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Author: 15736

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ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training

Prolonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive systems. Existing posture sensing methods such as vision-based or wearable approaches face limitations including occlusion, privacy concerns, use…

Lala Shakti Swarup Ray et al.German Research Center for Artificial Intelligence

iBreath: Usage of Breathing Gestures as Means of Interactions

Breathing is a spontaneous but controllable body function that can be used for hands-free interaction. Our work introduces ``iBreath'', a novel system to detect breathing gestures similar to clicks using bio-impedance. We evaluated iBreath's accuracy and user experience using two lab studies (n=34). Our results show…

Mengxi Liu et al.German Research Center for Artificial Intelligence

LLMs Enable Context-Aware Augmented Reality in Surgical Navigation

Wearable Augmented Reality (AR) technologies are gaining recognition for their potential to transform surgical navigation systems. As these technologies evolve, selecting the right interaction method to control the system becomes crucial. Our work introduces a voice user interface (VUI) for surgical AR assistance syst…

Hamraz Javaheri et al.German Research Center for Artificial Intelligence

From Concept to Clinic: Multidisciplinary Design, Development, and Clinical Validation of Augmented Reality-Assisted Open Pancreatic Surgery

Wearable augmented reality (AR) systems have significant potential to enhance surgical outcomes through in-situ visualization of patient-specific data. Yet, efforts to develop AR-based systems for open surgery have been limited, lacking comprehensive interdisciplinary research and actual clinical evaluations in real s…

Hamraz Javaheri et al.German Research Center for Artificial Intelligence

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iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets

This work proposes an incremental learning (IL) framework for wearable sensor human activity recognition (HAR) that tackles two challenges simultaneously: catastrophic forgetting and non-uniform inputs. The scalable framework, iKAN, pioneers IL with Kolmogorov-Arnold Networks (KAN) to replace multi-layer perceptrons a…

Mengxi Liu et al.German Research Center for Artificial Intelligence

Enhancing Inertial Hand based HAR through Joint Representation of Language, Pose and Synthetic IMUs

Due to the scarcity of labeled sensor data in HAR, prior research has turned to video data to synthesize Inertial Measurement Units (IMU) data, capitalizing on its rich activity annotations. However, generating IMU data from videos presents challenges for HAR in real-world settings, attributed to the poor quality of s…

Vitor Fortes Rey et al.German Research Center for Artificial Intelligence

Head ’n Shoulder: Gesture-Driven Biking Through Capacitive Sensing Garments to Innovate Hands-Free Interaction

Distractions caused by digital devices are increasingly causing dangerous situations on the road, particularly for more vulnerable road users like cyclists. While researchers have been exploring ways to enable richer interaction scenarios on the bike, safety concerns are frequently neglected and compromised. In this w…

Daniel Geißler et al.German Research Center for Artificial Intelligence

Ghost Readers of the Nile: Decrypting Password Sharing Habits in Chatting Applications among Egyptian Women

Password sharing is a convenient means to access shared resources, save on subscription costs, provide emergency access, and avoid forgetting vital account details. However, it also raises significant privacy concerns, especially in digital communication contexts where content may be inadvertently exposed to unintende…

Mennatallah Saleh et al.Technical University of Berlin

Quali-Mat: Evaluating the Quality of Execution in Body-Weight Exercises with a Pressure Sensitive Sports Mat

While sports activity recognition is a well studied subject in mobile, wearable and ubiquitous computing, work to date mostly focuses on recognition and counting of specific exercise types. Quality assessment is a much more difficult problem with significantly less published results. In this work, we present Quali-Mat…

Bo Zhou et al.German Research Center for Artificial Intelligence

MoCaPose: Motion Capturing with Textile-integrated Capacitive Sensors in Loose-fitting Smart Garments

"We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable IMU MoCap based on inverse dynamics, MoCaPose decouples the sens…

Bo Zhou et al.German Research Center for Artificial Intelligence

Selecting the Motion Ground Truth for Loose-fitting Wearables: Benchmarking Optical MoCap Methods

To help smart wearable researchers choose the optimal ground truth methods for motion capturing (MoCap) for all types of loose garments, we present a benchmark, DrapeMoCapBench (DMCB), specifically designed to evaluate the performance of optical marker-based and marker-less MoCap. High-cost marker-based MoCap systems…

Lala Shakti Swarup Ray et al.German Research Center for Artificial Intelligence

Paper Title	Authors	Research Topics	Paper Database	Year
ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training Prolonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive systems. Existing posture sensing methods such as vision-based or wearable approaches face limitations including occlusion, privacy concerns, use…	LR Lala Shakti Swarup Ray et al.German Research Center for Artificial Intelligence
iBreath: Usage of Breathing Gestures as Means of Interactions Breathing is a spontaneous but controllable body function that can be used for hands-free interaction. Our work introduces ``iBreath'', a novel system to detect breathing gestures similar to clicks using bio-impedance. We evaluated iBreath's accuracy and user experience using two lab studies (n=34). Our results show…	ML Mengxi Liu et al.German Research Center for Artificial Intelligence
emoji_events LLMs Enable Context-Aware Augmented Reality in Surgical Navigation Wearable Augmented Reality (AR) technologies are gaining recognition for their potential to transform surgical navigation systems. As these technologies evolve, selecting the right interaction method to control the system becomes crucial. Our work introduces a voice user interface (VUI) for surgical AR assistance syst…	HJ Hamraz Javaheri et al.German Research Center for Artificial Intelligence
From Concept to Clinic: Multidisciplinary Design, Development, and Clinical Validation of Augmented Reality-Assisted Open Pancreatic Surgery Wearable augmented reality (AR) systems have significant potential to enhance surgical outcomes through in-situ visualization of patient-specific data. Yet, efforts to develop AR-based systems for open surgery have been limited, lacking comprehensive interdisciplinary research and actual clinical evaluations in real s…	HJ Hamraz Javaheri et al.German Research Center for Artificial Intelligence
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets This work proposes an incremental learning (IL) framework for wearable sensor human activity recognition (HAR) that tackles two challenges simultaneously: catastrophic forgetting and non-uniform inputs. The scalable framework, iKAN, pioneers IL with Kolmogorov-Arnold Networks (KAN) to replace multi-layer perceptrons a…	ML Mengxi Liu et al.German Research Center for Artificial Intelligence
Enhancing Inertial Hand based HAR through Joint Representation of Language, Pose and Synthetic IMUs Due to the scarcity of labeled sensor data in HAR, prior research has turned to video data to synthesize Inertial Measurement Units (IMU) data, capitalizing on its rich activity annotations. However, generating IMU data from videos presents challenges for HAR in real-world settings, attributed to the poor quality of s…	VR Vitor Fortes Rey et al.German Research Center for Artificial Intelligence
Head ’n Shoulder: Gesture-Driven Biking Through Capacitive Sensing Garments to Innovate Hands-Free Interaction Distractions caused by digital devices are increasingly causing dangerous situations on the road, particularly for more vulnerable road users like cyclists. While researchers have been exploring ways to enable richer interaction scenarios on the bike, safety concerns are frequently neglected and compromised. In this w…	DG Daniel Geißler et al.German Research Center for Artificial Intelligence
Ghost Readers of the Nile: Decrypting Password Sharing Habits in Chatting Applications among Egyptian Women Password sharing is a convenient means to access shared resources, save on subscription costs, provide emergency access, and avoid forgetting vital account details. However, it also raises significant privacy concerns, especially in digital communication contexts where content may be inadvertently exposed to unintende…	MS Mennatallah Saleh et al.Technical University of Berlin
Quali-Mat: Evaluating the Quality of Execution in Body-Weight Exercises with a Pressure Sensitive Sports Mat While sports activity recognition is a well studied subject in mobile, wearable and ubiquitous computing, work to date mostly focuses on recognition and counting of specific exercise types. Quality assessment is a much more difficult problem with significantly less published results. In this work, we present Quali-Mat…	BZ Bo Zhou et al.German Research Center for Artificial Intelligence
MoCaPose: Motion Capturing with Textile-integrated Capacitive Sensors in Loose-fitting Smart Garments "We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable IMU MoCap based on inverse dynamics, MoCaPose decouples the sens…	BZ Bo Zhou et al.German Research Center for Artificial Intelligence
Selecting the Motion Ground Truth for Loose-fitting Wearables: Benchmarking Optical MoCap Methods To help smart wearable researchers choose the optimal ground truth methods for motion capturing (MoCap) for all types of loose garments, we present a benchmark, DrapeMoCapBench (DMCB), specifically designed to evaluate the performance of optical marker-based and marker-less MoCap. High-cost marker-based MoCap systems…	LR Lala Shakti Swarup Ray et al.German Research Center for Artificial Intelligence