominique Nshimyimana, Vitor Fortes Rey, Mengxi Liu +2
Wearable human activity recognition (HAR) remains challenging due to the computational and energy constraints of deep learning models on resource-limited devices. Existing lightwei…
VSMP-IMU: Video-Grounded Semantic Motion Programs for Sensor-Aware Synthetic IMU Generation
Lala Shakti Swarup Ray, Vitor Fortes Rey, Mengxi Liu +2
Wearable human activity recognition (HAR) is often limited by the scarcity of labeled sensor data, especially in low-resource, class-imbalanced, and subject-generalization settings…
Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook
Sizhen Bian, Mengxi Liu, Lala Shakti Swarup Ray +7
Sensor-based Human Activity Recognition (HAR) underpins many ubiquitous and wearable computing applications, yet current models remain limited by scarce labels, sensor heterogeneit…
Embedded Inter-Subject Variability in Adversarial Learning for Inertial Sensor-Based Human Activity Recognition
Francisco M. Calatrava-Nicolás, Shoko Miyauchi, Vitor Fortes Rey +3
This paper addresses the problem of Human Activity Recognition (HAR) using data from wearable inertial sensors. An important challenge in HAR is the model's generalization capabili…
ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training
Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou +2
Prolonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive system…
On the Generalization Limits of Quantum Generative Adversarial Networks with Pure State Generators
Jasmin Frkatovic, Akash Malemath, Ivan Kankeu +7
We investigate the capabilities of Quantum Generative Adversarial Networks (QGANs) in image generations tasks. Our analysis centers on fully quantum implementations of both the gen…
TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices
Sizhen Bian, Mengxi Liu, Vitor Fortes Rey +2
Human Activity Recognition (HAR) on resource-constrained wearable devices demands inference models that harmonize accuracy with computational efficiency. This paper introduces Tini…
Combining Human-centred Explainability and Explainable AI
Janin Koch, Vitor Fortes Rey
This position paper looks at differences between the current understandings of human-centered explainability and explainability AI. We discuss current ideas in both fields, as well…
Boosting Classification with Quantum-Inspired Augmentations
Matthias Tschöpe, Vitor Fortes Rey, Sogo Pierre Sanon +3
Understanding the impact of small quantum gate perturbations, which are common in quantum digital devices but absent in classical computers, is crucial for identifying potential ad…
TxP: Reciprocal Generation of Ground Pressure Dynamics and Activity Descriptions for Improving Human Activity Recognition
Lala Shakti Swarup Ray, Lars Krupp, Vitor Fortes Rey +3
Sensor-based human activity recognition (HAR) has predominantly focused on Inertial Measurement Units and vision data, often overlooking the capabilities unique to pressure sensors…
PIM: Physics-Informed Multi-task Pre-training for Improving Inertial Sensor-Based Human Activity Recognition
Dominique Nshimyimana, Vitor Fortes Rey, Sungho Suh +2
Human activity recognition (HAR) with deep learning models relies on large amounts of labeled data, often challenging to obtain due to associated cost, time, and labor. Self-superv…
Hybrid CNN-Dilated Self-attention Model Using Inertial and Body-Area Electrostatic Sensing for Gym Workout Recognition, Counting, and User Authentification
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
While human body capacitance () has been explored as a novel wearable motion sensing modality, its competence has never been quantitatively demonstrated compared to that of th…
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
The passive body-area electrostatic field has recently been aspiringly explored for wearable motion sensing, harnessing its two thrilling characteristics: full-body motion sensitiv…
Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets
Daniel Geissler, Dominique Nshimyimana, Vitor Fortes Rey +3
The research of machine learning (ML) algorithms for human activity recognition (HAR) has made significant progress with publicly available datasets. However, most research priorit…
GenAI Assisting Medical Training
Stefan Fritsch, Matthias Tschoepe, Vitor Fortes Rey +4
Medical procedures such as venipuncture and cannulation are essential for nurses and require precise skills. Learning this skill, in turn, is a challenge for educators due to the n…
DisQu: Investigating the Impact of Disorder in Quantum Generative Models
Yannick Werner, Jasmin Frkatovic, Vitor Fortes Rey +5
Disordered Quantum many-body Systems (DQS) and Quantum Neural Networks (QNN) have many structural features in common. However, a DQS is essentially an initialized QNN with random w…
Sensor Data Augmentation from Skeleton Pose Sequences for Improving Human Activity Recognition
Parham Zolfaghari, Vitor Fortes Rey, Lala Ray +3
The proliferation of deep learning has significantly advanced various fields, yet Human Activity Recognition (HAR) has not fully capitalized on these developments, primarily due to…
MuJo: Multimodal Joint Feature Space Learning for Human Activity Recognition
Stefan Gerd Fritsch, Cennet Oguz, Vitor Fortes Rey +3
Human activity recognition (HAR) is a long-standing problem in artificial intelligence with applications in a broad range of areas, including healthcare, sports and fitness, securi…
Text me the data: Generating Ground Pressure Sequence from Textual Descriptions for HAR
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +3
In human activity recognition (HAR), the availability of substantial ground truth is necessary for training efficient models. However, acquiring ground pressure data through physic…
iMove: Exploring Bio-impedance Sensing for Fitness Activity Recognition
Mengxi Liu, Vitor Fortes Rey, Yu Zhang +3
Automatic and precise fitness activity recognition can be beneficial in aspects from promoting a healthy lifestyle to personalized preventative healthcare. While IMUs are currently…
Contrastive Left-Right Wearable Sensors (IMUs) Consistency Matching for HAR
Dominique Nshimyimana, Vitor Fortes Rey, Paul Lukowic
Machine learning algorithms are improving rapidly, but annotating training data remains a bottleneck for many applications. In this paper, we show how real data can be used for sel…
Worker Activity Recognition in Manufacturing Line Using Near-body Electric Field
Sungho Suh, Vitor Fortes Rey, Sizhen Bian +5
Manufacturing industries strive to improve production efficiency and product quality by deploying advanced sensing and control systems. Wearable sensors are emerging as a promising…
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps
Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou +2
We propose PressureTransferNet, a novel method for Human Activity Recognition (HAR) using ground pressure information. Our approach generates body-specific dynamic ground pressure…
Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition
Si Zuo, Vitor Fortes Rey, Sungho Suh +2
Human activity recognition (HAR) from on-body sensors is a core functionality in many AI applications: from personal health, through sports and wellness to Industry 4.0. A key prob…