Visitsattapongse, Sarinporn

Loading...
Thumbnail Image
Preferred name
Visitsattapongse, Sarinporn
Alternative Name
Visitsattapongse, S.
Main Affiliation
Email
sarinporn.vi@kmitl.ac.th

Settings

Now showing 1 - 10 of 43
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A Novel Approach for Optimizing Molecularly Imprinted Polymer Composition in Electrochemical Detection of Collagen Peptides
    (2025-11-01)
    Vongmanee, Naphatsawan
    ;
    Nampeng, Jindapa
    ;
    Rattanapithan, Katesirin
    ;
    Sriwichai, Phuritasinee
    ;
    Pintavirooj, Chuchart
    Collagen peptides are key structural proteins that play an important role in maintaining the integrity and proper function of multiple tissues in the human body. Their breakdown is recognized as an important biomarker for various degenerative conditions, including the loss of muscle mass, joint and bone disorders, and compromised skin health. Current analytical approaches for collagen detection, such as ultraviolet spectrometry, enzyme-linked immunosorbent assay (ELISA), high-performance liquid chromatography (HPLC), and histochemical staining, are widely used but often expensive, time-consuming, and reliant on specific laboratory instrumentation, limiting their practicality for routine or rapid diagnostics. This study reports a novel biosensor for collagen peptide detection based on molecularly imprinted polymers (MIPs) integrated with screen-printed electrodes (SPEs). Electrochemical measurements revealed a clear correlation between collagen concentration and current response, confirming effective molecular binding within the imprinted matrix. The optimized MIP-modified electrode exhibited a detection range of 0.1–1000 µg/mL with a limit of detection (LOD) of 1.0106 µg/mL, limit of quantification (LOQ) of 4.46 µg/mL, sensitivity of 8.3816, and correlation coefficient (R<sup>2</sup> = 0.9436). These results highlight strong selectivity and sensitivity toward collagen peptides. The proposed MIP-based biosensor provides a rapid, low-cost platform for detecting collagen degradation products and holds potential for early diagnosis and future clinical applications in degenerative disease monitoring.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Store-operated calcium entry facilitates LPS-induced superoxide anion-dependent macrophage extracellular traps
    (2025-07-09)
    Nguyen, Thang Ngoc
    ;
    Lin, Tzu Chien
    ;
    Chimphlee, Waratchaya
    ;
    Siew, Kon Xuen
    ;
    Vongmanee, Naphatsawan
    Macrophage extracellular traps (METs) represent a recently discovered complex defence mechanism that is distinct from phagocytosis and involves the release of DNA and antibacterial proteins. They play an important role in pathogen removal, and calcium ions (Ca 2+) have also been reported to be involved. In the present study, we identified METotic cells using digitonin as an alternative to Triton X-100, coupled with immunofluorescence staining using lamin antibodies. The limited permeability of digitonin ensures exclusive intranuclear antibody labelling of MET cells, therefore providing a straightforward and intuitive differentiation method. We found that under lipopolysaccharide stimulation, macrophages undergo store-operated Ca 2+ entry (SOCE) to facilitate Ca 2+ influx. Elevation of cytoplasmic Ca 2+ levels by SOCE promotes the generation of superoxide anions by NADPH oxidase (NOX), ultimately leading to METosis. In summary, our study strengthens the role of Ca 2+ in NOX-dependent METosis, which differs from previous studies focusing on Ca 2+ in the NOX-independent pathway. Our research reveals that Ca 2+ -mediated regulation of NOX plays a crucial role in METosis, especially in SOCE, and provides novel ideas for future research.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Analysis of Deep Learning-Based Phase Retrieval Algorithm Performance for Quantitative Phase Imaging Microscopy
    (2022-05-01)
    Visitsattapongse, Sarinporn
    ;
    Thadson, Kitsada
    ;
    Pechprasarn, Suejit
    ;
    Thongpance, Nuntachai
    Quantitative phase imaging has been of interest to the science and engineering community and has been applied in multiple research fields and applications. Recently, the data-driven approach of artificial intelligence has been utilized in several optical applications, including phase retrieval. However, phase images recovered from artificial intelligence are questionable in their correctness and reliability. Here, we propose a theoretical framework to analyze and quantify the performance of a deep learning-based phase retrieval algorithm for quantitative phase imaging microscopy by comparing recovered phase images to their theoretical phase profile in terms of their correctness. This study has employed both lossless and lossy samples, including uniform plasmonic gold sensors and dielectric layer samples; the plasmonic samples are lossy, whereas the dielectric layers are lossless. The uniform samples enable us to quantify the theoretical phase since they are established and well understood. In addition, a context aggregation network has been employed to demonstrate the phase image regression. Several imaging planes have been simulated serving as input and the label for network training, including a back focal plane image, an image at the image plane, and images when the microscope sample is axially defocused. The back focal plane image plays an essential role in phase retrieval for the plasmonic samples, whereas the dielectric layer requires both image plane and back focal plane information to retrieve the phase profile correctly. Here, we demonstrate that phase images recovered using deep learning can be robust and reliable depending on the sample and the input to the deep learning.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Smart wheelchair based on eye tracking
    (2017-02-21)
    Wanluk, Nutthanan
    ;
    Visitsattapongse, Sarinporn
    ;
    Juhong, Aniwat
    ;
    Pintavirooj, C.
    This project is a smart wheelchair based on eye tracking which is designed for people with locomotor disabilities. The add-on controlled module can be used with any electrical wheelchair. The smart wheel chair consists of four modules including imaging processing module, wheelchair-controlled module, SMS manager module and appliance-controlled module. The image processing module comprises of a webcam installed on the eyeglass and C++ customized image processing software. The captured image which is transmitted to raspberry Pi microcontroller will be processed using OpenCV to derive the 2D direction of eye ball. The coordinate of eyeball movement is then wirelessly transmitted to wheelchair-controlled module to control the movement of wheel chair. The wheelchair-controlled module is two dimensional rotating stages that installed to the joystick of the electrical wheelchair to replace the manual control of the wheelchair. The motion of eyeball is also used as the cursor control on the raspberry Pi screen to control the operation of some equipped appliance and send message to smart phone.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Biosensors for Bacillus sphaericus detection to diagnostic Pseudotumor of the lung
    (2023-01-01)
    Vongmanee, Naphatsawan
    ;
    Visitsattapongse, Sarinporn
    In the present for diagnostic Pseudotumor in the lungs, X-ray image can help for diagnostic to the patient but could not approval the patient has got infection with bacteria type of Bacillus sphaericus. Diagnosis way of Pseudotumor in the lung by cause for this type of bacteria is very difficult because lesions are shown as pulmonary nodules or masses in which the border can be characteristically well distinguished on X-ray cannot approve infection with Bacillus sphaericus. For diagnostic need to confirm with result from laboratory and have a long time for get the result. So in this paper we will study about biosensors with molecular imprinting polymer for Bacillus sphaericus to examine the diagnosis and treatment of this disease for patient
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Automated segmentation of infarct lesions in t1‐weighted mri scans using variational mode decomposition and deep learning
    (2021-03-02)
    Paing, May Phu
    ;
    Tungjitkusolmun, Supan
    ;
    Bui, Toan Huy
    ;
    Visitsattapongse, Sarinporn
    ;
    Pintavirooj, Chuchart
    Automated segmentation methods are critical for early detection, prompt actions, and immediate treatments in reducing disability and death risks of brain infarction. This paper aims to develop a fully automated method to segment the infarct lesions from T1‐weighted brain scans. As a key novelty, the proposed method combines variational mode decomposition and deep learning-based segmentation to take advantages of both methods and provide better results. There are three main technical contributions in this paper. First, variational mode decomposition is applied as a pre-processing to discriminate the infarct lesions from unwanted non‐infarct tissues. Second, overlapped patches strategy is proposed to reduce the workload of the deep‐learning‐based segmentation task. Finally, a three‐dimensional U‐Net model is developed to perform patch‐wise segmentation of infarct lesions. A total of 239 brain scans from a public dataset are utilized to develop and evaluate the proposed method. Empirical results reveal that the proposed automated segmentation can provide promising performances with an average dice similarity coefficient (DSC) of 0.6684, intersection over union (IoU) of 0.5022, and average symmetric surface distance (ASSD) of 0.3932, respectively.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Automated Bacterial Colony Counting on Agar Plate
    (2023-01-01)
    Bunkum, Manao
    ;
    Visitsattapongse, Sarinporn
    In several fields, such as microbiology research, medical diagnostics, and food safety evaluation, bacterial colony counting is extremely important. However, the method of manual counting is time-consuming, labor-intensive, and prone to human error. This research approached these problems by using MATLAB's image processing feature to automatically count the number of bacterial colonies on agar plates. This technique effectively detects bacterial colonies from photos of agar plates by using image analysis algorithms. The images of agar plates were captured while controlling the lighting and adjusting the size to achieve the highest possible image quality. This study encompassed 10 bacterial species, achieving an accuracy of approximately 80%. This level of precision underscores the reliability and effectiveness of our automated system.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Automatic detection of pulmonary nodules using three-dimensional chain coding and optimized random forest
    (2020-04-01)
    Paing, May Phu
    ;
    Hamamoto, Kazuhiko
    ;
    Tungjitkusolmun, Supan
    ;
    Visitsattapongse, Sarinporn
    ;
    Pintavirooj, Chuchart
    The detection of pulmonary nodules on computed tomography scans provides a clue for the early diagnosis of lung cancer. Manual detection mandates a heavy radiological workload as it identifies nodules slice-by-slice. This paper presents a fully automated nodule detection with three significant contributions. First, an automated seeded region growing is designed to segment the lung regions from the tomography scans. Second, a three-dimensional chain code algorithm is implemented to refine the border of the segmented lungs. Lastly, nodules inside the lungs are detected using an optimized random forest classifier. The experiments for our proposed detection are conducted using 888 scans from a public dataset, and achieves a favorable result of 93.11% accuracy, 94.86% sensitivity, and 91.37% specificity, with only 0.0863 false positives per exam.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Emergency Blower-Based Ventilator with Novel-Designed Ventilation Sensor and Actuator
    (2022-03-01)
    Pintavirooj, Chuchart
    ;
    Maneerat, Areerat
    ;
    Visitsattapongse, Sarinporn
    The ventilator, a life-saving device for COVID-19-infected patients, especially for pneu-monia patients whose lungs are infected, has overwhelmingly skyrocketed since the pandemic of COVID-19 diseases started in December 2019. As a result, many biomedical engineers have rushed to design and construct emergency ventilators, using the Ambu-bag squeezing ventilator to compensate for the insufficient ventilators supply. The Ambu-bag squeezing ventilator, however, suffers from the limitation of delivered tidal volume to the patient, the setting respiration rate and the noisy operational sound due to the movement of mechanic parts. The Ambu-bag based ventilator is, hence, not suitable for prolonged treatment of the patient. This paper presents a design and construction of a blower-based pressure-controlled ventilator for home-treatment COVID-19 patients featured with our novel-designed flow and pressure sensor, electronic peep valve and proportional controlled valve. Our proposed ventilator can be programmed with the suitable parameter setting depending upon the weight, height, gender, and blood oxygen saturation (SpO<inf>2</inf>) of the patients. This is useful in the current situation of COVID-19 pandemics, where trained medical staff is limited. The designed ventilator is also equipped with a safety mechanism, including an excessive-pressure-release valve, excessive flow rate, overpressure, and over-temperature blower to prevent any hazardous event. A home ventilator server is also set where all ventilator parameters will be acquired and broadcasted for remote access of the health provider. The designed blower-based ventilator has been calibrated and evaluated with a lung simulator and standard ventilator tester, including alarmed functions, safety mechanism, sound level, and regulated pressure. The respiration output graph is complied with the simulation. The blower-based ventilator for home-treatment COVID-19 patients is suitable for life support, commensurate with the strict requirements of the FDA for life-support ventilators, and ready to be tested with animal subjects in the next phase.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Optical-based foot plantar pressure measurement with application in human postural balance, gait and recognition analysis
    (2020-07-01)
    Keatsamarn, Tanapon
    ;
    Visitsattapongse, Sarinporn
    ;
    Pintavirooj, Chuchart
    ;
    Aoyama, Hisayuki
    In this research, we purposed the design of real-time low-cost marker-free optical-based plantar-pressure measurement with application in human postural control, gait and recognition analysis. The system consists of a series of digital cameras capture installed underneath the acrylic-top platform. Light of LED strip mounted along the side of the acrylic plate deflected by the pressure exerted between the glossy white paper installed in the top of acrylic and the acrylic plate to the digital cameras provides the color-coded plantar pressure image of the subject standing on the platform. The system can provide both static features and dynamic features. Our hybrid system consists of a series of USB cameras aligned under the acrylic-plate walking platform. The mosaic image processing is used to concatenate the captured image to increase the sensing area. Captured the image data in video mode, various dynamic parameters can be derived for further dynamic analysis. The image capturing in one specific frame can be used for static analysis. Application in human-postural measurement, gait analysis, and person identification indicate that our system is an all-in-one system for plantar pressure measurement.