Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Comparing The Predictions Of Convolutional Neural Networks, Random Forest Transfer Learning, And Support Vector Machines In The Image Processing Of Neoplasms, Ali A. Wallam

Caroliniana Undergraduate Research Journal

This study investigated the efficacy of Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forest Transfer Learning (RFTL) in the image processing of lung neoplasms for enhanced diagnostic accuracy. Leveraging the Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI), chest CT images were analyzed to compare the three models' performance. It was hypothesized that the most accurate predictions would result from the RFTL model because it would have the most efficient data processing. Results indicated that all three models demonstrated high accuracy, with CNNs excelling in precision, SVMs in recall, and RFTL showing a balanced performance. Precision-recall …

Biosensor Development In East Africa: A Systematic Review Of Technologies, Applications, Challenges, And Future Directions, Ally Mahadhy

Tanzania Journal of Science

Biosensors integrate biological recognition elements with signal transduction systems to generate quantitative or semi-quantitative analytical information and have applications across healthcare, food safety, agriculture, environmental monitoring, and wildlife health. Despite substantial global advances, biosensor development in East Africa remains poorly characterized. This systematic review, conducted according to PRISMA 2020 guidelines, evaluated published evidence from 1995 to 2025 within a predefined East African Community geographical scope. Eligibility was based on IUPAC-aligned operational criteria requiring an integrated biological recognition element, transduction mechanism, and quantitative or semi-quantitative signal output. Three locally developed biosensors met the criteria: an electrochemical nano-biosensor for schistosomiasis diagnosis in …

Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark

Master's Theses

Rehabilitation assessment often relies on periodic observation, while many XR prototypes show scripted rather than recorded-motion evidence. iD-MORE Vision is an offline pipeline trained on KIMORE and IRDS and linked through JSON packets to a two-mode Unity desktop prototype. Both datasets include controls and rehabilitation participants with neurologic, musculoskeletal, or mobility impairments. This improves relevance but does not clinically validate the system.

Under fixed subject-wise splits, the primary five-seed Random Forest predicted KIMORE clinician scores with MAE 6.087 ± 0.044 cTS and R² 0.568 ± 0.006; the subject-level R² interval crossed zero. The primary IRDS five-run CUDA GRU averaged 0.877 …

Evaluating Chest-Worn Light Logger Adherence: Development And Application Of A Wear/Non-Wear Model, Carlyn Patterson Gentile, Adah Thomas, Ryan Shah, Blanca Marquez De Prado, Nichelle Raj, Christina Szperka, Geoffrey Aguirre

Student Papers, Posters & Projects

Light exposure plays an important role in overall health because it entrains circadian rhythms. Recent technological advances in wearable light loggers allow measurement daily light exposure habits. Using a chest-worn light logger, our goal was to (1) develop methodology for differentiating adherent versus non-adherent use, and (2) define differences in lighting intensity in indoor and outdoor environments, to improve data reliability in future clinical studies using this technology. Four testers used a 10-channel chest worn light logging device under different conditions of wear and non-wear (experiment 1), and another tester made measurements with the light logger across a variety of …

Hyposense: Multimodal Physiologic And Voc Wearable For Early Hypoglycemia Detection, Nidhi R. Patel

Honors Theses

Hypoglycemia remains a significant safety concern for insulin-dependent individuals, especially when blood glucose declines rapidly during exercise, sleep, or periods of impaired hypoglycemia awareness. Current continuous glucose monitors and automated insulin delivery systems have helped to improve diabetes management, but these technologies primarily respond to glucose trends after they have already started and may not actually provide sufficient warning before symptoms occur. This thesis describes the development of HypoSense, a noninvasive wrist worn wearable concept that is designed to support earlier hypoglycemia risk detection through multimodal physiologic and volatile organic compound emission sensing. HypoSense combines volatile organic compounds/gas sensing with …

Spectral Characterization Of Colorectal Cancer Using Excitation-Scanning Hyperspectral Imaging, Natalie Hadad

Honors Theses

Colorectal cancer is one of the most common and deadly cancers worldwide, with a lifetime risk of approximately one in twenty-three for men and one in twenty-five for women. Although early detection significantly improves survival, current diagnostic approaches such as tissue biopsy are invasive, reliant on subjective interpretation, have extended turnaround times, and risk missing flat or depressed lesions that are more difficult to detect than raised polyps. These limitations highlight the need for objective, minimally invasive technologies capable of detecting early tissue changes. This study investigates excitation-scanning hyperspectral imaging (Ex-HSI) as a label-free optical approach for identifying colorectal cancer–associated …

An Investigation Of Data Granularity In Rag Pipelines For Personalized Medicine, Paritosh Pandey

Master's Theses

Generative AI, exemplified by large language models like the OpenAI GPT and Meta LLaMA families, can produce diverse content in response to prompts. This capability offers a promising solution to challenges in precision medicine, which seeks to tailor treatments to individual clinical profiles but often struggles with data collection, cost, and privacy concerns. By generating realistic, privacy-preserving patient data, generative AI has the potential to transform patient-centric healthcare. With such motivation, this research develops a comprehensive Generative AI pipeline emphasizing data granularity for accurate prediction of personalized treatments. The pipeline features a central Large Language Model interacting with a Machine …

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …

Robust Non-Invasive Cardiac Index Prediction Via Feature Integration And Data-Augmented Neural Networks, Chih-Hao Chang, Mei-Ling Chan, Yu-Hung Fang, Po-Lin Huang, Tsung-Yi Chen, Tsun-Kuang Chi, I Elizabeth Cha, Tzong-Rong Ger, Kuo-Chen Li, Shih-Lun Chen, Liang-Hung Wang, Jia-Ching Wang, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Concurrent with the rising consumption of ultra-processed, high-calorie diets and the decline in physical activity, obesity and related cardiovascular conditions among young adults have continued to increase, becoming an important global public health concern. This study integrates non-invasive Internet of Things (IoT) sensing devices, including the TERUMO ES-P2000 blood pressure monitor (Terumo Corp., Tokyo, Japan) and the PhysioFlow PF07 Enduro cardiac hemodynamic analyzer (Manatec Biomedical, Poissy, France), with an artificial neural network (ANN) for cardiac index (CI) prediction. Through appropriate data preprocessing and model training strategies, the generalization ability and stability of the proposed CI prediction model were significantly enhanced. …

Humanity Is Evolving Its Consciousness: The Role Of Archetypal Energies As Guides During An Unfolding Weeding Out And Alignment Process, Carroy U. Ferguson

Psychology Faculty Publication Series

Humanity is evolving its consciousness at individual and collective levels.  Given these seemingly tumultuous times, as of this writing (January 2026), to make such a statement may sound like a strange thing to say.  However, I suggest that if you are alive today and if you are reading these words, these are the very times for which you were born—to assist Humanity as it evolves its consciousness with your unique gifts, whatever they may be.  That is, this period of our individual and collective human being-ness may be characterized as an unfolding period of weeding out and alignment with the …

Wearable Biosensors For Continuous Monitoring Of Chronic Kidney Disease: Materials, Biofluids, And Digital Health Integration, Anupamaa Sivasubramanian, Shankara Narayanan, Gymama Slaughter

Center for Bioelectronics Publications

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

C. Difficile Detection Method For First Responder Glove Application, Alli N. Senedak

Williams Honors College, Honors Research Projects

Clostridioides Difficile (C. diff) is a Anaerobic Gram-positive bacillus that is capable of spore formation, making it difficult to control its spread and duration in clinical environments. This phenomenon can provide danger to first responders, healthcare workers, and patients. The goal of this project is to create a biosensor capable of detecting C. diff in a clinical setting that can be applied to a glove apparatus. The project will involve the use of C. diff aptamers activated on the surface of an electrode. Once surface activation has been verified via surface analysis, the electrodes will be exposed to C. diff …

Hyperglycemia Detection From Single-Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes need to measure their glucose levels in order to determine how much insulin or medicine …

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …

Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu

Electrical & Computer Engineering Faculty Publications

Bioceramics are important biomaterials in biomedical engineering because of their biocompatibility, bioactivity, osteoconductivity, and structural resemblance to actual bone tissue. In recent years, materials science and nanotechnology have enabled the use of bioceramics in bone regeneration, dental restoration, tissue engineering, drug delivery systems, and implantable medical devices. This comprehensive review covers advances in bioceramics, including calcium phosphates, hydroxyapatite (HAp), tricalcium phosphate, bioactive glasses, zirconia, alumina, and multifunctional ceramic nanocomposites. Priority is given to techniques such as additive manufacturing, 3D printing, sol-gel processing, electrospinning, and nanostructuring to improve mechanical strength, porosity, bioactivity, and cell interactions. Recent advances include ion doping, surface …

Consensus And Controversies Of International Guidelines For The Diagnosis, Surveillance, And Management Of Fetal Growth Restriction: An Updated Comparison, Daniele Diane Mascio, Suneet P. Chauhan, Tullio Ghi, Asma Khalil, Juliana G. Martins, Sara Sorrenti, Tamara Stampalija, Fabrizio Zullo, Francesc Figueras

Department of Obstetrics & Gynecology Faculty Publications

OBJECTIVE: To compare areas of consensus and disagreements across contemporary international and national guidelines on the diagnosis, surveillance, and management of fetal growth restriction (FGR).

DATA SOURCES: Electronic searches of MEDLINE from database inception up to March 2026 using MeSH terms and keywords related to FGR and guidelines. STUDY ELIGIBILITY CRITERIA: Critical, structured comparison of national or international guidelines on FGR published since 2010. Final inclusion required unanimous agreement from all authors.

STUDY APPRAISAL AND SYNTHESIS METHODS: Pre-specified extraction across domains: definition; prediction/prevention; surveillance tools and frequency; delivery timing and mode; and labor induction methods. Dual data …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress-strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Nanosecond Pulsed Electric Fields For Extracellular Vesicle Engineering: From Electro-Exocytosis To Cargo Modulation, Art Neal, Teresa Graham, Mohamadmahdi Samandari, Arash Ghorbannia, Anca Dobrian, Stephen J. Beebe, Ruben M. L. Colunga-Biancatelli

Bioelectrics Publications

Extracellular vesicles (EVs), including small extracellular vesicles (sEVs) and medium/large extracellular vesicles (MVs), have emerged as promising therapeutic vectors and diagnostic biomarkers across various branches of biomedicine. However, the clinical translation of EV-based technologies remains constrained by persistent challenges in manufacturing: insufficient yield from primary cell sources, limited control over cargo composition, and the absence of scalable, standardized production platforms. Nanosecond pulsed electric fields (nsPEF) represent an emerging biophysical approach that can address several of these limitations. Unlike conventional electroporation, which targets the plasma membrane using microsecond-to-millisecond pulses, nsPEF delivers ultrashort (1–300 ns), high-amplitude (10–300 kV/cm) pulses that penetrate intracellularly …

Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson

Honors Undergraduate Theses

This study investigates the relationship between electrical stimulus characteristics of shape and charge on evoked sensations and electroencephalogram (EEG) data during multi-waveform transcutaneous electrical nerve stimulation (TENS) of the median nerve. Neuromodulation methods have traditionally had little control over the location and quality of their associated evoked sensation (e.g., electric, vibration, touch). This experiment utilized five unique stimulus waveforms during TENS stimulation. EEG data were collected concurrently to provide an introductory objective measure of the neural responses underlying these sensory changes. Eleven participants completed three tasks (thresholding, super-threshold stimulation, two-alternative forced choice) using a two-electrode TENS approach. Stimulus waveforms were …

A Chicken Model For Non-Invasive Diagnosis Of Infant Developmental Dysplasia Of The Hip (Ddh) Using Acoustic Transmission Measurements, Aliza Shah

Honors Undergraduate Theses

Developmental dysplasia of the hip (DDH) is a condition characterized by abnormal development and stability of the hip joint. In a healthy infant, the femoral head (ball) fits securely within the acetabulum (socket of the pelvis), allowing for proper joint function. In DDH, the relationship is disrupted, ranging from mild acetabular dysplasia to partial (subluxation) or complete dislocation of the femoral head. This condition represents a range of structural abnormalities that develop during early growth. The integrity of the hip joint is essential for physical mobility, and disruption of this structure can lead to significant functional impairment. DDH may result …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

A Portable Potentiostat Integrated With A Pt/Zno/Lig Electrode For Non-Enzymatic Glucose Detection, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Continuous glucose monitoring is critical for effective diabetes management; however, conventional benchtop potentiostats are bulky, costly, and unsuitable for decentralized point-of-care (PoC) applications. To address these limitations, this work presents a miniaturized, low-cost electrochemical sensing platform integrating a non-enzymatic glucose sensor with a portable potentiostat. The sensing electrode is based on laser-induced graphene modified with zinc oxide and platinum nanostructures via electrodeposition to enable sensitive glucose detection under physiological conditions. A custom-designed portable potentiostat was developed to control electrode potentials and perform electrochemical measurements, and its performance was experimentally validated against a commercial Metrohm system. Glucose detection was evaluated using …

Modulation Of Prussian Blue Redox Signaling By Molecular Imprinting For Reagent-Free Electrochemical Detection Of Emtricitabine, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

Reagent-free electrochemical sensors offer significant benefits for rapid, affordable point-of-care drug testing. In this study, we introduce a novel, reagent-free electrochemical sensor based on a molecularly imprinted polymer (MIP) specifically designed for the selective detection of Emtricitabine (FTC), a common antiretroviral used in HIV therapy. The sensor uses laser-induced graphene (LIG) electrodes, renowned for their high conductivity and porosity, ideal for electrochemical sensing. To enable reagent-free operation, the LIG surface was electrochemically coated with Prussian Blue, serving as a redox-active layer. Next, an MIP-PPy film was electropolymerized onto the Prussian Blue surface in the presence of FTC as a template, …

Linker-Free Gold-Sputtered Tapered Optical Fiber Plasmonic Sensors For High-Sensitivity Refractive Index Detection In Microfluidic Platforms, Erem Ujah, Gymama Slaughter

Center for Bioelectronics Publications

Gold-sputtered tapered optical fiber (Au-TOF) sensors were developed for high-sensitivity refractive-index (RI) detection using aqueous glucose standards spanning 1.33–1.41 RIU (0–50% w/v). The sensors were fabricated using a reproducible workflow combining flame-brushing tapering, plasma surface preparation, and rotational magnetron sputtering, enabling azimuthally uniform gold coatings without the use of thiol or sulfur linker chemistries. Two sputtering durations (24 s and 30 s) were investigated to examine thickness-dependent plasmonic coupling and sensing performance. Optical measurements were conducted using a broadband supercontinuum source and compact spectrometer within a 20 µL microfluidic sensing chamber. Increasing glucose concentration produced a monotonic decrease in transmission …

Electrochemical Hemoglobin Biosensors For Point-Of-Care Diagnostics, Ashwini Dantanarayana, Gymama Slaughter

Center for Bioelectronics Publications

Hemoglobin (Hb) and its glycated variant (HbA1c) are essential clinical biomarkers for diagnosing anemia, acute hemorrhage, and long-term glycemic control. The growing demand for decentralized point-of-care (POC) testing has accelerated the development of rapid, inexpensive, and portable electrochemical sensing platforms. These technologies exploit the intrinsic redox activity of the heme prosthetic group, yet achieving efficient direct electron transfer (DET) remains a fundamental challenge because the electroactive iron center is deeply embedded within the globin structure. This review critically examines recent advances in electrochemical Hb sensing, tracing the evolution of electrode architectures from conventional carbon substrates to nanostructured materials, including graphene, …

Engineering Electrospun Pvdf Nanofibers For Next-Generation Wearable Bioelectronics, Reshmi Banerjee, Gymama Slaughter

Center for Bioelectronics Publications

Electrospun poly(vinylidene fluoride) (PVDF) and P(VDF-TrFE) nanofibers offer a mechanically flexible, high-surface-area platform for wearable bioelectronics, including piezoelectric sensing and self-powered operation. This review establishes a process–structure–property–performance framework for engineering electrospun PVDF- and P(VDF-TrFE)-based wearable systems. Relationships amongst precursor composition, electrospinning parameters, fiber morphology and alignment, crystalline phase formation, dipole orientation, and device-level piezoelectric performance are examined. Electrospinning is compared with other established fabrication methods including solution casting, spin coating, melt processing, phase inversion, and printing in terms of electroactive β-phase fraction, flexibility, scalability, manufacturing complexity, cost, and wearable-device suitability. Device architectures and performance are evaluated across pressure and strain …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …