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arXiv 2025年

作者： Zhetpissov, Yernar Ma, Xihan Yang, Kehan Zhang, Haichong K. Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Department of Biomedical Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Conventional freehand ultrasound (US) imaging is highly dependent on the skill of the operator, often leading to inconsistent results and increased physical demand on sonographers. Robotic Ultrasound Systems (RUSS) aim to address these limitations by providing standardized and automated imaging solutions, especially in environments with limited access to skilled operators. This paper presents the development of a novel RUSS system that employs dual RGB-D depth cameras to maintain the US probe normal to the skin surface, a critical factor for optimal image quality. Our RUSS integrates RGB-D camera data with robotic control algorithms to maintain orthogonal probe alignment on uneven surfaces without preoperative data. Validation tests using a phantom model demonstrate that the system achieves robust normal positioning accuracy while delivering ultrasound images comparable to those obtained through manual scanning. ASEE2.0 demonstrates 2.47 ± 1.25 degrees error for flat surface normal-positioning and 12.19 ± 5.81 degrees normal estimation error on mannequin surface. This work highlights the potential of A-SEE2.0 to be used in clinical practice by testing its performance during in-vivo forearm ultrasound examinations. © 2025, CC BY.

关键词： Medical robotics

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Precision Control of Fingertip Force by a Biorealistic Hand with a Pair of Neuromorphic Muscles *

Precision Control of Fingertip Force by a Biorealistic Hand ...

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

作者： Anran Xie Chih-Hong Chou Zhuozhi Zhang Chen Li Ning Lan Laboratory of NeuroRehabilitation Engineering School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Laboratory of NeuroRehabilitation Engineering and Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

In this paper, the ability of precision control of fingertip forces was investigated in an antagonistic cable-driven prosthetic hand with neuromorphic twin of muscles. Surface electromyography (sEMG) signals collected from able-bodied subjects’ forearm were processed and used as alpha motor commands to drive the neuromorphic muscle models. A pair of antagonistic muscles were cascaded by two servo motors to control the index finger. Force control performance was tested by pressing a spring with a fixed stiffness using the fingertip, where forces with varying target levels were regulated with visual feedback. Two able-bodied subjects performed the precision force control task with the prosthetic index finger by sEMG signals and the intact hand. One subject was tested with force level changes of 0.1N, and another subject with force level changes of 0.2N. The ability of force regulation by the prosthetic finger was compared to that of the intact finger. Results showed that the overall root-mean-squares (RMS) error of the prosthetic finger was low, although significantly higher than the intact finger, 75% higher in subject 1 and 57% in subject 2. However, the correlation coefficient between the forces of prosthetic finger and intact finger was high, 75% for subject 1 and 84% for subject 2, respectively. This preliminary study is encouraging, illustrating the feasibility of accurate and stable control of different levels of fingertip forces by the prosthetic finger, which is comparable to that of the intact finger. This capability may allow the prosthetic hand for fine manipulation tasks, such as grasping brittle objects, or response to object slip during *** Relevance—This work attempts to restore the ability of a prosthetic hand for precision fingertip force control that may enrich the functionality for users in activities of daily living.

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Rationale of the design of antenna systems for the control of insect pests of agricultural crops 5

Rationale of the design of antenna systems for the control o...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Kosulina, Natalia Korshunov, Kostiantyn Kosulin, Stanislav Kuskova, Svitlana Chorna, Mariia Sukhin, Vitaly Department of Electromechanics Robotics Biomedical and Electrical Engineering State Biotechnological University Kharkiv Ukraine Department of Oncology Radiotherapy Oncosurgery and Palliative Care Kharkiv National Medical University Kharkiv Ukraine Department of Management Business and Administration State Biotechnological University Kharkiv Ukraine

ISBN: (纸本)9798350384499

The paper discusses the calculation of the parameters of an antenna system for controlling plant pests, namely: determining the electric field strength of the E-sectorial horn in the near zone, determining the electric field strength of the E-sectorial horn in the far zone, calculating the geometric dimensions of the lens. The dependence of the integration limit parameter on the height of the plant bush is given for three values: 20 mm, 30 mm, 40 mm aperture E-sectorial horn, radiation pattern of the E-sectorial horn in the xoz plane at a distance 1200 mm from the radiating aperture, radiation pattern of the E-sectorial horn in the yüz plane for different aperture sizes and horn lengths. ©2024 IEEE.

关键词： Horn antennas

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Intelligent upper-limb exoskeleton integrated with soft bioelectronics and deep learning for intention-driven augmentation

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npj Flexible Electronics 2024年第1期8卷 856-868页

作者： Jinwoo Lee Kangkyu Kwon Ira Soltis Jared Matthews Yoon Jae Lee Hojoong Kim Lissette Romero Nathan Zavanelli Youngjin Kwon Shinjae Kwon Jimin Lee Yewon Na Sung Hoon Lee Ki Jun Yu Minoru Shinohara Frank L.Hammond Woon-Hong Yeo Department of Mechanical Roboticsand Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea IEN Center for Wearable Intelligent Systems and Healthcare Institute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30332USA George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA School of Industrial Design Georgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering Yonsei UniversitySeoul 03722Republic of Korea School of Biological Sciences Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Materials Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for Robotics and Intelligent MachinesGeorgia Institute of TechnologyAtlantaGA 30332USA

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper ***,we introduce an intelligent upper-limb exoskeleton system that utilizes deep learning to predict human intention for strength *** embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities,which are simultaneously computed to determine the user’s intended *** deep learning predicts four upper-limb joint motions with an average accuracy of 96.2%at a 500–550 ms response rate,suggesting that the exoskeleton operates just by human *** addition,an array of soft pneumatics assists the intended movements by providing 897 newtons of force while generating a displacement of 87mm at *** intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.

关键词： skeleton learning utilize

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Nonlinearity of optoacoustic signals and a new contrast mechanism for imaging

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光：科学与应用（英文版） 2025年第5期14卷 1420-1432页

作者： Jaber Malekzadeh-Najafabadi Jaya Prakash Daniel Razansky Jorge Ripoll Vipul Gujrati Vasilis Ntziachristos Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Institute for Biomedical Engineering Department of Information Technology and Electrical EngineeringETH ZurichZurichSwitzerland Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Department of Instrumentation and Applied Physics Indian Institute of ScienceBengaluruIndia Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology Faculty of MedicineUniversity of ZurichZurichSwitzerland Institute for Biomedical Engineering Department of Information Technology and Electrical EngineeringETH ZurichZurichSwitzerland Department of Bioengineering and Aerospace Engineering Universidad Carlos Ⅲ de MadridMadridSpain Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Biological Imaging Central Institute for Translational Cancer Research(TranslaTUM)School of Medicine and Health & School of ComputationInformation and TechnologyTechnical University of MunichMunichGermany Institute of Biological and Medical Imaging Bioengineering CenterHelmholtz Zentrum MünchenNeuherbergGermany Munich Institute of Robotics and Machine Intelligence(MIRMI) Technical University of MunichMunichGermany

Optoacoustic signals behave nonlinearly at light fluences above a few mJ/cm2,which may affect the interpretation and quantification of *** has been proposed that optoacoustic nonlinearity arises from the heat-induced formation of nanobubbles or changes in local thermo-physical ***,such explanations are only valid at much higher fluences than typically used in biomedical optoacoustic imaging(＞20 mJ/cm2)or in the presence of materials with high absorption coefficients such as gold *** propose herein that electromagnetic permittivity changes in response to photon absorption are major source of optoacoustic signal nonlinearity at low *** provide theoretical and experimental evidence that supports this postulation and show that optoacoustic pressure responses due to permittivity changes,which are function of thermally excited third-order nonlinear susceptibility,can explain the nonlinear behavior of the optoacoustic *** different materials exhibit different thermally excited third-order nonlinear susceptibility,this property could function as a new contrast mechanism that can identify the sensitivity of a substance's dielectric constant to photon-induced temperature ***,we propose an imaging method based on nonlinear optoacoustic signals that exploits this newly identified contrast *** findings may have far-reaching implications for improving the accuracy of optoacoustics and utilizing the proposed new contrast mechanism would advance our understanding of cellular and tissue functionality.

关键词： mechanism contrast imaging nonlinearity optoacoustic signals

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Multistep Modelling and Monitoring of Bioprocesses

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International Journal Bioautomation 2024年第4期28卷 185-196页

作者： Lyubenova, Velislava Ignatova, Maya Kristeva, Denitsa Roeva, Olympia Department of Mechatronic Bio Technological Systems Institute of Robotics Bulgarian Academy of Science Acad. G. Bonchev Str. Bl. 2 Sofia1113 Bulgaria Department of Bioinformatics and Mathematical Modelling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Acad. G. Bonchev Str. Bl. 105 Sofia1113 Bulgaria

A new approach is proposed for modelling and monitoring bioprocesses dynamics characterized by different metabolic states. Bioprocesses cannot be described by a single model. For this reason, three phases characterised by the bioprocess are defined – periodic, exponential, and stationary. During each phase, the process passes through one or more physiological states. Each physiological state is described by a sub-model with a different structure and parameter values. The transition of the process from one physiological state to another is carried out by switching the sub-models based on a predefined key parameter. Monitoring is performed by a cascade of software sensors using the sub-models and real-time measurement of the concentrations of the main process variables. The proposed approach was tested by modelling and monitoring the Escherichia coli phytase production process. © 2024 by the authors.

关键词： Escherichia coli

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Analysis of Visual Expression of Light and Color in Movies based on Wavelet Neural Network 2

Analysis of Visual Expression of Light and Color in Movies b...

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2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Murugan, K. Mothi, R. George, Retty Priya, R. Esther Nagarathinam, S. Krishnakumar, S. Kpr Institute of Engineering and Technology Department of Electronics and Communication and Engineering Coimbatore India Dr. N.G.P. Institute of Technology Department of Biomedical Engineering Coimbatore India Scms School of Engineering and Technology Department of Ece Kerala Ernakulam India Jansons Institute of Technology Department of Artificial Intelligence and Data Science Coimbatore India Kumaraguru College of Technology Department of Ece Coimbatore India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India

ISBN: (纸本)9798350369960

Movies are in the era of 'black, white and gray' ruling the screen, people have a strong desire for movies to truly reproduce colors, because the main rhythm of the 'black, white and gray' film visual music is not clear enough, the momentum is not strong enough, the meaning is not rich enough, and the color is not enough. Visual aesthetics cannot be attractive... Aiming at the dual challenges of colorization quality and timing stability in film colorization, a generative adversarial network with a recurrent structure is proposed, which can be used for automatic colorization of films without any reference frames and artificial intervention. The network generates a confrontation network based on classical conditions: the generator is used to generate color images and complete the task of colorization;The discriminator is used to identify the authenticity and improve the performance of the generator. Cycle structure and timing consistency loss are introduced to integrate timing information and solve the stability problem of coloring. Experimental results show that this method can effectively reduce flicker in the generated movie sequence while ensuring the coloring of a single frame image. This paper studies and analyzes the visual expression of light and color in movies based on wavelet neural network. © 2023 IEEE.

关键词： Color vision film Neural network

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HITTING THE GYM: REINFORCEMENT LEARNING CONTROL OF EXERCISE-STRENGTHENED BIOHYBRID ROBOTS IN SIMULATION

arXiv

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arXiv 2024年

作者： Schaffer, Saul Pamu, Hima Hrithik Webster-Wood, Victoria A. Mechanical Engineering Department Carnegie Mellon University United States Mechanical Engineering Department Biomedical Engineering Department McGowan Institute for Regenerative Medicine Robotics Institute Carnegie Mellon University United States

Animals can accomplish many incredible behavioral feats across a wide range of operational environments and scales that current robots struggle to match. One explanation for this performance gap is the extraordinary properties of the biological materials that comprise animals, such as muscle tissue. Using living muscle tissue as an actuator can endow robotic systems with highly desirable properties such as self-healing, compliance, and biocompatibility. Unlike traditional soft robotic actuators, living muscle biohybrid actuators exhibit unique adaptability, growing stronger with use. The dependency of a muscle’s force output on its use history endows muscular organisms the ability to dynamically adapt to their environment, getting better at tasks over time. While muscle adaptability is a benefit to muscular organisms, it currently presents a challenge for biohybrid researchers: how does one design and control a robot whose actuators’ force output changes over time? Here, we incorporate muscle adaptability into a many-muscle biohybrid robot design and modeling tool, leveraging reinforcement learning as both a co-design partner and system controller. As a controller, our learning agents coordinated the independent contraction of 42 muscles distributed on a lattice worm structure to successfully steer it towards eight distinct targets while incorporating muscle adaptability. As a co-design tool, our agents enable users to identify which muscles are important to accomplishing a given task. Our results show that adaptive agents outperform non-adaptive agents in terms of maximum rewards and training time. Together, these contributions can both enable the elucidation of muscle actuator adaptation and inform the design and modeling of adaptive, performant, many-muscle robots. © 2024, CC BY.

关键词： Biocompatibility

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MR Elastography with Optimization-Based Phase Unwrapping and Traveling Wave Expansion-Based Neural Network (TWENN)

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IEEE Transactions on Medical Imaging 2023年第9期42卷 2631-2642页

作者： Ma, Shengyuan Wang, Runke Qiu, Suhao Li, Ruokun Yue, Qi Sun, Qingfang Chen, Liang Yan, Fuhua Yang, Guang-Zhong Feng, Yuan Shanghai Jiao Tong University School of Biomedical Engineering Institute of Medical Robotics The Natl. Eng. Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy Shanghai200030 China Shanghai Jiao Tong University Ruijin Hospital School of Medicine Department of Radiology Shanghai200025 China Fudan University Huashan Hospital Department of Neurosurgery Shanghai200040 China Shanghai Jiao Tong University Ruijin Hospital School of Medicine Department of Neurosurgery Shanghai200020 China Shanghai Jiao Tong University Institute of Medical Robotics The School of Biomedical Engineering The Natl. Eng. Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy Shanghai200240 China

Magnetic Resonance Elastography (MRE) can characterize biomechanical properties of soft tissue for disease diagnosis and treatment planning. However, complicated wavefields acquired from MRE coupled with noise pose challenges for accurate displacement extraction and modulus estimation. Using optimization-based displacement extraction and Traveling Wave Expansion-based Neural Network (TWENN) modulus estimation, we propose a new pipeline for processing MRE images. An objective function with Dual Data Consistency (Dual-DC) has been used to ensure accurate phase unwrapping and displacement extraction. For the estimation of complex wavenumbers, a complex-valued neural network with displacement covariance as an input has been developed. A model of traveling wave expansion is used to generate training datasets for the network with varying levels of noise. The complex shear modulus map is obtained through fusion of multifrequency and multidirectional data. Validation using brain and liver simulation images demonstrates the practical value of the proposed pipeline, which can estimate the biomechanical properties with minimal root-mean-square errors when compared to state-of-the-art methods. Applications of the proposed method for processing MRE images of phantom, brain, and liver reveal clear anatomical features, robustness to noise, and good generalizability of the pipeline. © 1982-2012 IEEE.

关键词： Data mining

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A Pipeline for Population and Analysis of Personal Health Knowledge Graphs (PHKGs) 18

A Pipeline for Population and Analysis of Personal Health Kn...

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18th International Conference on Semantic Systems, SEMPDW 2022

作者： Bosanska, Dagmar Celuchova Huptych, Michal Lhotská, Lenka Faculty of Biomedical Engineering Czech Technical University Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic

Personal Health Knowledge Graphs (PHKGs) are not yet ubiquitous, even though they have a great potential to enrich general knowledge captured in various Knowledge Graphs by adding personal contexts. This poster paper presents work in progress about a pipeline for generating PHKGs from tree-structured Electronic Health Record (EHR) data by applying a hierarchical ontological approach. This pipeline could also be applied to other domains of Personal Knowledge Graphs. Moreover, this pipeline targets the intersection between the symbolic representation of knowledge used for computational semantics and numeric graph data representation used for graph analysis and machine learning. We present the first results from applying this pipeline to synthetic patient EHRs with the diagnosis of colorectal cancer (based on Synthea). The resulting numeric representation of PHKGs or their subgraphs can be used in many practical graph algorithms. Finally, our pipeline study uncovers future research on how this numeric representation of PHKGs should be embedded into continuous and low-dimensional vector space to utilize graph machine learning and deep learning methods. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Ontology

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