The complete blood count (CBC) is one of the most important clinical steps in clinical diagnosis. The instruments used for CBC are usually expensive and bulky and require well-trained operators. Therefore, it is difficult for medical institutions below the tertiary level to provide these instruments, especially in underprivileged countries. Several reported on-chip blood cell tests are still in their infancy and do not deviate from conventional microscopic or impedance measurement methods. In this study, we (i) combined magnetically activated cell sorting and the differential density method to develop a method to selectively isolate three types of leukocytes from blood and obtain samples with high purity and concentration for portable leukocyte classification using the lens-free shadow imaging technique (LSIT), and (ii) established several shadow parameters to identify the type of leukocytes in a complete leukocyte shadow image by shadow image analysis. The purity of the separated leukocytes was confirmed by flow cytometry. Several shadow parameters such as the “order ratio” and “minimum ratio” were developed to classify the three types of leukocytes. A shadow image library corresponding to each type of leukocyte was created from the tested samples. Compared with clinical reference data, a correlation index of 0.98 was obtained with an average error of 6% and a confidence level of 95%. This technique offers great potential for biological, pharmaceutical, environmental, and clinical applications, especially where point-of-care detection of rare cells is required.

We studied electrochemical sensors using printed carbon nanotubes (CNT) film on a polyethylene telephtalate (PET) substrate. The mechanical stability of the printed CNT film (PCF) was confirmed by using bending and Scotch tape tests. In order to determine the optimum sensor structure, a resistance-type PCF sensor (R-type PCF sensor) and a comb-type PCF sensor (C-type PCF sensor) were fabricated and compared using a diluted NH₃ droplet with various concentrations. The magnitude of response, response time, sensitivity, linearity, and limit of detection (LOD) were compared, and it was concluded that C-type PCF sensor has superior performance. In addition, the feasibility of PCF electrochemical sensor was investigated using 12 kinds of hazardous and noxious substances (HNS). The detection mechanism and selectivity of the PCF sensor are discussed.

Field-portable observation and analysis of particulate matter (PM) is required to enhance healthy lives. Various types of the PM measurement methods are in use; however, each of these methods has significant limitations in that real time measurement is impossible, the detection system is bulky, or the measurement accuracy is insufficient. In this work, we introduce an optical method to perform a fast and accurate PM analysis with a higher-contrast microscopic image enabled by a side-illuminated total internal reflection (TIR) technique to be implemented in a compact device. The superiority of the proposed method was quantitatively demonstrated by comparing the signal-to-noise ratio of the proposed side-illuminated TIR method with a traditional halogen lamp-based transmission microscope. With the proposed device, signal-to-noise ratios (SNRs) for microbeads (5~20 µm) and ultrafine dust particles (>5 µm) increased 4.5~17 and 4~10 dB, respectively, compared to the conventional transmission microscope. As a proof of concept, the proposed method was also applied to a low-cost commercial smartphone toy microscope enabling field-portable detection of PMs. We believe that the proposed side-illuminated TIR PM detection device holds significant advantages over other commonly used systems due to its sufficient detection capability along with simple and compact configuration as well as low cost.

The refractive index (RI), an important optical property of a material, is measured by commercial refractometers in the food, agricultural, chemical, and manufacturing industries. Most of these refractometers must be equipped with a prism for light dispersion, which drastically limits the design and size of the refractometer. Recently, there have been several reports on the development of a surface plasmon resonance (SPR)-based RI detector, which is characterized by its high sensitivity and simplicity. However, regardless of the prism, an expensive spectrometer is required to analyze the resonance wavelength or angle of incidence. This paper proposes a method that eliminates the need for the prism and other conventional spectrometer components. For this purpose, total internal reflection SPR technology was used on an Ag thin film, and RI analysis was combined with a lens-free CMOS image sensor or a smartphone camera. A finite-difference time-domain (FDTD) numerical simulation was performed to evaluate the relationship between the output power intensity and Ag film thickness for different RIs at three wavelengths of commercial light-emitting diodes (LEDs). The maximum sensitivity of −824.54 RIU⁻¹ was achieved with AG20 at an incident wavelength of 559 nm. Due to its simple design and cost effectiveness, this prism-less, SPR-based refractometer combined with a lens-free CMOS image sensor or a smartphone could be a superior candidate for a point-of-care device that can determine the RIs of various analytes in the field of biological or chemical sensing.

For marine accidents, prompt actions to minimize the casualties and loss of property are crucial. Remote sensing using satellites or aircrafts enables effective monitoring over a large area. Hyperspectral remote sensing allows the acquisition of high-resolution spectral information. This technology detects target objects by analyzing the spectrum for each pixel. We present a clustering method of seawater and floating objects by analyzing aerial hyperspectral images. For clustering, unsupervised learning algorithms of K-means, Gaussian Mixture, and DBSCAN are used. The detection performance of those algorithms is expressed as the precision, recall, and F1 Score. In addition, this study presents a color mapping method that analyzes the detected small object using cosine similarity. This technology can minimize future casualties and property loss by enabling rapid aircraft and maritime search, ocean monitoring, and preparations against marine accidents.