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16th IEEE International Conference on Nano/Molecular Medicine and engineering, NANOMED 2023

作者： Zou, Xiaoyang Li, Xiaoting Xue, Jiaqi Chan, Colin Pak Yu Li, Ziqi Zhang, Jing Lai, King Wai Chiu City University of Hong Kong Centre for Robotics and Automation Department of Biomedical Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350343700

The knee joint is one of the most important joints in our lower body, affecting humans' lower limb activities. For instance, the knee joint can even bear three to four times the human body's weight when running and climbing. The knee joint is prone to degenerative lesions for older people as they age, which significantly affects their daily lives. Therefore, long-term and real-time assessment of lower-limb motions in older people is crucial for their lower-limb health detection. In this work, we developed wearable knee sensors based on nanocomposite e-textile strain sensors for detecting knee joints' range of motion (ROM) while older people perform lower-limb activities. A total of ten features were extracted to characterize their STS performance by detecting their knee joint range of motion through normal speed and fast speed sit-to-stand (STS). The elderly subjects were grouped by their age, gender, and body mass index (BMI) to assess the relationship of these three parameters with the extracted features. As a result, the stability, ROM, and gender of elderly subjects while performing fast speed STS had a significant relationship with age and BMI (P © 2023 IEEE.

关键词： Nanocomposites

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Human Fall Detection Using Machine Learning and Deep Learning Techniques: A Survey 4

Human Fall Detection Using Machine Learning and Deep Learnin...

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4th International Conference on Signal Processing and Communication, ICSPC 2023

作者： Sherin Zebiah, S. Shalomy, Ancy Vetha Kachhap, Jyotsana Tete, Nikita Nancy, R. Ananthi, A. Prasanna, J. Subathra, M.S.P. George, S.Thomas Robotics and Automation Karunya Institute of Technology and Sciences Coimbatore India Karunya Institute of Technology and Sciences Department of Robotics Engineering Coimbatore India Karunya Institute of Technology and Sciences Department of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350300772

Wearable airbag systems manifest an important role in the senior population, where falls have become a serious health problem. As a result, these devices are increasingly being utilized by elderly people in order to safeguard them from falling, particularly those with chronic diseases. This paper reviews about the previous research on human fall detection systems based on Machine Learning (ML) and Deep Learning (DL) techniques using different sensors that are employed in the various positions of the body. Apart from ML and DL techniques, few researchers analyzed other techniques and micro mechanical devices are designed for the prevention and detection of falls as mentioned in this research paper. © 2023 IEEE.

关键词： Fall detection

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Design and Validation of a Prosthetic Foot Adaptable to Sagittal Plane Ground Irregularity

Design and Validation of a Prosthetic Foot Adaptable to Sagi...

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2024 International Symposium on 3D Analysis of Human Movement, 3DAHM 2024

作者： Lagones, Marco Abarca, Victoria E. Elias, Dante A. Biomedical Engineering Program Pontificia Universidad Católica del Perú Biomedical Engineering Program Universidad Peruana Cayetano Heredia Lima Peru Pontificia Universidad Católica del Perú Biomechanics and Applied Robotics Research Laboratory Lima Peru

ISBN: (纸本)9798331521738

Amputation involves the removal of a limb or part of it. In the case of the lower extremity, amputation affects the ankle joint and the metatarsophalangeal and intertarsal joints, improving the foot's adaptability on uneven terrain. Therefore, based on state-of-the-art technology that does not address the other joints of the foot to a large extent, a prosthetic foot has been developed that integrates the support structure of the foot through a foot arch with an extension analogous to the forefoot and an elastic element that mimics the plantar fascia that deforms against obstacles and provides stability to the prosthetic arch foot. The work addresses the design of the prosthetic foot from its design to its prototyping and validation, where the foot was shown to withstand the loads recommended for the P5 category of the ISO 22675 standard and to provide a return energy equal to 95.72%, 77.13%, and 90.21 %, in the heel strike, mid-stance, and toe-off stages, respectively. In addition to showing linear stiffness properties (66.95 kN /m) and torsional stiffness properties(2.05 kN.m/rad) in the forefoot analog element, values that are comparable with those recorded in commercial tests such as LP Variflex categories 7 and 8. © 2024 IEEE.

关键词： Arches

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loT based Patient Monitoring System towards Improving quality of life for Patients with Mild Respiratory Failure

loT based Patient Monitoring System towards Improving qualit...

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International Conference on Computer Vision and Internet of Things 2023, ICCVIoT 2023

作者： Vijai, S. Jayakumar, J. Jose, P. Subha Hency Sekaran, K. Raja Raj, P. Anantha Christu Division of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Electrical and Electronics Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Biomedical Engineering Karunya Institute of Technology and science Coimbatore India Department of Biomedical Engineering KPR Institute of Engineering and Technology Coimbatore India Division of Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9781839539848

Internet of things (loT) it is a network of several devices recognizable items are linked to the web and mobile app. Patient Monitoring devices accumulate healthcare information such as Body parameters Heart rate (BPM), Oxygen saturation level(SpO2). Healthcare providers receive data from Patients through loT devices. There need patient health monitoring regularly and collecting data will need a stay at home. Patients are spending less time in hospitals because to remote patient monitoring. Healthcare prices have decreased as treatment quality has increased. Using information from of the loT-enabled devices, patients and healthcare professionals can see patient data that is collected by an loT device and delivered to a software program. The data may be analyzed and therapy recommendations are made using algorithms. Any abnormality in a person's everyday activities will trigger an alarm mechanism that will notify care takers and medical professional. The sensor data is delivered to cloud through a ESP 8266 WiFi module and Arduino uno board that allows the health care system to operate efficiently. © The Institution of engineering & Technology 2023.

关键词： Patient treatment

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Uncover rock-climbing fish's secret of balancing tight adhesion and fast sliding for bioinspired robots

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National Science Review 2023年第8期10卷 222-231页

作者： Wenjun Tan Chuang Zhang Ruiqian Wang Yuanyuan Fu Qin Chen Yongliang Yang Wenxue Wang Mingjun Zhang Ning Xi Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Histology and Embryology Basic Medical CollegeChina Medical University Chengdu Institute of Biology Chinese Academy of Sciences Department of Biomedical Engineering School of Medicine Tsinghua University Emerging Technologies Institute Department of Industrial and Manufacturing Systems EngineeringUniversity of Hong Kong

The underlying principle of the unique dynamic adaptive adhesion capability of a rock-climbing fish（Beaufortia kweichowensis） that can resist a pull-off force of 1000 times its weight while achieving simultaneous fast sliding(7.83 body lengths per second（BL/S）) remains a mystery in the literature. This adhesion-sliding ability has long been sought for underwater robots. However, strong surface adhesion and fast sliding appear to contradict each other due to the need for high surface contact stress. The skillfully balanced mechanism of the tight surface adhesion and fast sliding of the rock-climbing fish is disclosed in this work. The Stefan force（0.1 mN/mm2） generated by micro-setae on pectoral fins and ventral fins leads to a 70 N/m2adhesion force by conforming the overall body of the fish to a surface to form a sealing chamber. The pull-off force is neutralized simultaneously due to the negative pressure caused by the volumetric change of the chamber. The rock-climbing fish's micro-setae hydrodynamic interaction and sealing suction cup work cohesively to contribute to low friction and high pull-off-force resistance and can therefore slide rapidly while clinging to the surface. Inspired by this unique mechanism, an underwater robot is developed with incorporated structures that mimic the functionality of the rock-climbing fish via a micro-setae array attached to a soft self-adaptive chamber, a setup which demonstrates superiority over conventional structures in terms of balancing tight underwater adhesion and fast sliding.

关键词： bioinspired underwater adhesion crawling robots rock-climbing fish Stefan adhesion underwater robots

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Empowering Dysarthric Communication: Hybrid Transformer-Ctc Based Speech Recognition System

SSRN

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SSRN 2023年

作者： Vinotha, R. Hepsiba, D. Vijay Anand, L.D. Department of Robotics Engineering Department of Biomedical Engineering

People suffering from speech disorders face various challenges in their ability to communicate effectively, and one of the conditions they may experience is dysarthria. Dysarthria is a motor speech disorder that impacts an individual's ability to speak due to difficulties in controlling the muscles responsible for speech production. People with dysarthria may experience difficulties with articulation, pronunciation, intonation, rhythm, and pace, resulting in a slow or slurred speech pattern that can be difficult to understand. Augmentative and Alternative Communication (AAC) aids that utilize speech recognition technology have emerged as an appealing solution to support communication for individuals with dysarthria. Automatic Speech Recognition (ASR) systems trained solely on normal speech data may not accurately recognize dysarthric speech due to variations in their speech patterns and accent differences. However, a significant challenge in training ASR systems for dysarthric speech is the limited availability of data. To overcome these challenges, a hybrid architecture using the Transformer and Connectionist Temporal Classification (CTC) approach is proposed in this work. The transformer architecture is effective in learning speech patterns using limited data due to its self-attention mechanism, while the CTC approach allows for direct mapping between input speech features and output character sequences without requiring explicit alignment information. This approach is especially beneficial for speech recognition in situations involving variations in speech patterns. A hybrid architecture is trained using UA speech corpus that allows it to focus on important features of the speech and capture the relationships between them, leading to more accurate speech recognition. The performance of the proposed ASR system shows a remarkable decrease in Word Error Rate (WER) up to 2.78% and 15.67% for individuals with dysarthria who have low and very low intelligibility, respe

关键词： Speech recognition

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Weakly-and Semisupervised Probabilistic Segmentation and Quantification of Reverberation Artifacts

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biomedical engineering Frontiers 2022年第1期3卷 67-81页

作者： Alex Ling Yu Hung Edward Chen John Galeotti Department of Biomedical Engineering Carnegie Mellon UniversityPittsburghPAUSA Robotics Institute Carnegie Mellon UniversityPittsburghPAUSA

Objective and Impact *** propose a weakly-and semisupervised,probabilistic needle-and-reverberation-artifact segmentation algorithm to separate the desired tissue-based pixel values from the superimposed *** method models the intensity decay of artifact intensities and is designed to minimize the human labeling *** image quality has continually been ***,when needles or other metallic objects are operating inside the tissue,the resulting reverberation artifacts can severely corrupt the surrounding image *** effects are challenging for existing computer vision algorithms for medical image *** reverberation artifacts can be hard to identify at times and affect various pixel values to different *** boundaries of such artifacts are ambiguous,leading to disagreement among human experts labeling the *** learning-based framework consists of three *** first part is a probabilistic segmentation network to generate the soft labels based on the human *** soft labels are input into the second part which is the transform function,where the training labels for the third part are *** third part outputs the final masks which quantifies the reverberation *** demonstrate the applicability of the approach and compare it against other segmentation *** method is capable of both differentiating between the reverberations from artifact-free patches and modeling the intensity fall-off in the *** method matches state-of-the-art artifact segmentation performance and sets a new standard in estimating the per-pixel contributions of artifact vs underlying anatomy,especially in the immediately adjacent regions between reverberation *** algorithm is also able to improve the performance of downstream image analysis algorithms.

关键词： image probabilistic anatomy

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GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration

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IEEE Transactions on Medical Imaging 2025年第6期44卷 2617-2630页

作者： Yankai Chen Guanyu Li Chunming Li Wei Yu Zehao Fan Jingfeng Bai Shengxian Tu Department of Biomedical Engineering and the Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

The registration of coronary artery structures from preoperative coronary computed tomography angiography to intraoperative coronary angiography is of great interest to improve guidance in percutaneous coronary interventions. However, non-rigid deformation and discrepancies in both dimensions and topology between the two imaging modalities present a challenge in the 2D/3D coronary artery registration. In this study, we address this problem by formulating it as a centerline feature matching task and propose a GNN-based vessel matching network (GVM-Net) to establish dense correspondence between different image modalities in an end-to-end manner. GVM-Net considers centerline points as nodes in graphs and effectively models the complex topological relationships between them through attention mechanisms and message passing. Furthermore, by incorporating redundant rows and columns into the matching matrix, GVM-Net can effectively handle inconsistencies in vascular structures. We also introduce the query-based nodes grouping module, which clusters nodes in the feature space to further explore the topological relationships. GVM-Net achieves an average F1-score of 89.74% with a mean pixel distance of 0.48 pixels on the synthetic dataset with 276 data pairs and an average F1-score of 83.35% with a mean error of 1.52 mm in 55 manually labeled clinical cases, both exceeding existing feature matching methods.

关键词： Arteries Three-dimensional displays Feature extraction Iterative methods Deformation Training Accuracy Topology Light sources Image segmentation

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WEARABLE ULTRASOUND DEVICE FOR MONITORING BLOOD FLOW IN INTERNAL CAROTID ARTERY

WEARABLE ULTRASOUND DEVICE FOR MONITORING BLOOD FLOW IN INTE...

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2024 Design of Medical Devices Conference, DMD 2024

作者： Hage, Benjamin D. Krings, Ethan J. Walker, Quentin Markvicka, Eric J. Bashford, Gregory R. Biomedical Imaging and Biosignal Analysis Laboratory Department of Biological Systems Engineering University of Nebraska-Lincoln LincolnNE United States Smart Materials and Robotics Laboratory Department of Mechanical & Materials Engineering University of Nebraska-Lincoln LincolnNE United States Department of Biomedical Engineering The Ohio State University ColumbusOH United States

ISBN: (纸本)9780791887752

Aneurysmal subarachnoid hemorrhage affects 6.1/100, 000 people annually worldwide. After initial bleeding has stopped, victims are at high risk of vasospasm, a narrowing of cerebral arteries that may lead to stroke, for two weeks. One currently used method of monitoring for vasospasm involves calculation of the Lindegaard ratio, a ratio of blood flow velocity in the middle cerebral artery to the ipsilateral internal carotid artery. However, this method requires trained operators, limiting the frequency at which it is performed (no more than once per day). This work demonstrates a proof-of-concept device for frequent Lindegaard ratio calculation via periodic monitoring of blood flow in the internal carotid artery. © 2024 by ASME.

关键词： Ultrasonic devices

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Early Detection and Treatment of Skin Diseases Using Advanced Image Preprocessing and Machine Learning Techniques 4

Early Detection and Treatment of Skin Diseases Using Advance...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Pandian, Jeswin Paul Jegan, R. Jerlinkasmir, R. Jose, P. Subha Hency Raj, P. Anantha Christu Karunya Institute of Technology and Science Division of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Science Department of Mathematics Coimbatore India Karunya Institute of Technology and Science Division of Robotics and Automation Engineering Coimbatore India

ISBN: (纸本)9798331529635

This research aims to develop a more accurate and efficient system for classifying skin diseases, including both malignant and non-cancerous conditions. The study utilizes a comprehensive dataset encompassing various skin diseases, including melanomas, basal cell carcinomas, and benign conditions like nevi and warts. To address the challenge of class imbalance with a higher number of melanoma images, the researchers employ techniques like SMOTE (Synthetic Minority Oversampling Technique) to create synthetic data for under-represented classes. The pre-processing stage involves crucial steps like image scaling, augmentation, normalization, and data cleaning to ensure the quality and consistency of the data. Following pre-processing, feature extraction and model training will be conducted. This research has the potential to significantly contribute to the field of dermatology by enabling faster and more precise diagnosis of skin diseases through the use of advanced pre-processing techniques and a diversified dataset. © 2024 IEEE.

关键词： Lung cancer

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