Photoplethysmography (PPG) is an affordable and straightforward optical technique used to detect changes in blood volume within tissue microvascular beds. PPG technology has found widespread application in commercial medical devices, enabling measurements of oxygen saturation, blood pressure, and cardiac output; the assessment of autonomic nerve function; and the diagnosis of peripheral vascular disease. Recently, the growing demand for non-invasive, portable, cost-effective technology, along with advancements in small semiconductor components, has led to the integration of PPG into various wrist-worn wearable devices. Multiple sensor structures have been proposed and, through appropriate signal processing and algorithmic application, these wearable devices can measure a range of health indicators during daily life. This paper begins by addressing the market status of wrist-worn wearable devices, followed by an explanation of the fundamental principles underlying light operation and its interaction with living tissue for PPG measurements. Moving on to technological advancements, the paper addresses the analog front end for the measurement of the PPG signal, sensor configurations with multiple light emitters and receivers, the minimum sampling rate required for low-power systems, and the measurement of stress, sleep, blood pressure, blood glucose, and activity using PPG signals. Several challenges in the field are also identified, including selecting the appropriate wavelength for the PPG sensor’s light source, developing low-power interpolation methods to extract high-resolution inter-beat intervals at a low sampling rate, and exploring the measurement of physiological phenomena using multi-wavelength PPG signals simultaneously collected at the same location. Lastly, the paper presents future research directions, which encompass the development of new, reliable parameters specific to wearable PPG devices and conducting studies in real-world scenarios, such as 24-h long-term measurements.

Dopamine (DA), a vital neurotransmitter, plays a critical role in the human brain and relates to neuropsychiatric disorders such as Parkinson's disease and schizophrenia. Numerous studies have explored detection of such biomarkers through surface-enhanced Raman spectroscopy (SERS). However, most of the studies focused on SERS detection face significant challenges with plasmonic nanostructure development. Such challenges often include time-consuming processes, complex fabrication, specialized chemical labeling, poor reproducibility, and random hotspot generation. Therefore, the need for simple and rapid nanostructure development is evident in SERS. We propose an innovative SERS-active sensing technique for 50 nm silver nanoparticle (AgNP) clustering based on surface acoustic wave (SAW). When a 1 μL droplet of AgNP colloid is dispensed onto the SAW-propagation zone, the AgNP cluster is deposited after the droplet completely evaporates, developing plasmonic nanogaps for SERS hotspot caused by spherical AgNP aggregation. By optimizing the SAW system through the hydrophobic treatment and modulation of the operational power, the SAW-induced AgNP clustering showed densely packed AgNP within a dot-like configuration (∼2200 AgNP μm^-2), effectively preventing particle welding. The characterization of 4-mercaptobenzoic acid as a probe analyte revealed that concentrations as low as 1.14 pM was detected using our SAW-SERS system under 785 nm laser excitation. Moreover, DA was detected up to 4.28 nM with a determination of 0.99 (R²). This technique for AgNP clustering induced by SAW provides a rapid, in situ, label-free SERS sensing method with outstanding sensitivity and linearity. A mere act of dropping can create extensive plasmonic hotspots featuring nanogap of ∼1.5 nm. The SAW-induced AgNP clustering can serve as an ultrasensitive SERS-active substrate for diverse molecular detections, including neurotransmitter detection.

Highly porous heterojunction films of SnO₂/TiO₂ were prepared using gas-flow thermal evaporation followed by atomic layer deposition (ALD). Highly porous SnO₂ was fabricated by introducing an inert gas, Ar, during thermal evaporation. To build heterogeneous structures, the TiO₂ layers were conformally deposited on porous SnO₂ with a range of 10 to 100 cycles by means of ALD. The photocatalytic properties for different TiO₂ thicknesses on the porous SnO₂ were compared using the degradation of methylene blue (MB) under UV irradiation. The comparisons showed that the SnO₂/TiO₂-50 heterostructures had the highest photocatalytic efficiency. It removed 99% of the MB concentration, and the decomposition rate constant (K) was 0.013 min⁻¹, which was approximately ten times that of the porous SnO₂. On the other hand, SnO₂/TiO₂-100 exhibited a lower photocatalytic efficiency despite having a TiO₂ layer thicker than SnO₂/TiO₂-50. After 100 cycles of TiO₂ ALD deposition, the structure was transferred from the heterojunction to the core–sell structure covered with TiO₂ on the porous SnO₂, which was confirmed by TEM analysis. Since the electrons photogenerated by light irradiation were separated into SnO₂ and produced reactive oxygen, O₂⁻, the heterojunction structure, in which SnO₂ was exposed to the surface, contributed to the high performance of the photocatalyst.

Microplastics adsorb toxic substances and act as a transport medium. When microplastics adsorbed with toxic substances accumulate in the body, the microplastics and the adsorbed toxic substances can cause serious diseases, such as cancer. This work aimed to develop a surface-enhanced Raman spectroscopy (SERS) detection method for surface-adsorbent toxic substances by forming gold nanogaps on microplastics using surface acoustic waves (SAWs). Polystyrene microparticles (PSMPs; 1 μm) and polycyclic aromatic hydrocarbons (PAHs), including pyrene, anthracene, and fluorene, were selected as microplastics and toxic substances, respectively. Gold nanoparticles (AuNPs; 50 nm) were used as a SERS agent. The Raman characteristic peaks of the PAHs adsorbed on the surface of PSMPs were detected, and the SERS intensity and logarithm of the concentrations of pyrene, anthracene, and fluorene showed a linear relationship (R² = 0.98), and the limits of detection were 95, 168, and 195 nM, respectively. Each PAH was detected on the surface of PSMPs, which were adsorbed with toxic substances in a mixture of three PAHs, indicating that the technique can be used to elucidate mixtures of toxic substances. The proposed SERS detection method based on SAWs could sense toxic substances that were surface-adsorbed on microplastics and can be utilized to monitor or track pollutants in aquatic environments.