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oai:www.repository.cam.ac.uk:1810/3832462025-12-19T21:20:28Zcom_1810_213729com_1810_256065col_1810_219485

AI-assisted Development of Energy Harvesters for POCT https://doi.org/10.17863/CAM.117741 Kandukuri, Tharun Reddy 0009000630538102 Occhipinti, Luigi G This thesis, titled "AI-assisted Development of Energy Harvesters for POCT" investigates innovative energy harvesting technologies and neural network optimization to enhance design of pathogen detection and energy harvesting in biomedical applications. The work is centered on the design and validation of impedance spectroscopy-based biosensors that offer sensitive, and specific pathogen detection, crucial for timely healthcare interventions. A key component of this research is the multipotentiostat, a PCB board design incorporating four AFE chips that perform potentiostat operations like cyclic voltammetry simultaneously, with capabilities for Arduino Nano integration enabling both wired and wireless communication and data transfer. Additionally, the thesis explores piezoelectric energy harvesters, tailored to power these biosensors autonomously, addressing the limitations imposed by conventional power sources and promoting sustainability in medical devices. A significant contribution of this research is the development of a neural network-optimized framework that streamlines the process of designing and integrating these technologies effectively. The results demonstrate that integrating energy harvesting with optimized biosensor systems could significantly advance the field of portable and sustainable medical diagnostics, thereby offering robust tools for managing public health, particularly in resource-limited settings. This work not only furthers the development of autonomous biomedical devices but also sets the stage for future innovations in the integration of renewable energy solutions in medical technology. University of Cambridge 2024-12-21 Thesis Doctoral Doctor of Philosophy (PhD) eng https://www.repository.cam.ac.uk/handle/1810/383246 https://www.repository.cam.ac.uk/bitstreams/0cb2c475-3425-496b-83f5-8ced0199b6ae/download 87eda9de84448d1f82354d60eee3eb5f https://www.repository.cam.ac.uk/bitstreams/4198fbdf-f71b-4e90-abff-d354182c957d/download 679abf135454aed8aa974da9d87a1585 http://purl.org/NET/rdflicense/allrightsreserved Biomedical Devices Energy Harvesters Point of care Optimisation Algorithms