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Recent advancements in wearable robots have focused on developing soft, compliant, and lightweight structures to provide comfort for the users and to achieve the primary function of assisting body motions. The interaction forces induced by physical human-robot interaction (pHRI) not only cause skin discomfort or pain due to relatively high localized pressures but also degrade the wearability and the safety of the wearer's joints by unnaturally altering the joint reaction forces (JRFs) and the joint reaction moments (JRMs). Although the correlation between excessive JRFs/JRMs and joint-related conditions has been reported by researchers, the biomechanical effects of forces and moments caused by the pHRI of a wearable robot on the wearer's joints remain under-analyzed. In this study, we propose a method of measuring and analyzing these interactions and effects, using a custom-designed soft, three-degree-of-freedom (DOF) force sensor. The sensor is made of four Hall effect sensors and a neodymium magnet embedded in a silicone elastomer structure, enabling simultaneous measurement of normal and two-axis shear forces by detecting the distance changes between the magnet and each Hall effect sensor. These sensors are embedded in contact pads of a commercial wearable robot and measure the interaction forces, used for calculating JRF and JRM. We also propose a modified inverse dynamics approach that allows us to consider the physical interactions between the robot and the human body. The proposed method of sensing and analysis provides the potential to enhance the design of future wearable robots, ensuring long-term safety.
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http://dx.doi.org/10.1017/wtc.2025.10014 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712.
Many soft, tough materials have emerged in recent years, paving the way for advances in wearable electronics, soft robotics, and flexible displays. However, understanding the interfacial fracture behavior of these materials remains a significant challenge, owing to the difficulty of quantifying the respective contributions from viscoelasticity and damage to energy dissipation ahead of cracks. This work aims to address this challenge by labeling a series of polymer networks with fluorogenic mechanophores, subjecting them to T-peel tests at various rates and temperatures, and quantifying their force-induced damage using a confocal microscope.
View Article and Find Full Text PDFNanomicro Lett
September 2025
Nanomaterials & System Lab, Major of Mechatronics Engineering, Faculty of Applied Energy System, Jeju National University, Jeju, 63243, Republic of Korea.
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring, clinical diagnosis, and robotic applications. Nevertheless, it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility, adhesion, self-healing, and environmental robustness with excellent sensing metrics. Herein, we report a multifunctional, anti-freezing, self-adhesive, and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes (CoN CNT) embedded in a polyvinyl alcohol-gelatin (PVA/GLE) matrix.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, 510641, China.
Recently, flexible airflow sensors have attracted significant attention due to their impressive characteristics and capabilities for airflow sensing. However, the development of high-performance flexible airflow sensors capable of sensing airflow over large areas remains a challenge. In this work, it is proposed that a hair-like flexible airflow sensor, based on laser direct writing and electrostatic flocking, offers an efficient technology for airflow sensing.
View Article and Find Full Text PDFSmall
September 2025
State Key Laboratory of Flexible Electronics (LoFE) & Institute of Flexible Electronics (IFE), Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, 710072, P. R. China.
Flexible strain sensors are pivotal for the advancement of robotics, wearable healthcare, and human-machine interaction in the post-Moore era. However, conventional materials struggle to simultaneously achieve high sensitivity, a broad strain range, and low power consumption for cutting-edge applications. In this work, the issue is addressed through single crystal 1D tellurium nanoribbons (NRs), which are synthesized on SiO/Si substrate by hydrogen-assisted chemical vapor deposition (CVD) method.
View Article and Find Full Text PDFJ Imaging Inform Med
September 2025
Heart Center, Department of Geriatrics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
The growing heterogeneity of cardiac patient data from hospitals and wearables necessitates predictive models that are tailored, comprehensible, and safeguard privacy. This study introduces PerFed-Cardio, a lightweight and interpretable semi-federated learning (Semi-FL) system for real-time cardiovascular risk stratification utilizing multimodal data, including cardiac imaging, physiological signals, and electronic health records (EHR). In contrast to conventional federated learning, where all clients engage uniformly, our methodology employs a personalized Semi-FL approach that enables high-capacity nodes (e.
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