Jinying Tu

ORCID: 0009-0009-5740-9142
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About
Contact & Profiles
Research Areas
  • Microfluidic and Capillary Electrophoresis Applications
  • Sleep and Work-Related Fatigue
  • Knee injuries and reconstruction techniques
  • Obstructive Sleep Apnea Research
  • Advanced Sensor and Energy Harvesting Materials
  • Sleep and related disorders
  • Adhesion, Friction, and Surface Interactions
  • Electrowetting and Microfluidic Technologies
  • Innovative Microfluidic and Catalytic Techniques Innovation

Tsinghua University
2023-2025

Tendon and ligament ruptures are prevalent, severe sports injuries require surgical repair. In clinical practice, monitoring of tissue strain is critical to alert postoperative complications such as graft reinjury loosening. Here, we present a sensor system that integrates communication coil onto silk sutures, enabling in situ wireless readout strains via implantation. The flexible shows excellent adaptability soft tissues, providing range 0 10% with minimum detection threshold 0.25%...

10.1126/sciadv.adt3811 article EN cc-by-nc Science Advances 2025-02-28

In bioanalysis, precisely isolating liquid reactions in distinct systems or at different temporal sequences is vital for ensuring accurate results devoid of crosstalk. However, passive isolation unattainable through existing microfluidic valves. Here, bridge cutting valves (LBCVs) are introduced to automatically segregate liquids by establishing airlocks, offering an innovative structure distribution. The principle breakup studied and applied the design LBCVs. Additionally, monolithic chips...

10.1002/smll.202411708 article EN Small 2025-03-09

This work proposes a method utilizing oxygen saturation (SpO2) for predicting incident hypertension in patients with obstructive sleep apnea (OSA). We extracted time domain features and frequency from the SpO2 signal. For prediction, we employed several machine learning algorithms to establish 3-year risk prediction model Chinese Sleep Health Study, including 250 subjects without baseline who underwent monitoring. The proposed random forest achieved an accuracy of 84.4%, sensitivity 77.0%,...

10.1109/embc40787.2023.10340756 article EN 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2023-07-24
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