Session: ASME Undergraduate Student Design Expo

Paper Number: 173339

Portable Readout System for Electrochemical Biosensor for Alzheimer’s Disease Biomarkers Detection in Point-of-Care Settings 

With more than six million Americans currently living with Alzheimer’s disease (AD), early diagnosis is essential for initiating therapeutic interventions and improving patient outcomes. However, the existing clinical diagnostic tools such as magnetic resonance imaging (MRI) and positron emission tomography (PET) are expensive, time consuming, and often inaccessible, especially in community clinics and resource limited settings. These limitations underscore the urgent need for affordable, accessible, and portable point-of-care (POC) diagnostic technologies capable of detecting AD related biomarkers at early stages of the disease. Electrochemical biosensors, particularly capacitive biosensors, have emerged as promising candidates for early and quantitative detection of biomarkers such as amyloid beta 42 (Aβ-42), which is strongly associated with the progression of Alzheimer’s disease. Capacitive biosensors offer advantages including label-free detection, high sensitivity, and low power consumption. However, their application in POC settings remains limited due to the reliance on bulky and costly laboratory instruments such as LCR meters for signal readout and analysis.

To address this challenge, this study presents the development of a compact, low-cost electrochemical reader specifically designed for capacitive biosensors. The system is built using an Arduino microcontroller integrated with a resistor capacitor (RC) circuit, which is engineered to detect real time changes in capacitance during electrochemical immunoassay measurements. It is implemented within a microfluidic based multiplex biosensing platform that uses interdigitated electrodes to transduce signals resulting from antigen and antibody binding events related to AD biomarkers. By monitoring capacitance continuously, the system enables real time analysis of antigen and antibody binding kinetics, which can significantly improve the sensitivity, specificity, and reproducibility of label-free immunoassays. Initial validation experiments were performed using bare interdigitated electrodes to evaluate the system’s reliability for capacitance measurement. Although Arduino’s basic setup was capable of detecting capacitance changes, it exhibited difficulty in consistently measuring small signal variations, suggesting a need for enhanced signal resolution and circuit optimization. To overcome this challenge, the RC circuit was redesigned by testing multiple resistor values to increase sensitivity to small capacitance changes. In parallel, the timing and signal processing in the Arduino code were adjusted to improve signal resolution. Through iterative hardware and software adjustments, the system’s ability to detect low-level capacitance changes was enhanced. The results demonstrate the feasibility of transitioning capacitive biosensing from laboratory settings to portable diagnostic applications.

Future work will focus on improving circuit design, refining embedded code, and integrating functionalized biosensors to enhance sensitivity and stability. This research contributes to the development of an accessible point-of-care diagnostic platform for early detection of Alzheimer’s disease and can be expanded for other electrochemical biosensors for a wide variety of diseases detection, which broaden the applications of point-of-care testing techniques.

Presenting Author: Sachi Rele New Jersey Institute of Technology

Presenting Author Biography: Sachi Rele is an undergraduate junior majoring in Mechanical Engineering at the New Jersey Institute of Technology (NJIT) and an Honors College student. She conducts undergraduate research in the Advanced Energy Systems and Microdevices Laboratory, where her work focuses on developing portable diagnostic technologies and microfluidic-based biosensing systems. Her academic interests combine mechanical engineering, biomedical devices, and sustainabililty.

Authors:

Sachi Rele New Jersey Institute of Technology
Yudong Wang Georgia Institute of Technology
Eon Soo Lee New Jersey Institute of Technology