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 40

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A Novel Approach for Optimizing Molecularly Imprinted Polymer Composition in Electrochemical Detection of Collagen Peptides
(2025-11-01)
Vongmanee, Naphatsawan
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Nampeng, Jindapa
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Rattanapithan, Katesirin
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Sriwichai, Phuritasinee
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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.
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Use of computational fluid dynamics nasal airflow measurement to design septoplasty: A pilot study
(2013-01-01)
Mahasittiwat, Visan
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Hemtiwakorn, Khaisang
;
Pintavirooj, Chuchart
Deviation in the nasal septum that obstructs airflow is a source of discomfort to patients. Areas of nasal malformation then, need to be identified before performing surgery. In the present study, the authors introduce the computational fluid dynamic (CFD) technique to predict regions of limited airflow based on CT scan reconstruction of the nasal cavity. The present study proposes to use CFD to identify regions of obstructed airflow and design a surgical procedure to correct them. The authors report three cases with obstructed nasal airflow together with CFD measurements before and after the surgery. Results indicate that CFD is useful to verify the areas of airflow abnormality and conform with the results obtained using other methods.
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An accurate forearm EMG signal classification method using two-channel electrode
(2013-01-01)
Sueaseenak, Direk
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Chanwimalueang, Theerasak
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Pintavirooj, Chuchart
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Sangworasil, Manas
An accurate electromyography (EMG) classification algorithm to control a virtual hand prosthesis with 12 degrees of freedom using two surface EMG electrodes is presented in this paper. We propose the application of independent component analysis (ICA) for blind-source separation of the EMG signals obtained from two electrodes. One of the problems affecting the EMG classification accuracy is the location dependence of the EMG signal due to the superposition of signals from multiple sources. ICA is used to separate the two signals obtained from two surface electrodes into two independent EMG signals prior to the feature extraction and classification processes. We demonstrate that the EMG classification accuracy can be improved using the ICA algorithm. We also propose a novel eigen-based feature that is extracted from the short-time Fourier transform (STFT) magnitude spectrum. Our new feature not only decreases feature dimensions but also performs better than other well-known features. We also implement the EMG classification scheme on the virtual robot arm. The performance shows promising result as indicated by a decrease in the Davies-Bolden (DB) index after applying the ICA. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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Design and Development of an Assistive System Based on Eye Tracking
(2022-02-01)
Paing, May Phu
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Juhong, Aniwat
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Pintavirooj, Chuchart
This research concerns the design and development of an assistive system based on eye tracking, which can be used to improve the quality of life of disabled patients. With the use of their eye movement, whose function is not affected by their illness, patients are capable of communicating with and sending notifications to caretakers, controlling various appliances, including wheelchairs. The designed system is divided into two subsystems: Stationary and mobile assistive systems. Both systems provide a graphic user interface (GUI) that is used to link the eye tracker with the appliance control. There are six GUI pages for the stationary assistive system and seven for the mobile assistive system. GUI pages for the stationary assistive system include the home page, smart appliance page, eye-controlled television page, eye-controlled air conditional page, i-speak page and entertainment page. GUI pages for the mobile assistive system are similar to the GUI pages for the stationary assistive system, with the additional eye-controlled wheelchair page. To provide hand-free secure access, an authentication based on facial landmarks is developed. The operational test of the proposed assistive system provides successful and promising results.
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Multi-parameter vital sign telemedicine system using web socket for covid-19 pandemics
(2021-03-01)
Pintavirooj, Chuchart
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Keatsamarn, Tanapon
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Treebupachatsakul, Treesukon
Telemedicine has become an increasingly important part of the modern healthcare infras-tructure, especially in the present situation with the COVID-19 pandemics. Many cloud platforms have been used intensively for Telemedicine. The most popular ones include PubNub, Amazon Web Service, Google Cloud Platform and Microsoft Azure. One of the crucial challenges of telemedicine is the real-time application monitoring for the vital sign. The commercial platform is, by far, not suitable for real-time applications. The alternative is to design a web-based application exploiting Web Socket. This research paper concerns the real-time six-parameter vital-sign monitoring using a web-based application. The six vital-sign parameters are electrocardiogram, temperature, plethysmogram, percent saturation oxygen, blood pressure and heart rate. The six vital-sign parameters were encoded in a web server site and sent to a client site upon logging on. The encoded parameters were then decoded into six vital sign signals. Our proposed multi-parameter vital-sign telemedicine system using Web Socket has successfully remotely monitored the six-parameter vital signs on 4G mobile network with a latency of less than 5 milliseconds.
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Adenoma Dysplasia Grading of Colorectal Polyps Using Fast Fourier Convolutional ResNet (FFC-ResNet)
(2023-01-01)
Paing, May Phu
;
Pintavirooj, Chuchart
Colorectal polyps are precursor lesions of colorectal cancer; hence, early detection and dysplasia grading of polyps are essential for determining cancer risk, the possibility of developing subsequent polyps, and follow-up recommendations. The significant contribution of this study is the development of an enhanced deep-learning model called Fast Fourier Convolutional ResNet (FFC-ResNet) to classify dysplasia grades of polyps. It is based on the ResNet-50 architecture and uses cross-feature fusion, which combines local features extracted by traditional spatial convolution with global features extracted by Fourier convolution. Due to the compensatory effect between local and global features, the learnability and performance of FFC-ResNet have increased. The proposed FFC-ResNet was developed and tested using UniToPatho, a dataset containing 7000 μm and 800 μm hematoxylin-and-eosin (H&E)-stained colorectal images. And a favorable performance of sensitivity 0.95, specificity 0.93, balance accuracy 0.94, precision 0.95, F1 score 0.95, and AUC 0.99 was obtained using 800 μm polyp patches.
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A numerical model for ultrasonic measurements of swelling and mechanical properties of a swollen PVA hydrogel
(2010-08-01)
Lohakan, M.
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Jamnongkan, T.
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Pintavirooj, C.
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Kaewpirom, S.
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Boonsang, S.
This paper presents a numerical model for the evaluation of mechanical properties of a relatively thin hydrogel. The model utilizes a system identification method to evaluate the acoustical parameters from ultrasonic measurement data. The model involves the calculation of the forward model based on an ultrasonic wave propagation incorporating diffraction effect. Ultrasonic measurements of a hydrogel are also performed in a reflection mode. A Nonlinear Least Square (NLS) algorithm is employed to minimize difference between the results from the model and the experimental data. The acoustical parameters associated with the model are effectively modified to achieve the minimum error. As a result, the parameters of PVA hydrogels namely thickness, density, an ultrasonic attenuation coefficient and dispersion velocity are effectively determined. In order to validate the model, the conventional density measurements of hydrogels were also performed. © 2010 Elsevier B.V. All rights reserved.
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Patient-specific aided surgery approach of deviated nasal septum using computational fluid dynamics
(2015-05-01)
Hemtiwakorn, Khaisang
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Mahasitthiwat, Visan
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Tungjitkusolmun, Supan
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Hamamoto, Kazuhiko
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Pintavirooj, Chuchart
In treating a patient with deviated nasal septum (DNS), a surgeon draws up a surgical plan based on the patient's rhinomanometry outcomes and self-assessment of nose conditions, e.g. the nasal obstruction septoplasty effectiveness (NOSE) score. However, the procedure fails to localize the DNS and determine the nose's aerodynamic effects. This paper proposes a DNS-aided surgery approach using computational fluid dynamics (CFD) and computed tomography (CT) techniques consisting of three main processes: preoperative, presurgical planning, and postoperative processes. The healthy baseline refers to a benchmark consisting of five subjects without DNS and nasal airway obstructions. To assess the possibility of using the CFD-CT-aided surgery approach as a presurgical planning tool in the DNS operation, comparative tests were carried out with DNS patient #1, who received a conventional nasal surgery without the proposed presurgical planning. Although DNS patient #1's surgical outcome was relatively satisfying to the patient, evaluating from the reduction of the NOSE score the conventional surgical method could induce an excessive excision of nasal airway, resulting in water loss in the nasal mucosa and a large reduction in airflow velocity. In addition, the postoperative nasal resistance measured by a rhinomanometer was not acceptable to the surgeon. Virtual surgery using the CFD-CT approach performed after surgery could suggest suitable patient-specific components of nasal operation with predictable results. Subsequently, implementation of the proposed CFD-CT approach in aid of DNS surgery was performed in DNS patient #2. The benefits of the CFD-CT-aided surgery approach were determined based on the pre- and postoperative outcomes (i.e. nasal geometric data and nasal airflow patterns), NOSE scores, and rhinomanometric data of DNS patient #2, which were compared against those of the healthy baseline benchmark. The CFD-CT approach could assist the surgeon to localize the DNS and determine the defective nasal tissues to be removed. The actual postoperative outcomes were clinically acceptable to the surgeon and DNS patient #2. It is evident that the CFD-CT-aided surgery approach is suitable for and applicable to surgery of DNS patients with small variability from the presurgical planning stage.
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Hybrid facial features with application in person identification
(2020-08-14)
Purahong, Boonchana
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Chutchavong, Vanvisa
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.
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Vein pattern verification and identification based on local geometric invariants constructed from minutia points and augmented with barcoded local feature
(2020-05-01)
Pititheeraphab, Yutthana
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Thongpance, Nuntachai
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Aoyama, Hisayuki
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Pintavirooj, Chuchart
This paper presents the development of a hybrid feature-dorsal hand vein and dorsal geometry-modality for human recognition. Our proposed hybrid feature extraction method exploits two types of features: dorsal hand geometric-related and local vein pattern. Using geometric affine invariants, the peg-free system extracts minutia points and vein termination and bifurcation and constructs a set of geometric invariants, which are then used to establish the correspondence between two sets of minutiae-one for the query vein image and the other for the reference vein image. When the correspondence is established, geometric transformation parameters are computed to align the query with the reference image. Once aligned, hybrid features are extracted for identification. In this study, the algorithm was tested on a database of 140 subjects, in which ten different dorsal hand geometric-related images were taken for each individual, and yielded the promising results. In this regard, we have achieved an equal error rate (EER) of 0.243%, indicating that our method is feasible and effective for dorsal vein recognition with high accuracy. This hierarchical scheme significantly improves the performance of personal verification and/or identification.

Pintavirooj, Chuchart

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