Search
3 articles for “soft biosensors”
-
Advances in Polymeric In Situ Drug Delivery and Soft Biosensors: Innovations in Biochemical Sensing and Personalized Healthcare
Abstract: Advanced healthcare and personalized medicine are undergoing a transformation thanks to in situ medication delivery systems and biochemical sensor technology. Polymeric in situ drug delivery systems form gels upon administration, releasing medications in a controlled manner and providing benefits such as ease of administration and enhanced patient compliance. Similarly, advancements in soft electronics, including flexible and stretchable biosensors, enable continuous, in situ biochemical monitoring, conforming to complex biological environments like …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 27–32 Read article
-
Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
-
Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article