Pintavirooj, Chuchart

Preferred name

Alternative Name

Pintavirooj, C.

Pintavirooj, Chuchat

Main Affiliation

School of Engineering

chuchart.pi@kmitl.ac.th

Now showing 1 - 10 of 20

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A Novel Approach for Optimizing Molecularly Imprinted Polymer Composition in Electrochemical Detection of Collagen Peptides
(2025-11-01)
Vongmanee, Naphatsawan
;
Nampeng, Jindapa
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Rattanapithan, Katesirin
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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 (R2 = 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.
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Automated segmentation of infarct lesions in t1‐weighted mri scans using variational mode decomposition and deep learning
(2021-03-02)
Paing, May Phu
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Tungjitkusolmun, Supan
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Bui, Toan Huy
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Visitsattapongse, Sarinporn
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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.
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Automatic detection of pulmonary nodules using three-dimensional chain coding and optimized random forest
(2020-04-01)
Paing, May Phu
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Hamamoto, Kazuhiko
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Tungjitkusolmun, Supan
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Visitsattapongse, Sarinporn
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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.
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Emergency Blower-Based Ventilator with Novel-Designed Ventilation Sensor and Actuator
(2022-03-01)
Pintavirooj, Chuchart
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Maneerat, Areerat
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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.
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Optical-based foot plantar pressure measurement with application in human postural balance, gait and recognition analysis
(2020-07-01)
Keatsamarn, Tanapon
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Visitsattapongse, Sarinporn
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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.
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Ultrasensitive Label-Free Electrochemical Detection of Pseudomonas aeruginosa Using a Surface Molecularly Imprinted Polymer-Modified Screen-Printed Electrode
(2026-06-01)
Vongmanee, Naphatsawan
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Nampeng, Jindapa
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Pintavirooj, Chuchart
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Visitsattapongse, Sarinporn
Pseudomonas aeruginosa is a major opportunistic pathogen frequently associated with nosocomial infections, such as pneumonia, urinary tract infections, and wound infections, particularly in immunocompromised or hospitalized patients. These infections are often difficult to treat due to the pathogen’s intrinsic antibiotic resistance and biofilm-forming ability. Therefore, rapid and selective detection of P. aeruginosa is essential for early diagnosis and effective infection control. In this study, a novel surface-imprinted MIP design uniquely combines methacrylamide (MAM), acrylamide (AAM), and vinylpyrrolidone (VP) monomers to generate recognition cavities that are complementary to the surface morphology and physicochemical properties of Pseudomonas aeruginosa cells. Unlike traditional MIP approaches, this surface imprinting strategy provides improved stability and reproducibility, without relying on biological recognition elements like antibodies or aptamers. This novel approach enabled us to achieve an ultralow LOD of 1 CFU/mL over a linear range of 1–104 CFU/mL, demonstrating excellent analytical performance. In addition, the sensor exhibited good reproducibility with an RSD of 5–12%. The novelty of this work lies in the use of a surface-imprinted MIP strategy combined with a multi-monomer system to enhance bacterial recognition and sensing performance. Overall, the proposed MIP-based electrochemical biomimetic sensor offers a rapid, cost-effective, and portable platform with strong potential for the detection of P. aeruginosa in clinical and environmental applications.
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Electrochemical Characterization of a Molecularly Imprinted Polymer Sensor for the Selective Recognition of Type II Collagen in Joint Degeneration Monitoring
(2026-02-01)
Nampeng, Jindapa
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Vongmanee, Naphatsawan
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Pintavirooj, Chuchart
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Visitsattapongse, Sarinporn
Type II collagen is a primary fibrillar component of articular cartilage, and its early degradation is a key biomarker of joint-degenerative disorders such as osteoarthritis, rheumatoid arthritis, gout, etc. Reliable detection at low concentrations remains challenging due to limited assay accessibility, complex analytical procedures, and nonspecific responses in multicomponent biological matrices. This research reports the development of a Molecularly Imprinted Polymer (MIP)–based electrochemical sensor engineered for the selective recognition of type II collagen. A series of monomer formulations were evaluated, and the 1AAM:2VP composition produced a well-defined imprinted layer on screen-printed carbon electrodes, yielding the highest electrochemical sensitivity and linearity. The optimized sensor exhibited strong anodic and cathodic responses proportional to increasing collagen concentrations, with a calibration slope corresponding to an R2 value of 0.9394. Minimal signal interference was observed, confirming high molecular selectivity. The limit of detection (LOD) was calculated to be approximately 0.065 µg/mL. These characteristics demonstrate that the proposed MIP sensor provides a low-cost, accessible, and highly selective analytical platform suitable for early-stage cartilage degeneration monitoring.
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Biosensors for Klebsiella pneumoniae with Molecularly Imprinted Polymer (MIP) Technique
(2022-06-01)
Pintavirooj, Chuchart
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Vongmanee, Naphatsawan
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Sukjee, Wannisa
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Sangma, Chak
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Visitsattapongse, Sarinporn
Nosocomial infection is one of the most important problems that occurs in hospitals, as it directly affects susceptible patients or patients with immune deficiency. Klebsiella pneumoniae (K. pneu-moniae) is the most common cause of nosocomial infections in hospitals. K. pneumoniae can cause various diseases such as pneumonia, urinary tract infections, septicemias, and soft tissue infections, and it has also become highly resistant to antibiotics. The principal routes for the transmission of K. pneumoniae are via the gastrointestinal tract and the hands of hospital personnel via healthcare workers, patients, hospital equipment, and interventional procedures. These bacteria can spread rapidly in the hospital environment and tend to cause nosocomial outbreaks. In this research, we developed a MIP-based electrochemical biosensor to detect K. pneumoniae. Quantitative detection was performed using an electrochemical technique to measure the changes in electrical signals in different concentrations of K. pneumoniae ranging from 10 to 105 CFU/mL. Our MIP-based K. pneumoniae sensor was found to achieve a high linear response, with an R2 value of 0.9919. A sensitivity test was also performed on bacteria with a similar structure to that of K. pneumoniae. The sensitivity results show that the MIP-based K. pneumoniae biosensor with a gold electrode was the most sensitive, with a 7.51 (% relative current/log concentration) when compared with the MIP sensor applied with Pseudomonas aeruginosa and Enterococcus faecalis, where the sensitivity was 2.634 and 2.226, respectively. Our sensor was also able to achieve a limit of detection (LOD) of 0.012 CFU/mL and limit of quantitation (LOQ) of 1.61 CFU/mL.
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Bone mineral density screening system using CMOS-sensor X-ray detector
(2021-11-01)
Maneerat, Areerat
;
Visitsattapongse, Sarinporn
;
Pintavirooj, Chuchart
This research concerns a design and construction of a bone mineral density (BMD) and bone mineral content (BMC) measurement system based on dual energy x-ray absorptiometry (DEXA). An indirect x-ray detector is designed by optical coupling CMOS sensor with image on the intensifying screen. A dedicated microcontroller x-ray apparatus is used as an x-ray source to cap-ture two energy level x-ray of middle phalanges bone of middle finger. The captured image is processed based on modified Beer-Lambert law to compute bone mineral density. Bone mineral content is also computed by determining the area of the phalanges bone using active contour. The designed bone mineral density (BMD) and bone mineral content (BMC) measurement system is low-cost and hence can be distributed at district hospital for screening purposes of Osteoporosis of the elderly. Compared with BMD measured from commercial model, BMD measurement of our system ac-quires linear relation with R2 equals 0.969. The mean square error between the normalized BMD value and that of the commercial model is 0.0000981.
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Electrochemical Biosensors by Means of Molecularly Imprinted Polymers (MIPs) Cortisol Recognition
(2025-02-01)
Nampeng, Jindapa
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Vongmanee, Naphatsawan
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Pintavirooj, Chuchart
;
Chiu, Wen Tai
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Visitsattapongse, Sarinporn
Depression and anxiety are two common mental health issues that require serious attention, as they have significant impacts on human well-being, with both being emotionally and physically reflected in the increasing number of suicide cases globally. The World Health Organization (WHO) estimated that about 322 million people around the world experienced mental illnesses in 2017, and this number continues to increase. Cortisol is a major stress-controlled hormone that is regulated by the hypothalamic–pituitary–adrenal (HPA) axis. The HPA axis has three main components, including the hypothalamus, pituitary gland, and adrenal gland, where cortisol, the primary stress hormone, is released. It plays crucial roles in responding to stress, energy balance, and the immune system. The cortisol level in the bloodstream usually increases when stress develops. Molecularly imprinted polymers (MIPs) have been highlighted in terms of creating artificial bioreceptors by mimicking the shape of detected biomolecules, making natural bioreceptor molecules no longer required. MIPs can overcome the limitations of chemicals and physical properties reducing over time and the short-time shelf life of natural bioreceptors. MIPs’ benefits are reflected in their ease of use, high sensitivity, high specificity, reusability, durability, and the lack of requirement for complicated sample preparation before use. Moreover, MIPs incur low costs in manufacturing, giving them a favorable budget for the market with simple utilization. MIPs can be formulated by only three key steps, including formation, the polymerization of functional monomers, and the creation of three-dimensional cavities mimicking the shape and size of targeting molecules. MIPs have a high potential as biosensors, especially working as bioanalytics for protein, anti-body, antigen, or bacteria detection. Herein, this research proposes an MIP-based cortisol biosensor in which cortisol is imprinted on methyl methacrylate (MMA) and methacrylic acid (MAA) produced by UV polymerization. This MIP-based biosensor may be an alternative method with which to detect and monitor the levels of hormones in biological samples such as serum, saliva, or urine due to its rapid detection ability, which would be of benefit for diagnosing depression and anxiety and prescribing treatment. In this study, quantitative detection was performed using an electrochemical technique to measure the changes in electrical signals in different concentrations of a cortisol solution ranging from 0.1 to 1000 pg/mL. The MIP-based biosensor, as derived by calculation, achieved its best detection limit of 1.035 pg/mL with a gold electrode. Tests were also performed on molecules with a similar molecular structure, including Medroxyprogesterone acetate and drospirenone, to ensure the sensitivity and accuracy of the sensors, demonstrating a low sensitivity and low linear response.

Pintavirooj, Chuchart

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