This review into recent advancements in silicon-based technology, with a particular emphasis on the biomedical applications of silicon sensors. Owing to their diminutive size, high sensitivity, and intrinsic compatibility with electronic systems, silicon-based sensors have found widespread utilization across healthcare, industrial, and environmental monitoring domains. In the realm of biomedical sensing, silicon has demonstrated significant potential to enhance human health outcomes while simultaneously driving progress in microfabrication techniques for multifunctional device development. The review systematically examines the versatile roles of silicon in the fabrication of electrodes, sensing channels, and substrates. Silicon electrodes are widely used in electrochemical biosensors for glucose monitoring and neural activity recording, while sensing channels in field-effect transistor biosensors enable the detection of cancer biomarkers and small molecules. Porous silicon substrates are applied in optical biosensors for label-free protein and pathogen detection. Key challenges in this field, including the interaction of silicon with biomolecules, the economic barriers to miniaturization, and issues related to signal stability, are critically analyzed. Proposed strategies to address these challenges and improve sensor functionality and reliability are also discussed. Furthermore, the article explores emerging developments in silicon-based biosensors, particularly their integration into wearable technologies. The pivotal role of artificial intelligence (AI) in enhancing the performance, functionality, and real-time capabilities of these sensors is also highlighted. This review provides a comprehensive overview of the current state, challenges, and future directions in the field of silicon-based biomedical sensing technologies.

Monitoring and assessing the progression of symptoms in neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease, are critical for improving patient outcomes. Traditional biomarkers, such as cerebrospinal fluid analysis and brain imaging, are widely used to investigate the underlying mechanisms of disease and enable early diagnosis. In contrast, digital biomarkers derived from phenotypic changes—such as EEG, eye movement, gait, and speech analysis—offer a noninvasive and accessible alternative. Leveraging portable and widely available devices, such as smartphones and wearable sensors, digital biomarkers are emerging as a promising tool for ND diagnosis and monitoring. This review highlights the comprehensive developments in digital biomarkers, emphasizing their unique advantages and integration potential alongside traditional biomarkers.

Researchers are interested in measuring mental stress because it is linked to a variety of diseases. Real-time stress monitoring via wearable sensor systems can aid in the prevention of stress-related diseases by allowing stressors to be controlled immediately. Physical tests, such as heart rate or skin conductance, have recently been used to assess stress; however, these methods are easily influenced by daily life activities. As a result, for more accurate stress monitoring, validations requiring two or more stress-related biomarkers are demanded. In this review, the combinations of various types of sensors (hereafter referred to as multiplexed sensor systems) that can be applied to monitor stress are discussed, referring to physical and chemical biomarkers. Multiplexed sensor systems are classified as multiplexed physical sensors, multiplexed physical–chemical sensors, and multiplexed chemical sensors, with the effect of measuring multiple biomarkers and the ability to measure stress being the most important. The working principles of multiplexed sensor systems are subdivided, with advantages in measuring multiple biomarkers. Furthermore, stress-related chemical biomarkers are still limited to cortisol; however, we believe that by developing multiplexed sensor systems, it will be possible to explore new stress-related chemical biomarkers by confirming their correlations to cortisol. As a result, the potential for further development of multiplexed sensor systems, such as the development of wearable electronics for mental health management, is highlighted in this review.