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Preliminary study of the polymesoda expansa based hydroxyapatite for medical devices coating application

AIP Conference Proceedings 2020年第1期2306卷

作者： M. Riza Roslan N. F. Mohd Nasir M. A. Gilani Nur Farahiyah Mohammad E. M Cheng M. F. Abdul Khalid A. S. Zoolfakar N. A. M. Amin S. F. Khan 1Biomedical Electronic Engineering Program School of Mechatronic Engineering Universiti Malaysia Perlis Perlis Malaysia 2Microwave Research Institute (MRI) Universiti Teknologi Mara Shah Alam Malaysia 3Faculty of Electrical Engineering Universiti Teknologi Mara Shah Alam Malaysia 4Mechanical Engineering Program School of Mechatronic Engineering Universiti Malaysia Perlis Perlis Malaysia

Hydroxyapatite (HA) which is a group of calcium phosphate (CaP) is used as a medical devices coating due to its ability to increase the bioactivity and biocompatibility of the device surface. The attraction of using waste seashells products is interesting due to its sustainability and low cost solution especially in biomedical application. Polymesoda expansa or locally known as Lokan is potentially rich with calcium carbonate (CaCO3). Here, the synthesis of HA was done via precipitation method by utilizing the Polymesoda expansa (Lokan) shells as the resource of calcium precursors. Hydroxyapatite synthesized from Polymesoda expansa was carried out with different pH solution (pH 9 and 13) in alkaline environment. The effects of pH on the morphological and chemical composition properties as well as the Ca/P ratio of HA powders were analyzed through Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Energy Dispersive X-ray Spectrometry (EDS). The finding demonstrates as the pH increases, the calcium apatite reduced and this had increases the Ca/P ratio.

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Lumen and nuclei detection in histopathology of prostate cancer based on morphological feature extraction

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AIP Conference Proceedings 2023年第1期2554卷

作者： S. T. Yukiko Irliyani Riries Rulaningtyas S. Anny Rahaju I. Made Mas Dwiyana Prasetya Wibawa 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Airlangga University Surabaya Indonesia 2Anatomical Pathology Department Medical Faculty Universitas Airlangga Dr. Soetomo Academic Hospital Universitas Airlangga Hospital Surabaya Indonesia

Prostate cancer is the most common cancer in men. The results of a fast and precise classification can be a fundamental objective of reference. Histological assessment is valuable information for doctors. The most common assessment for histological assessment of prostate cancer is the Gleason Grading System. Gleason pattern detection was done by extracting morphological features in the form of Line Length, Area Fraction, and the comparison between Line Length and Area Fraction. All morphological features become the input of backpropagation. Based on the results of backpropagation testing, this method can classify Gleason pattern images with an accuracy of 91.67%. The threshold of segmentation in determining the lumen and nucleus did not have a specific range in its threshold due to the lack of uniform contrast in each image.

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Collagen-chitosan scaffold - Lauric acid plasticizer for skin tissue engineering on burn cases

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AIP Conference Proceedings 2017年第1期1817卷

作者： Prihartini Widiyanti Ewing Dian Setyadi Djony Izak Rudyardjo 1Biomedical Engineering Faculty of Science and Technology Universitas Airlangga Mulyorejo Surabaya 60115 Indonesia 2Institute of Tropical Disease Universitas Airlangga Mulyorejo Surabaya 60115 Indonesia 3Physics Study Program Faculty of Science and Technology Universitas Airlangga Mulyorejo Surabaya 60115 Indonesia

The prevalence of burns in the world is more than 800 cases per one million people each year and this is the second highest cause of death due to trauma after traffic accident. Many studies are turning to skin substitute methods of tissue engineering. The purpose of this study is to determine the composition of the collagen, chitosan, and lauric acid scaffold, as well as knowing the results of the characterization of the scaffold. The synthesis of chitosan collagen lauric acid scaffold as a skin tissue was engineered using freeze dried method. Results from making of collagen chitosan lauric acid scaffold was characterized physically, biologically and mechanically by SEM, cytotoxicity, biodegradation, and tensile strength. From the morphology test, the result obtained is that pore diameter size ranges from 94.11 to 140.1 µm for samples A,B,C,D, which are in the range of normal pore size 63-150 µm, while sample E has value below the standard which is about 37.87 to 47.36 µm. From cytotoxicity assay, the result obtained is the percentage value of living cells between 20.11 to 21.51%. This value is below 50% the standard value of living cells. Incompatibility is made possible because of human error mainly the replication of washing process over the standard. Degradation testing obtained values of 19.44% - 40% by weight which are degraded during the 7 days of observation. Tensile test results obtained a range of values of 0.192 - 3.53 MPa. Only sample A (3.53 MPa) and B (1.935 MPa) meet the standard values of skin tissue scaffold that is 1-24 MPa. Based on the results of the characteristics of this study, composite chitosan collagen scaffold with lauric acid plasticizer has a potential candidate for skin tissue engineering for skin burns cases.

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Expert system for risk prediction of cesarean section delivery with Dempster Shafer method

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AIP Conference Proceedings 2020年第1期2314卷

作者： Ismaiba Riries Rulaningtyas Katherine Ernawati 1Biomedical Engineering Program Study Faculty of Science and Technology Universitas Airlangga Campus C Zip Code: 60115 Surabaya East Java Indonesia 2Fetomaternal Division of Obstetrics and Gynecology Department Faculty of Medicine Universitas Airlangga Campus A Zip Code: 60131 Surabaya East Java Indonesia

The maternal mortality rate in Indonesia is related to the lack of knowledge of mothers regarding high-risk pregnancies, especially with cesarean delivery. In this case, the prediction system designed is done as an effort to increase the awareness of mothers or women who were preparing for high-risk pregnancies. In this article, an Android-based prediction application will be presented using an expert system with the Dempster Shafer method. This method is based on a mathematical theory which consists of a combination of belief function and plausible reasoning from the risk parameters of each labor class by representing the knowledge obtained from experts. This study uses 16 risk parameters as input based on Poejo Rochati's high-risk pregnancy card with 2 outputs, with risk or no risk of having cesarean delivery. The result obtained from this system is 85%, concludes that the prediction system is able to predict the risk of cesarean delivery.

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EEG channels reduction using PCA to increase XGBoost’s accuracy for stroke detection

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AIP Conference Proceedings 2017年第1期1862卷

作者： N. Fitriah S. K. Wijaya M. I. Fanany C. Badri M. Rezal 1Biomedical Engineering Study Program Universitas Indonesia Jl. Salemba Raya No. 4 Jakarta 10430 DKI Jakarta Indonesia 2Department of Physics Faculty of Mathematics and Natural Sciences (FMIPA) Universitas Indonesia Depok 16424 Indonesia 3Faculty of Computer Science Universitas Indonesia Depok 16424 Indonesia

In Indonesia, based on the result of Basic Health Research 2013, the number of stroke patients had increased from 8.3 ‰ (2007) to 12.1 ‰ (2013). These days, some researchers are using electroencephalography (EEG) result as another option to detect the stroke disease besides CT Scan image as the gold standard. A previous study on the data of stroke and healthy patients in National Brain Center Hospital (RS PON) used Brain Symmetry Index (BSI), Delta-Alpha Ratio (DAR), and Delta-Theta-Alpha-Beta Ratio (DTABR) as the features for classification by an Extreme Learning Machine (ELM). The study got 85% accuracy with sensitivity above 86 % for acute ischemic stroke detection. Using EEG data means dealing with many data dimensions, and it can reduce the accuracy of classifier (the curse of dimensionality). Principal Component Analysis (PCA) could reduce dimensionality and computation cost without decreasing classification accuracy. XGBoost, as the scalable tree boosting classifier, can solve real-world scale problems (Higgs Boson and Allstate dataset) with using a minimal amount of resources. This paper reuses the same data from RS PON and features from previous research, preprocessed with PCA and classified with XGBoost, to increase the accuracy with fewer electrodes. The specific fewer electrodes improved the accuracy of stroke detection. Our future work will examine the other algorithm besides PCA to get higher accuracy with less number of channels.

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Finite element analysis of posterior leaf spring ankle-foot orthosis for tibialis anterior atrophy case

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AIP Conference Proceedings 2022年第1期2663卷

作者： Alfian Pramudita Putra Arief Sofian Hidayat Akif Rahmatillah Pujiyanto Pujiyanto Dinda Cyberputri I. Putu Alit Pawana 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 2Biomedical Signals and Systems Research Group Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 3Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 4Department of Rehabilitation and Physical Medicine Dr. Soetomo General Academic Hospital Surabaya Indonesia

Stroke is a neurological disease and is a significant cause of disability throughout the world. Patients with stroke or post-stroke usually still experience interference in walking in the form of a drop foot caused by atrophy of the anterior tibialis muscle, so they cannot perform dorsiflexion. Drop foot disorders can be treated by rehabilitation using Posterior Leaf Spring Ankle-Foot Orthosis (PLS AFO). PLS AFO has the advantage of a higher level of flexibility compared to other AFO types. The primary purpose of this research is to observe the level of resilience based on the influence of AFO thickness. This study uses the finite element analysis of three model variations in the initial contact, midstance, terminal stance, and calf loading phases. The material used in this study was carbon fiber. The simulation will result in the distribution of stress, strain, and deformation values in each AFO model. The simulation results show that AFO resistance is affected by variations in AFO thickness where the increase in strength is proportional to the increase in AFO thickness. The AFO with a thickness of 10 mm is the most suitable for the tibialis anterior atrophy case.

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