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Advances in Science and engineering Technology International Conferences (ASET)

作者： Rabah M. Al Abdi Amer Zakaria Hasan Al Nashash Tasnim Zalak Nandu Goswami Vishwa Jeet Dept. of Biomedical Engineering Jordan Univ. Of Science and Tech. Irbid Jordan Dept. of Electrical Engineering American University of Sharjah Sharjah UAE Master of Science in Biomedical Engineering Program American University of Sharjah Sharjah UAE College of Medicine Mohammed Bin Rashed University of Medicine and Health Sciences Dubai UAE

Peripheral arterial disease (PAD) is the narrowing of the arteries within the lower extremities, which inhibits blood flow to the foot. We present the use of dynamic diffuse optical tomography (DDOT) system to measure blood flow in the foot during venous and arterial occlusions. DDOT is a non-ionizing, contrast-free, and fast imaging modality. The DDOT system consists of 4 sensors, each containing four laser diodes (at wavelengths of 670, 780, 808, and 850 nm) and two silicon photodiodes. We examined 11 healthy subjects with a protocol consisting of five consecutive measurements. Biomarkers were extracted from changes in hemoglobin concentrations during the measurements. The results from a pilot study are presented in this report. The average increase in total hemoglobin was $\mathbf{17.2\pm 5.8}\ \mu \mathbf{M}$ during a measurement with 60 mmHg occlusion and $\mathbf{10.4\pm 6.7} \ \mu \mathbf{M}$ during a measurement with 180 mmHg occlusion. The biomarkers can quantify blood perfusion and oxygen consumption in the foot, and they have the potential to detect and monitor PAD.

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Low-intensity electrical stimulation and stem cells in a dog with acute spinal cord injury

Low-intensity electrical stimulation and stem cells in a dog...

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International Conference on biomedical engineering (IBIOMED)

作者： Eddy Krueger Lidiane M. S. Magri Agatha S. Botelho Fernando S. Bach Carmen L. K. Rebellato Letícia Fracaro Felipe Y. I. Fragoso José A. Villanova Paulo R. S. Brofman Lana Popović-Maneski Graduate Program in Biomedical Engineering Technological Federal University Curitiba Paraná Brazil Master and Doctoral Program in Rehabilitation Sciences UEL-I TNOPAR State University of Londrina Londrina Brazil Graduate Program in Biomedical Engineering Technological Federal University - Paraná Curitiba Brazil Federal University of Paraná Curitiba Brazil Pontificial Catholical University of Paraná Curitiba Brazil Institute of Technical Sciences of the Serbian Academy of Sciences and Arts Belgrade Serbia

Spinal cord injury (SCI) is classified as neurological disorder that affects motor and sensory function below the injury level. Studies show that application of low-intensity electrical stimulation (LIES) to neural tissue increases neurochemical factors responsible for regeneration as nerve growth factor. Stem cell (SC) therapy for patients with SCI can result in the replacement of injured neurons after trauma. The electromechanical delay (EMD) is defined as time elapsed between the onset of muscle electrical activation and onset of force production. A dog diagnosed with incomplete thoracolumbar SCI followed by disc hernia between the vertebral segments LI and L2, was evaluated by electromyography and mechanomyography after surgical decompression procedure, one SC transplantation and LIES. We observed motor response and decrease in the EMD from 8.25ms to 5.75ms after the procedures. The wavelet decomposition of EMG signals showed reestablishment of vastus lateralis muscle activity 30 days after the procedure. In addition, the EMG RMS increased from 3.3 µV RMS to 157 µV RMS . The preliminary results of this case report indicate positive effects of the hybrid therapy involving stem cells and low-intensity electrical stimulation after surgical decompression.

关键词： Dogs Injuries Stem cells Surgery

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WARMING EFFECT of BLANKETS with HIGH FAR-INFRARED EMISSIVITY on SKIN MICROCIRCULATION in TYPE 2 DIABETIC PATIENTS

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biomedical engineering - Applications, Basis and Communications 2020年第6期32卷

作者： Bau, Jian-Guo Yang, Chun-Pai Huang, Bo-Wen Lin, Yung-Sheng Wu, Ming-Feng Hungkuang University Department of Biomedical of Engineering Taichung Taiwan Department of Neurology Kuang Tien General Hospital Taichung Taiwan Department of Nutrition Hungkuang University Taichung Taiwan Feng Chia University Master's Program of Bioinformatics and Biomedical Engineering Taichung Taiwan National United University Department of Chemical Engineering Miaoli Taiwan Department of Medical Intensive Care Unit Kuang Tien General Hospital Taichung Taiwan

Vascular complications are responsible for most of the morbidity and mortality in diabetic patients. Effective strategies to improve circulation appear to be another important issue in addition to the interventions of blood glucose control. Previous studies have shown that the biological effects on humans after using the materials containing ceramic particles emits far infrared radiation (FIR). The present study is to investigate the warming effect of the fabrics containing specified metals in diabetic patients. A total of 28 diabetic patients were blinded and randomly assigned to treatment group (N = 18) and control group (N = 10), respectively. The subjects of treatment group were ministered with the blankets with fibers containing the specified metals, while the subjects of control group were provided with blankets of ordinary material. The skin temperature and microcirculatory perfusion were monitored before and after 20-min use of the blankets at shoulder and bilateral calves. After warming with blankets, the treatment group revealed a higher increased ratio of skin perfusion than control (p © 2020 National Taiwan University.

关键词： Infrared radiation

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A Computationally Efficient Algorithm for Estimating Respiratory Rate from Seismocardiogram

SSRN

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SSRN 2024年

作者： Ku, Tienhsiung Lin, Yue-Der Department of Anesthesiology Changhua Christian Hospital Changhua50051 Taiwan Artificial Intelligence Development Center Changhua Christian Hospital Changhua50051 Taiwan Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung40724 Taiwan

Respiratory rate (RR) monitoring is crucial in clinical and healthcare settings. With the advancements in microelectromechanical system (MEMS) technology, monitoring respiration using seismocardiogram (SCG) is emerging as a promising approach. This study presents a computationally efficient algorithm for estimating RR from SCG signal. The proposed algorithm consists of two primary steps: firstly applying Gaussian averaging filter for pre-processing and next computing the averaged spectrum from the scalogram based on complex Morlet wavelet within the specified frequency range. RR is then estimated from the dominant frequency appeared in the averaged spectrum. This study also establishes the analytical relationship between the parameters of Gaussian averaging filter and the sampling frequency of SCG signal, which serves as the design criterion for pre-processing filter. The proposed algorithm undergoes testing on two SCG datasets and has demonstrated its feasibility for estimating RR from SCG signal. Furthermore, the algorithm is also tested on both finger and wrist PPG datasets for RR estimation. The test results present high agreement between the RR estimations from SCG (or PPG) signal and those from respiration signal. Based on these testing results, the proposed algorithm shows significant potential in clinical and healthcare applications. © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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Prediction of anterior cruciate ligament injury from MRI using deep learning

Prediction of anterior cruciate ligament injury from MRI usi...

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International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Truong, Nguyen Khanh Hung Nguyen, Thuan Phuoc Kha, Quang Hien Le, Ngoc Hoang Le, Van Tuan Cao, Thi Luu, Ho Thanh Lam Le, Nguyen Quoc Khanh Kang, Jiunn-Horng International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Orthopedic and Trauma Cho Ray Hospital Ho Chi Minh city Viet Nam Mechatronics Engineering Ho Chi Minh City University of Technology Ho Chi Minh city Viet Nam Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan Orthopedic and Rehabilitation Department University of Medicine and Pharmacy at Ho Chi Minh city Ho Chi Minh city Viet Nam Children's Hospital 2 Ho Chi Minh City Viet Nam Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei Taiwan Department of Physical Medicine and Rehabilitation Taipei Medical University Hospital Taipei Taiwan Department of Physical Medicine and Rehabilitation School of Medicine College of Medicine Taipei Medical University Taipei Taiwan

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Knee injury emerges as one of the most common diseases, causing dislocation of knee joints, immobility, etc., in which the anterior cruciate ligament (ACL) injury is the most common one. The development of various artificial intelligence (AI) frameworks gained enormous attention in many areas, including injury prediction and health management via medical image analysis. The objective of the current study is to focus on a comprehensive high accurate prediction of ACL injury based on MRI medical images, and also demonstrate the ability of AI in practical and outline conceptual prediction and diagnosis frameworks for other types of knee injuries in the future. Our dataset comprised of knee MRI reports from Cho Ray Hospital, Vietnam which are composed of ACL and non-ACL injury patients. The MRI images were used as supporting data in the deep learning classification model with DenseNet-121 algorithm. The successful establishment of an ACL injury diagnosis model from MRI will pave the way for us to develop more diagnostic models of other injuries in the body as well as the prediction of bone diseases. © 2021 SPIE.

关键词： Magnetic resonance imaging

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Respiratory acoustic thoracic imaging (RATHI): Assessing intrasubject variability

Respiratory acoustic thoracic imaging (RATHI): Assessing int...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： A. Torres-Jimenez S. Charleston-Villalobos R. Gonzalez-Camarena G. Chi-Lem T. Aljama-Corrales Master student of the Biomedical Engineering Program Universidad Autonoma Metropolitana Mexicali Mexico Electrical Engineering Department Universidad Autonoma Metropolitana Mexicali Mexico Health Science Department Universidad Autonoma Metropolitana Mexicali Mexico Pulmonary Acoustic Laboratory National Institute of Respiratory Diseases Mexicali Mexico

Respiratory acoustic thoracic imaging (RATHI) permits analysing lung sounds (LS) temporal and spatial distribution, however, a deep understanding of RATHI repeatability associated with the pulmonary function is necessary. As a consequence, in the current work intrasubject variability of RATHI is evaluated at different airflows. For generating RATHIs, LS were acquired at the posterior thoracic surface. The associated image was computed at the inspiratory phases by interpolation through a Hermite function. The acoustic information of eleven subjects was considered at airflows of 1.0, 1.5 and 2.0 L/s. Several RATHIs were generated for each subject according to the number of acquired inspiratory phases. Quadratic mutual information based on Cauchy-Schwartz inequality (I CS ) was used to evaluate the degree of similitude between intrasubject RATHIs. The results indicated that, for the same subject, I CS averaged 0.893, 0.897, and 0.902, for airflows of 1.0, 1.5, and 2 L/s, respectively. In addition, when the airflow was increased, increments in intensity values and in the dispersion of the spatial distribution reflected in RATHI were observed. In conclusion, since the intrasubject variability of RATHI was low for airflows between 1.0 and 2.0 L/s, the pattern of sound distribution during airflow variations is repeatable but differences in sound intensity should be considered.

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Base lung sound in diffuse interstitial pneumonia analyzed by linear and nonlinear techniques

Base lung sound in diffuse interstitial pneumonia analyzed b...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： L. Albuerne-Sanchez S. Charleston-Villalobos R. Gonzalez-Camarena G. Chi-Lem J.G. Carrillo T. Aljama-Corrales Master student of the Biomedical Engineering Program Universidad Autónoma Metropoiitana Mexicali Mexico Electrical Engineering Department Universidad Autónoma Metropoiitana Mexicali Mexico Health Science Department Universidad Autónoma Metropoiitana Mexicali Mexico National Institute of Respiratory Diseases Mexicali Mexico

Abnormal lung sounds in diffuse interstitial pneumonia have been characterized by the presence of crackles. However, few attempts have tried to analyze the sound where crackles are immersed. In this work base lung sounds (BLS) were analyzed by linear and nonlinear techniques to find possible differences between normal subjects and patients with diffuse interstitial pneumonia. In both groups, segments of lung sounds (crackles absent) and segments of BLS (lung sound in between crackles) were analyzed from acquired lung sounds from four points at the posterior chest, two apical and two basal. In this study, 8 healthy subjects and 8 patients participated and BLS were analyzed by spectral percentiles and sample entropy. Although spectral percentiles and sample entropy (SampEn) tended to be lower in the group of patients, statistical differences (p<0.05) between normal subjects and patients were found in BLS at the left hemithorax at basal and apical regions, while at the right hemithorax significant differences were found only at the basal region using the nonlinear technique. We conclude that in respect to normal subjects, BLS of patients with diffuse interstitial pneumonia present differences as assessed by SampEn, so that BLS by itself provides useful information. Moreover, it seems that nonlinear technique did a better discrimination of abnormal BLS than spectral percentile parameters.

关键词： Lung Diseases Sensors Entropy Urban areas Dispersion Frequency control

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FDG-PET as a pre-operative biomarker for predicting and optimizing response to subcallosal cingulate area deep brain stimulation

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Biological psychiatry 2025年

作者： Gavin J B Elias Sarah A Iskin Michelle E Beyn Uyiosa Omere Sakina J Rizvi Amanda K Ceniti Alexandre Boutet Daphne Voineskos Sidney H Kennedy Andres M Lozano Jürgen Germann Joint Department of Medical Imaging University of Toronto Toronto Canada Division of Neurosurgery Department of Surgery University of Toronto & University Hospital Network Toronto Canada. Department of Psychiatry University Health Network & University of Toronto Toronto Canada. Master of Arts Program in the Social Sciences (MAPSS) University of Chicago Chicago USA. Department of Psychiatry University Health Network & University of Toronto Toronto Canada Krembil Brain Institute Toronto Canada. Division of Neurosurgery Department of Surgery University of Toronto & University Hospital Network Toronto Canada Krembil Brain Institute Toronto Canada Center for Advancing Neurotechnological Innovation to Application (CRANIA) Toronto Canada Institute of Biomedical Engineering University of Toronto Toronto Canada. Electronic address: jurgen.germann@uhn.ca.

BACKGROUND:Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS) has emerged as a promising therapy for treatment-resistant depression (TRD). However, only half to two thirds of patients experience meaningful clinical response, highlighting the need for biomarkers that could help to optimize SCC-DBS outcomes. Our group previously showed that a support vector machine (SVM) incorporating pre-operative FDG-PET glucose metabolism values from frontal pole, anterior cingulate cortex, and temporal pole could retrospectively classify treatment response in 21 TRD patients with 81.0% accuracy. Here, we assessed the out-of-sample performance and wider applicability of this putative biomarker. METHODS:Baseline FDG-PET data were preprocessed and fed into an SVM classifier. This model, which employed the three aforementioned regional inputs, was trained and tuned using the familiar 21-patient cohort and tested on an unseen TRD validation set (n=35). Within the combined cohort, we also explored glucose metabolism's potential influence on previously demonstrated relationships between white matter tract stimulation and clinical outcome. RESULTS:Our model classified out-of-sample response status with 77.1% accuracy (80.0% precision; 87.0% recall; 0.83 F1 score).This performance proved statistically significant in permutation testing (p=0.008) and exceeded that of an alternative, clinically informed SVM. In addition, we found that patients with lower temporal pole metabolism showed stronger coupling between uncinate fasciculus engagement (approximated using electrode localization and activation modelling) and clinical outcome (p=0.027). CONCLUSIONS:These results corroborate the validity of FDG-PET models as a tool for predicting SCC-DBS outcomes and underscore their value in refining patient selection and further personalizing DBS treatment.

关键词： deep brain stimulation depression machine learning positron emission tomography prediction subcallosal cingulate

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Benefits and drawbacks of radiofrequency ablation via percutaneous or minimally invasive surgery for treating hepatocellular carcinoma

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World Journal of Gastrointestinal Surgery 2024年第11期16卷 3400-3407页

作者： Ching-Lung Hsieh Cheng-Ming Peng Chun-Wen Chen Chang-Hsien Liu Chih-Tao Teng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724Taiwan Department of Surgery Chung Shan Medical University HospitalTaichung 40201Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Department of Radiology Taichung Armed Forces General HospitalTaichung 406Taiwan Department of Medical Imaging and Radiological Sciences Central Taiwan University of Science and TechnologyTaichung 406Taiwan Department of Radiology School of MedicineNational Defense Medical CenterTaipei 11490Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital and China Medical UniversityHsinchu 302Taiwan Institute of Nuclear Engineering and Science National Tsing Hua UniversityHsinchu 300Taiwan Department of Radiology Nantou Hospital of the Ministry of Health and WelfareNantou 540Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia UniversityTaichung 407Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

The management of early stage hepatocellular carcinoma(HCC)presents significant *** radiofrequency ablation(RFA)has shown safety and effectiveness in treating HCC,with lower mortality rates and shorter hospital stays,its high recurrence rate remains a significant ***,achieving improved survival solely through RFA is challenging,particularly in retrospective studies with inherent *** is commonly used for guiding percutaneous RFA,but its low contrast can lead to missed tumors and the risk of HCC *** enhance the efficiency of ultrasound-guided percutaneous RFA,various techniques such as artificial ascites and contrast-enhanced ultrasound have been developed to facilitate complete tumor *** invasive surgery(MIS)offers advantages over open surgery and has gained traction in various surgical *** studies suggest that laparoscopic intraoperative RFA(IORFA)may be more effective than percutaneous RFA in terms of survival for HCC patients unsuitable for surgery,highlighting its ***,combining MIS-IORFA with these enhanced percutaneous RFA techniques may hold greater significance for HCC treatment using the MIS-IORFA *** article reviews liver resection and RFA in HCC treatment,comparing their merits and proposing a trajectory involving their combination in future therapy.

关键词： Percutaneous radiofrequency ablation Minimally invasive surgery Hepatocellular carcinoma Intraoperative radiofrequency ablation Contrast-enhanced ultrasound

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jen-Chien Yu Chun-Chieh Yang John Reuben Gilbert Rou-Jun Liu Yen-Jen Oyang Meng-Han Yang Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan ROC Master Program in Statistics National Taiwan University Taipei Taiwan ROC Department of Computer Science & Information Engineering National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset.

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