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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Stretchable and self-adhesive triboelectric sensor for re...
Cai Lin, Yunyi Ding, Kai Lin, Ru Wang, Yichen Luo, Xiaofen Wu · 2025-08-05 · via eess.SP updates on arXiv.org

Recent advances in medical diagnostics have highlighted the importance of wearable technologies for continuous and real-time physiological monitoring. In this study, we introduce a flexible, self-powered triboelectric nanogenerator (MB-TENG) engineered from commercially available medical elastic bandages for biomechanical sensing during rehabilitation and gait analysis. Leveraging the porous and skin-friendly properties of the bandage combined with a PTFE film, the MB-TENG delivers robust electrical performance, achieving a peak open-circuit voltage (VOC) of 122~V, a short-circuit current (ISC) of 25~$μ$A, and a transferred charge (QSC) of 110~nC, while maintaining long-term stability across 40{,}000 mechanical cycles. Its inherent self-adhesive property allows for multi-layer assembly without extra bonding agents, and mechanical stretching enhances output, enabling dual configurability. A stacked design further improves the power capacity, supporting applications in wearable medical electronics. The MB-TENG device seamlessly conforms to joint surfaces and foot regions, providing accurate detection of motion states and abnormal gait patterns. These features underscore the MB-TENG's potential as a low-cost, scalable platform for personalized rehabilitation, injury monitoring, and early musculoskeletal diagnosis.