Search Results (101)

Background/Objectives: Glaucoma affects over 70 million people worldwide and is a major cause of irreversible blindness, with elevated intraocular pressure (IOP) as the only modifiable risk factor. Conventional techniques like Goldmann applanation tonometry (GAT) are widely used but cannot provide continuous or nocturnal monitoring, limiting the detection of pressure peaks relevant to disease progression. Emerging technologies, including home-based devices, wearable sensors, such as contact lens-based sensors (CLBS), and implantable biomedical microelectromechanical systems (bioMEMS), offer more comprehensive and continuous assessment of IOP patterns. Thus, this scoping review aimed to map the available evidence on technologies for continuous IOP monitoring, summarizing their performance and agreement with traditional tonometry. Methods: A systematic search of electronic databases was conducted to identify studies published in the last 10 years evaluating self-tonometry devices, CLBS, or implantable systems designed for continuous IOP monitoring. Two reviewers independently screened articles, applied eligibility criteria, charted relevant data, including device characteristics and agreement with GAT, and reported clinical applications. Results: Self-tonometry devices demonstrated generally good agreement with GAT while enabling patients to monitor IOP outside clinical settings. These devices provided valuable information on diurnal and nocturnal IOP fluctuations, especially in individuals with rapid progression or those undergoing postoperative follow-up. BioMEMS-based wearable and implantable sensors showed promise for continuous long-term monitoring and revealed previously unrecognized fluctuation patterns, including activity-related changes. Conclusions: Emerging IOP-monitoring technologies appear to complement standard clinical methods by offering more detailed IOP profiles. Their integration into clinical practice may support individualized risk assessment and improved management of glaucoma progression. Full article

The rapid evolution of healthcare technology is being driven by advancements in Micro-Electro-Mechanical Systems (MEMS), BioMEMS (Biological MEMS), and the expanding concept of the Internet of Bodies (IoB). This review explores the convergence of these three domains and their transformative impact on personalized medicine (PM), with a focus on smart, connected biomedical devices. Starting from the historical development of MEMS for medical sensing and diagnostics, the review traces the emergence of BioMEMS as biocompatible, minimally invasive solutions for continuous monitoring and real-time intervention. The integration of such devices within the IoB ecosystem enables data-driven, remote, and predictive healthcare, offering tailored diagnostics and treatment for chronic and acute conditions alike. The paper classifies IoB-associated technologies into non-invasive, invasive, and incorporated devices, reviewing wearable systems such as smart bracelets, e-tattoos, and smart footwear, as well as internal devices including implantable and ingestible. Alongside these opportunities, significant challenges persist, particularly in device biocompatibility, data interoperability, cybersecurity, and ethical regulation. By synthesizing recent advances and critical perspectives, this review aims to provide a comprehensive understanding of the current landscape, clinical potential, and future directions of MEMS, BioMEMS, and IoB-enabled personalized healthcare. Full article

Continuous monitoring of environmental and physiological parameters is essential for early diagnostics, real-time decision making, and intelligent system adaptation. Recent advancements in bio-microelectromechanical systems (BioMEMS) sensors have significantly enhanced our ability to track key metrics in real time. However, continuous monitoring demands sustainable energy supply solutions, especially for on-site energy replenishment in areas with limited resources. Artificial intelligence (AI), particularly large language models, offers new avenues for interpreting the vast amounts of data generated by these sensors. Despite this potential, fully integrated systems that combine self-powered BioMEMS sensing with AI-based analytics remain in the early stages of development. This review first examines the evolution of BioMEMS sensors, focusing on advances in sensing materials, micro/nano-scale architectures, and fabrication techniques that enable high sensitivity, flexibility, and biocompatibility for continuous monitoring applications. We then examine recent advances in energy harvesting technologies, such as piezoelectric nanogenerators, triboelectric nanogenerators and moisture electricity generators, which enable self-powered BioMEMS sensors to operate continuously and reducereliance on traditional batteries. Finally, we discuss the role of AI in BioMEMS sensing, particularly in predictive analytics, to analyze continuous monitoring data, identify patterns, trends, and anomalies, and transform this data into actionable insights. This comprehensive analysis aims to provide a roadmap for future continuous BioMEMS sensing, revealing the potential unlocked by combining materials science, energy harvesting, and artificial intelligence. Full article

Designing and manufacturing devices at the micro- and nanoscales offers significant advantages, including high precision, quick response times, high energy density ratios, and low production costs. These benefits have driven extensive research in micro-electromechanical systems (MEMS) and nano-electromechanical systems (NEMS), resulting in various classifications of materials and manufacturing techniques, which are ultimately used to produce different classifications of MEMS devices. The current work aims to systematically organize the literature on MEMS in biomedical devices, encompassing past achievements, present developments, and future prospects. This paper reviews the current research trends, highlighting significant material advancements and emerging technologies in biomedical MEMS in order to meet the current challenges facing the field, such as ensuring biocompatibility, achieving miniaturization, and maintaining precise control in biological environments. It also explores projected applications, including use in advanced diagnostic tools, targeted drug delivery systems, and innovative therapeutic devices. By mapping out these trends and prospects, this review will help identify current research gaps in the biomedical MEMS field. By pinpointing these gaps, researchers can focus on addressing unmet needs and advancing state-of-the-art biomedical MEMS technology. Ultimately, this can lead to the development of more effective and innovative biomedical devices, improving patient care and outcomes. Full article

Endometrial organoids (EOs) have emerged as a powerful three-dimensional (3D) model for studying the human endometrium, offering new insights into infertility and reproductive disorders. These self-organizing miniature structures closely mimic the cellular composition, hormonal responsiveness, and functional characteristics of the endometrium, making them valuable preclinical tools for investigating implantation failure, endometrial receptivity, and disease pathophysiology. This review explores the role of EOs in reproductive medicine, with a focus on their applications in infertility research, environmental toxicology, and regenerative therapies. Traditional 2D cell cultures fail to capture the complexity of these physiological and pathological interactions, whereas organoids provide a physiologically relevant system for studying implantation mechanisms. Additionally, co-culture models incorporating stromal and immune cells have further enhanced our understanding of the maternal–fetal interface. Beyond modeling infertility, EOs hold significant promise for therapeutic applications. Advances in organoid transplantation have demonstrated potential for treating endometrial dysfunction-related infertility, including conditions such as Asherman’s syndrome and thin endometrium. Moreover, these models serve as a platform for drug screening and biomarker discovery, paving the way for personalized reproductive medicine. Despite their transformative potential, limitations remain, including the need for improved extracellular matrices, vascularization, and immune system integration. This review emphasizes the significant contributions of EOs to the field of infertility treatment and reproductive biology by examining recent advancements and emerging research. The continued refinement of these models would offer a paradigm for improving assisted reproductive technologies (ARTs) and regenerative medicine outcomes, offering new hope for individuals facing infertility challenges. Full article

Cardiovascular diseases (CVD) are the primary cause of death and disability around the world. Over the past decades, several conventional model systems based on two-dimensional (3D) monolayer cultures or experimental animals have been adopted to dissect and understand heart diseases in order to develop treatment modalities. However, traditional models exhibit several limitations in recapitulating human-specific key physiological and pathological characteristics, which highlights the necessity of developing physiologically relevant models. In recent years, tissue engineering approaches have been extensively employed to generate revolutionary three-dimensional (3D) cardiac models. In particular, the combined use of various bioengineering strategies and cellular reprogramming approaches has facilitated the development of various models. This review presents an overview of different approaches (bioprinting, scaffolding, and electrospinning) for creating bioengineered cardiac tissue models. Next, a broad survey of recent research related to the modeling of various cardiac diseases is presented. Finally, current challenges and future directions are proposed to foster further developments in the field of cardiac tissue engineering. Full article

Wearable and implantable BioMEMSs (biomedical microelectromechanical systems) have transformed modern healthcare by enabling continuous, personalized, and minimally invasive monitoring, diagnostics, and therapy. Wearable BioMEMSs have advanced rapidly, encompassing a diverse range of biosensors, bioelectronic systems, drug delivery platforms, and motion tracking technologies. These devices enable non-invasive, real-time monitoring of biochemical, electrophysiological, and biomechanical signals, offering personalized and proactive healthcare solutions. In parallel, implantable BioMEMS have significantly enhanced long-term diagnostics, targeted drug delivery, and neurostimulation. From continuous glucose and intraocular pressure monitoring to programmable drug delivery and bioelectric implants for neuromodulation, these devices are improving precision treatment by continuous monitoring and localized therapy. This review explores the materials and technologies driving advancements in wearable and implantable BioMEMSs, focusing on their impact on chronic disease management, cardiology, respiratory care, and glaucoma treatment. We also highlight their integration with artificial intelligence (AI) and the Internet of Things (IoT), paving the way for smarter, data-driven healthcare solutions. Despite their potential, BioMEMSs face challenges such as regulatory complexities, global standardization, and societal determinants. Looking ahead, we explore emerging directions like multifunctional systems, biodegradable power sources, and next-generation point-of-care diagnostics. Collectively, these advancements position BioMEMS as pivotal enablers of future patient-centric healthcare systems. Full article

Ovarian cancer (OC) is one of the leading causes of gynecological cancer-related death worldwide. Late diagnosis at advanced stages of OC is the reason for a higher mortality rate. Earlier diagnosis and proper treatment are important for improving the prognosis of OC patients. Biosensors offer accurate, low-cost, rapid, and user-friendly devices that can be employed for the detection of OC-specific biomarkers in the early stage. Therefore, it is important to consider the potential biomarkers in the biological fluids to confirm the OC prognosis. Out of many biomarkers, the most commonly tested clinically is cancer antigen 125 (CA-125). However, CA-125 is considered to be a poor biomarker for OC diagnosis. Several biosensing methods were developed for the sensitive and quantitative detection of each biomarker. In abnormal expression in OC patients, nucleic acids, enzymes, cells, and exosomes are used as target biomarkers for the construction of biosensors. This review focuses on the development for the detection of various biomarkers using multiple biosensing methods. Here, we describe the origin and the significance of OC-associated biomarkers, the working principle of biosensors, and the classification of biosensors based on their recognition elements and signal transducers. The modes of detection and sensitivity of the sensors are discussed. Finally, the challenges in the fabrication, obstacles in the clinical application, and future prospects are discussed. Full article

Standing surface acoustic wave (SSAW)-based acoustofluidics is widely used due to its compatibility with soft materials and polymer structures. In the presence of an acoustic field, particles move either toward pressure nodes or anti-nodes according to their contrast factor. Using this technique, blood cells with a certain characteristic can be oriented in different streamlines in a microchannel. The cumulative effect of parameters, such as the inlet velocity ratio of the buffer solution to the blood sample, acoustic frequency, voltage, and channel geometry, is key to effective separation in these microfluidic chips. In this study, simultaneous separation of white blood cells, red blood cells, and platelets in one stage is simulated by means of numerical calculations. The linear constitutive equation for the piezoelectric substrate, the Helmholtz equation for the acoustic field, and the Navier–Stokes equations for fluid mechanics are solved simultaneously to precisely capture the blood cell behavior in the SSAW-based device. The results show that whole blood cell separation can be achieved using a velocity ratio of 6.25, a resonance frequency of 8.28 MHz, and a voltage of 8.5 V in the proposed five-outlet microfluidic chip. Full article

Background: Respiratory viral infections are a major public health challenge and the most diagnosed medical condition, particularly for individuals living in close proximity, like military personnel. We compared the sensitivity and specificity of the Biomeme Franklin^TM and Truelab^® RT-PCR thermocyclers to determine which platform is more sensitive and specific at detecting SARS-CoV-2 and influenza A and B viruses. Methodology: RNA extracted from nasopharyngeal swabs of infected and uninfected individuals was tested on the Biomeme Franklin^TM at Lackland and the Truelab^® at Wright Patterson Air Force bases. Results: We found an 88% and 71% positivity rate in SARS-CoV-2-infected samples tested on Biomeme and Truelab^®, respectively. Likewise, we found a 49% and 80% positivity rate in influenza-positive samples tested on Biomeme and Truelab^®, respectively. One hundred percent of uninfected swab samples tested negative for SARS-CoV-2 on both platforms. Conversely, 91% and 100% of uninfected swabs tested negative for flu on Biomeme and Truelab^®, respectively. Significance: Differences in specificity and sensitivity in detection of SARS-CoV-2 and influenza between Biomeme and Truelab^® suggest that Truelab^® is a more promising and potentially deployable diagnostic platform for SARS-CoV-2 and influenza viruses’ detection in an austere environment. Full article

This work presents the design, fabrication, and rigorous validation of a flexible, wireless, capacitive pressure sensor for the full-range continuous monitoring of ventricular pressure. The proposed system consists of an implantable set and an external readout device; both modules were designed to form an RCL resonant circuit for passive, wireless pressure sensing and signal retrieving. Using surface micromachining and flexible electronics techniques, a two-variable capacitor array and a dual-layer planar coil were integrated into a flexible ergonomic substrate, avoiding hybrid-like connections in the implantable set. The proposed arrangement (capacitor array and dual-layer coil) allows us to optimize the operation pressure range and sensing distance. The use of polyimide as both the flexible substrate and the passivation material is a key feature, ensuring a biocompatible, implantable set that is mechanically flexible and can be folded to a compact size to achieve minimally invasive implantation. An external readout device has also been developed using a discrete printed circuit board (PCB) approach to support pressure measurements. The pressure responsivity of the sensor was validated to the laboratory level using a controlled pressure chamber. The results obtained show that the capacitance value of the sensor changed from 5.68 pF to 33.26 pF as the pressure varied from 0 to 300 mmHg. Correspondingly, the resonance frequency of the implantable set shifted from 12.75 MHz to 5.27 MHz. The sensitivity of the capacitive sensor was approximately 0.58 pF/mmHg and the typical response time was 220 ms. The wireless system performance was evaluated in both air and synthetic biological tissue using a Maxwell–Wien bridge circuit. The results showed a sensing distance longer than 3.5 cm, even under moderate misalignment conditions (up to 1.5 cm). The output voltage was successfully measured, ranging from 502.54 mV to 538.29 mV, throughout the full pressure range, with a measurement error of ±2.2 mV. Full article

A label-free biosensor based on a tunable MEMS metamaterial structure is proposed in this paper. The adopted structure is a one-dimensional array of metamaterial gratings with movable and fixed fingers. The moving unit of the optical detection system is a component of the MEMS structure, driven by the surface stress effect. Thus, these suspended optical nanoribbons can be moved and change the grating pattern by the biological bonds that happened on the modified cantilever surface. Such structural variations lead to significant changes in the optical response of the metamaterial system under illuminating angled light and subsequently shift its resonance wavelength spectrum. As a result, the proposed biosensor shows appropriate analytical characteristics, including the mechanical sensitivity of S_m = 11.55 μm/Nm⁻¹, the optical sensitivity of S_o = Δλ/Δd = 0.7 translated to S_o = Δλ/Δσ = 8.08 μm/Nm⁻¹, and the quality factor of Q = 102.7. Also, considering the importance of multi-biomarker detection, a specific design of the proposed topology has been introduced as an array for identifying different biomolecules. Based on the conducted modeling and analyses, the presented device poses the capability of detecting multiple biomarkers of disease at very low concentrations with proper precision in fluidic environments, offering a suitable bio-platform for lab-on-chip structures. Full article

Flexible manufacturing cells provide significant advantages in low-volume mass-customization production but also induce added complexity and technical challenges in terms of integration, control, and extensibility. The variety of closed-source industrial protocols, the heterogeneous equipment, and the product’s manufacturing specifications are main points of consideration in the development of such a system. This study aims to describe the approach, from concept to implementation, for the development of the controller for a flexible manufacturing cell consisting of heterogeneous equipment in terms of functions and communication interfaces. Emphasis is put on the considerations and challenges for effective integration, extensibility, and interoperability. Scheduling and monitoring performed by the developed controller are demonstrated for a manufacturing cell producing microfluidic devices (bioMEMS) that consists of six workstations and a robot-based handling system. Communication between the system controller and the workstations was based on open-source technologies instead of proprietary software and protocols, to support interoperability and, to a considerable extent, code reusability. Full article

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy’s invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis. Full article