Wearable Optical Fiber Sensors in Medical Monitoring Applications: A Review

Challenges in Adapting Fibre Optic Sensors for Biomedical Applications

Fibre optic sensors (FOSs) have developed as a transformative technology in healthcare, often offering unparalleled accuracy and sensitivity in monitoring various physiological and biochemical parameters. Their applications range from tracking vital signs to guiding minimally invasive surgeries, enabling advancements in medical diagnostics and treatment. However, the integration of FOSs into biomedical applications faces numerous challenges. This article describes some challenges for adopting FOSs for biomedical purposes, exploring technical and practical obstacles, and examining innovative solutions. Significant challenges include biocompatibility, miniaturization, addressing signal processing complexities, and meeting regulatory standards. By outlining solutions to the stated challenges, it is intended that this article provides a better understanding of FOS technologies in biomedical settings and their implementation. A broader appreciation of the technology, offered in this article, enhances patient care and improved medical outcomes.

Future of magnetic sensors applications in early prediction of cardiac health status

The evolution of health monitoring technologies has highlighted the need for accurate and reliable sensors, particularly in the context of cardiac health. This review examines the potential of magnetic sensors as a superior alternative to optical sensors for the early prediction of cardiac health status. Optical sensors face significant challenges, especially for individuals with darker skin tones, where increased light absorption adversely affects measurement accuracy. Additionally, issues such as sensor-skin coupling and motion artifacts further compromise the performance of optical devices. In contrast, magnetic sensors offer a compelling solution by providing consistent readings irrespective of skin tone, thereby enhancing inclusivity in health monitoring. These sensors leverage magnetic fields, which do not rely on light penetration, allowing for improved coupling with the skin's surface and maintaining accuracy during motion. This paper discusses recent advancements in magnetic sensor technology and their implications for cardiac health applications, emphasizing the potential for increased accuracy and reliability in predicting cardiac outcomes. As healthcare shifts toward more personalized and precise monitoring solutions, magnetic sensors emerge as a promising frontier, addressing critical challenges in current health status prediction methods. By focusing on these innovative technologies, we aim to contribute to the ongoing discourse on enhancing cardiac health monitoring and fostering more equitable healthcare solutions.

Innovations in quantitative rapid testing: Early prediction of health risks

As health monitoring becomes increasingly intricate, the demand for innovative solutions to predict and assess health status is more pressing than ever. This review focuses on the transformative potential of multi-sensor technologies in health monitoring, emphasizing their role in early health status prediction. By integrating diverse sensor types ranging from wearable fitness trackers to implantable devices and environmental monitors healthcare professionals can gain a richer, more nuanced understanding of an individual's physiological state. We analyze various configurations of multi-sensor networks and their efficacy in identifying early indicators of health issues, such as cardiovascular diseases, diabetes, and respiratory ailments. For example, the combination of biometric sensors that track vital signs with environmental data on pollutants can yield invaluable insights into a patient's overall health. This integrated approach not only improves the accuracy of health assessments but also facilitates timely interventions. Furthermore, we address the challenges inherent in multi-sensor systems, including data integration, device interoperability, and the need for advanced algorithms capable of processing complex datasets. Recent advancements in machine learning and artificial intelligence are underscored as pivotal in enhancing the capabilities of these technologies for predictive health analytics. Ultimately, this review highlights how multi-sensor systems can redefine early health status prediction, paving the way for proactive healthcare strategies that significantly improve patient outcomes and optimize healthcare delivery.

Utilising Inertial Measurement Units and Force-Velocity Profiling to Explore the Relationship Between Hamstring Strain Injury and Running Biomechanics

The purpose of this study was to retrospectively and prospectively explore associations between running biomechanics and hamstring strain injury (HSI) using field-based technology. Twenty-three amateur sprinters performed 40 m maximum-effort sprints and then underwent a one-year injury surveillance period. For the first 30 m of acceleration, sprint mechanics were quantified through force-velocity profiling. In the upright phase of the sprint, an inertial measurement unit (IMU) system measured sagittal plane pelvic and hip kinematics at the point of contact (POC), as well as step and stride time. Cross-sectional analysis revealed no differences between participants with a history of HSI and controls except for anterior pelvic tilt (increased pelvic tilt on the injured side compared to controls). Prospectively, two participants sustained HSIs in the surveillance period; thus, the small sample size limited formal statistical analysis. A review of cohort percentiles, however, revealed both participants scored in the higher percentiles for variables associated with a velocity-oriented profile. Overall, this study may be considered a feasibility trial of novel technology, and the preliminary findings present a case for further investigation. Several practical insights are offered to direct future research to ultimately inform HSI prevention strategies.

Advances in Photonic Materials and Integrated Devices for Smart and Digital Healthcare: Bridging the Gap Between Materials and Systems

Recent advances in developing photonic technologies using various materials offer enhanced biosensing, therapeutic intervention, and non-invasive imaging in healthcare. Here, this article summarizes significant technological advancements in materials, photonic devices, and bio-interfaced systems, which demonstrate successful applications for impacting human healthcare via improved therapies, advanced diagnostics, and on-skin health monitoring. The details of required materials, necessary properties, and device configurations are described for next-generation healthcare systems, followed by an explanation of the working principles of light-based therapeutics and diagnostics. Next, this paper shares the recent examples of integrated photonic systems focusing on translation and immediate applications for clinical studies. In addition, the limitations of existing materials and devices and future directions for smart photonic systems are discussed. Collectively, this review article summarizes the recent focus and trends of technological advancements in developing new nanomaterials, light delivery methods, system designs, mechanical structures, material functionalization, and integrated photonic systems to advance human healthcare and digital healthcare.

Lighting the Path to Precision Healthcare: Advances and Applications of Wearable Photonic Sensors

Recent advancements in wearable photonic sensors have marked a transformative era in healthcare, enabling non-invasive, real-time, portable, and personalized medical monitoring. These sensors leverage the unique properties of light toward high-performance sensing in form factors optimized for real-world use. Their ability to offer solutions to a broad spectrum of medical challenges - from routine health monitoring to managing chronic conditions, inspires a rapidly growing translational market. This review explores the design and development of wearable photonic sensors toward various healthcare applications. The photonic sensing strategies that power these technologies are first presented, alongside a discussion of the factors that define optimal use-cases for each approach. The means by which these mechanisms are integrated into wearable formats are then discussed, with considerations toward material selection for comfort and functionality, component fabrication, and power management. Recent developments in the space are detailed, accounting for both physical and chemical stimuli detection through various non-invasive biofluids. Finally, a comprehensive situational overview identifies critical challenges toward translation, alongside promising solutions. Associated future outlooks detail emerging trends and mechanisms that stand to enable the integration of these technologies into mainstream healthcare practice, toward advancing personalized medicine and improving patient outcomes.

A Unique Time-Reversal Algorithm-Enabled Flexible Ultrasound Transducer with a Controllable Acoustic Field

Flexible ultrasonic devices represent a feasible technology for providing timely signal detection and even a non-invasive disease treatment for the human brain. However, the deformation of the devices is always accompanied by a change in the acoustic field, making it hard for accurate focusing. Herein, we report a stable and flexible transducer. This device can generate a high-intensity acoustic signal with a controllable acoustic field even when the device is bent. The key is to use a low-impedance piezoelectric material and an island-bridge device structure, as well as to design a unique time-reversal algorithm to correct the deviation of signals after transcranial propagation. To provide an in-depth study of the acoustic field of flexible devices, we also analyze the effects of mechanical deformation and structural parameters on the corresponding acoustic response.

Wearable Loop Sensor for Bilateral Knee Flexion Monitoring

We have previously reported wearable loop sensors that can accurately monitor knee flexion with unique merits over the state of the art. However, validation to date has been limited to single-leg configurations, discrete flexion angles, and in vitro (phantom-based) experiments. In this work, we take a major step forward to explore the bilateral monitoring of knee flexion angles, in a continuous manner, in vivo. The manuscript provides the theoretical framework of bilateral sensor operation and reports a detailed error analysis that has not been previously reported for wearable loop sensors. This includes the flatness of calibration curves that limits resolution at small angles (such as during walking) as well as the presence of motional electromotive force (EMF) noise at high angular velocities (such as during running). A novel fabrication method for flexible and mechanically robust loops is also introduced. Electromagnetic simulations and phantom-based experimental studies optimize the setup and evaluate feasibility. Proof-of-concept in vivo validation is then conducted for a human subject performing three activities (walking, brisk walking, and running), each lasting 30 s and repeated three times. The results demonstrate a promising root mean square error (RMSE) of less than 3° in most cases.