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arXiv 2023年

作者： Sivaraman, Dileep Pillai, Branesh M. Suthakorn, Jackrit Ongwattanakul, Songpol Center for Biomedical and Robotics Technology BART LAB Faculty of Engineering Mahidol University Phutthamonthon District Nakhon Pathom73170 Thailand

A modified Lagrange Polynomial is introduced for polynomial extrapolation, which can be used to estimate the equally spaced values of a polynomial function. As an example of its application, this article presents a prime-generating algorithm based on a 1-degree polynomial that can generate prime numbers from consecutive primes. The algorithm is based on the condition that infinitely many prime numbers exist that satisfy the equation Πn = 2Πn−1 − Πn−2 ± 2 ∀ Πn > 7. where Πn−1 and Πn−2 are the consecutive primes. Copyright © 2023, The Authors. All rights reserved.

关键词： Polynomials

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Feasibility of Pointcloud-based Ultrasound-CT Registration towards Automated, Robot-Assisted Image-Guidance in Spine Surgery*

Feasibility of Pointcloud-based Ultrasound-CT Registration t...

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International Symposium on Medical robotics (ISMR)

作者： Xihan Ma Xiao Zhang Yang Wang Christopher Nycz Arno Sungarian Songbai Ji Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA University of Massachusetts Memorial Medical Center Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering and the Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350377118

ISBN: (纸本)9798350377125

Image-guidance has been shown to improve spine surgical accuracy and patient outcome. Such image guidance can be achieved by registering low-cost, realtime, and radiation-free intraoperative ultrasound (US) with preoperative computed tomography (CT). Employing robotic US system (RUSS) allows automated acquisition of a wide 3D volume, facilitating efficient and accurate registration with CT. However, the registration between CT and robotic 3D US remains an open problem mainly due to (i) the lack of relevant testbed and dataset, and (ii) the modality discrepancy between CT and US. To address these challenges, we present a custom-built lumbar spine phantom for multimodal imaging with rigidly attached fiducials. The phantom is scanned by CT and in-house RUSS. A novel pointcloud-based registration pipeline is presented to register CT and robotic 3D US data of the spine phantom. Preliminary experiments demonstrate efficient (0.53 ± 0.02 seconds) registration of the lumbar spine with an accuracy of 3.57 mm in terms of fiducial registration error (FRE), which is robust to varying initial alignment of the pointclouds. These results show initial feasibility of adopting the proposed registration pipeline in robotic US guided spine surgery. Future work includes further evaluation of registration performance in ex vivo spine samples with denser US acquisitions to further improve registration accuracy.

关键词： Accuracy Three-dimensional displays Ultrasonic imaging Medical robotics Computed tomography Spine Pipelines

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M-fiducial phantom based fast automatic ultrasound calibration technique: A novel approach for 2D to 3D image registration

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Heliyon 2024年第22期10卷 e40290页

作者： Suthakorn, Jackrit Chatrasingh, Maria Wiratkapun, Cholatip Ongwattanakul, Songpol Department of Biomedical Engineering Center for Biomedical and Robotics Technology (BART LAB) Faculty of Engineering Mahidol University Salaya Thailand Department of Radiology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand

This study introduces a novel M-fiducial phantom-based automatic ultrasound (US) calibration technique aimed at improving 2D to 3D image registration in ultrasound-guided procedures. The technique addresses limitations in existing methods by enhancing feature extraction capabilities and improving calibration accuracy. The proposed method utilizes an M-fiducial phantom, an extended version of the standard N-fiducial phantom, designed to facilitate automatic extraction with a linear probe, particularly in small field-of-view scenarios. A closed-form solution incorporating anisotropic scaling enables rapid and precise computation of transformation matrices for ultrasound calibration, and the method was tested across varying ultrasound depths to evaluate performance in point localization, length measurement, and volume estimation. Results show that the automatic extraction method, combined with the anisotropic closed-form solution, offers greater accuracy and reliability compared to manual methods. While in-plane measurements demonstrated high accuracy, out-plane estimations revealed potential limitations, especially with wire phantoms at increased depths. Despite these challenges, the M-fiducial phantom-based technique reduces operator workload and enhances ultrasound calibration precision, making it a promising approach for high-precision ultrasound-guided interventions. Future work should focus on refining the technique and validating its efficacy in clinical applications. © 2024 The Authors

关键词： 3D registration M-Fiducial phantom Non-uniform scaling Point set registration Ultrasound calibration Ultrasound images

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An improved CNN-LSTM deep model for Classification of guideRNA in CRISPR-Casl2 System 2

An improved CNN-LSTM deep model for Classification of guideR...

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2nd IEEE International Conference on Artificial Intelligence in Everything, AIE 2022

作者： Ameen, Zubaida Said Ibrahim, Abdullahi Umar Mubarak, Auwalu Saleh Al-Turjman, Fadi Near East University Research Genter for Ai and IoT Ai and Robotics Institute Artificial Intelligence Dept. Turkey Near East University Biomedical Engineering Nicosia Turkey Ai and Robotics Institute NearEast University Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Gene editing with CRISPR-Cas12 method has immense applications in diverse organisms from bacteria, and plants to humans especially in treating genetic diseases. GuideRNA and Cas enzyme are the two components required by the Cas12 gene editing method. However, the CRISPR-Cas12 system varies depending on the guideRNA sequence used. Therefore, it is important to develop improved methods for designing guideRNA sequences needed for gene editing. Here, we utilized a combination of convolutional neural networks and long short-term memory a type of recurrent neural network (bi-LSTM) model to classify guideRNA as either active or inactive, and the addition of an embedding layer for encoding guideRNA sequence improved model performance. Accuracy, AUC and F1-score were used to evaluate CNN-LSTM and achieved outstanding performance. CNN-LSTM will help in the design of guideRNA for genes with CRISPR-Cas12 system. © 2022 IEEE.

关键词： Embeddings

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Haptic Transparency and Interaction Force Control for a Lower-Limb Exoskeleton

arXiv

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arXiv 2023年

作者： Küçüktabak, Emek Barış Wen, Yue Kim, Sangjoon J. Short, Matthew R. Ludvig, Daniel Hargrove, Levi Perreault, Eric J. Lynch, Kevin M. Pons, Jose L. The Center for Robotics and Biosystems Department of Mechanical Engineering Northwestern University EvanstonIL United States Shirley Ryan AbilityLab ChicagoIL United States The Shirley Ryan AbilityLab Department of Physical Medicine and Rehabilitation Northwestern University ChicagoIL United States The Shirley Ryan AbilityLab Department of Biomedical Engineering Northwestern University EvanstonIL United States The Department of Biomedical Engineering Northwestern University United States The Shirley Ryan AbilityLab Center for Robotics and Biosystems Department of Physical Medicine and Rehabilitation Northwestern University United States The Department of Physical Medicine and Rehabilitation Department of Biomedical Engineering Shirley Ryan AbilityLab Center for Robotics and Biosystems United States Center for Robotics and Biosystems Department of Mechanical Engineering Northwestern University United States The Shirley Ryan AbilityLab Center for Robotics and Biosystems Department of Mechanical Engineering Department of Biomedical Engineering Department of Physical Medicine and Rehabilitation Northwestern University United States

Controlling the interaction forces between a human and an exoskeleton is crucial for providing transparency or adjusting assistance or resistance levels. However, it is an open problem to control the interaction forces of lower-limb exoskeletons designed for unrestricted overground walking. For these types of exoskeletons, it is challenging to implement force/torque sensors at every contact between the user and the exoskeleton for direct force measurement. Moreover, it is important to compensate for the exoskeleton's whole-body gravitational and dynamical forces, especially for heavy lower-limb exoskeletons. Previous works either simplified the dynamic model by treating the legs as independent double pendulums, or they did not close the loop with interaction force feedback. The proposed whole-exoskeleton closed-loop compensation (WECC) method calculates the interaction torques during the complete gait cycle by using whole-body dynamics and joint torque measurements on a hip-knee exoskeleton. Furthermore, it uses a constrained optimization scheme to track desired interaction torques in a closed loop while considering physical and safety constraints. We evaluated the haptic transparency and dynamic interaction torque tracking of WECC control on three subjects. We also compared the performance of WECC with a controller based on a simplified dynamic model and a passive version of the exoskeleton. The WECC controller results in a consistently low absolute interaction torque error during the whole gait cycle for both zero and nonzero desired interaction torques. In contrast, the simplified controller yields poor performance in tracking desired interaction torques during the stance phase. © 2023, CC BY.

关键词： Force control

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Hybrid Image-Based Motion Tracking and Adaptive Polynomial Kalman Filter for a Bio-Inspired Dual-Sheath Needle System

Hybrid Image-Based Motion Tracking and Adaptive Polynomial K...

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IEEE International Conference on robotics and Biomimetics

作者： Dileep Sivaraman Cholatip Wiratkapun Branesh M. Pillai Jackrit Suthakorn Boriphat Methachan Sakol Nakdhamabhorn Songpol Ongwattanakul Department of Biomedical Engineering Center for Biomedical and Robotics Technology (BART LAB) Faculty of Engineering Mahidol University Thailand Department of Radiology Breast Diagnostic Center Division of Diagnostic Radiology Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Functional Materials for Novel Engineering Applications National Science and Technology Development Agency Thailand

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

This preliminary study investigated sensor-fusion methods for accurate motion estimation in a bio-inspired dual-sheath needle system designed for biopsy applications. The needle system draws inspiration from the segmented dual-sheath mechanism of ovipositors found in Hymenoptera species, which allows controlled and precise movement. The aim is to develop a reliable tracking system for both the needle tip and base, which is essential for accurate needle placement during biopsy procedures. A hybrid tracking approach was used to achieve this, combining image-based tracking of the needle tip with an Inertial Measurement Unit (IMU) sensor for needle-base tracking. An Adaptive Polynomial Kalman Filter (APKF) was applied to improve the motion estimation accuracy. Performance tests on a linear-rail system demonstrated the ability of the developed system to provide accurate and consistent motion estimates. The results suggest that this bio-inspired needle system using sensor fusion and advanced filtering holds promise for use in medical robotics, potentially improving the precision of biopsy procedures.

关键词： Accuracy Tracking Motion segmentation Motion estimation Biopsy Needles Robot sensing systems Polynomials Kalman filters biomedical imaging

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Deep Learning Methods For Prediction of HLA-Peptide Interactions in IDB 2

Deep Learning Methods For Prediction of HLA-Peptide Interact...

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2nd IEEE International Conference on Artificial Intelligence in Everything, AIE 2022

作者： Ameen, Zubaida Said Ibrahim, Abdullahi Umar Mubarak, Auwalu Saleh Al-Turjman, Fadi Ghali, Umar Muhammad Near East University Research Center for Ai and IoT Ai and Robotics Institute Artificial Intelligence Engineering Dept. Turkey Near East University Biomedical Engineering Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus Near East University Medical Biochemistry Dept. Turkey

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Inflammatory bowel disease (IBD) is a complicated gastrointestinal disease linked to so many factors. Studying the interactions and functions of proteins in diseases is a challenging task. Here, we tried to understand the relationship between Human Leukocyte Antigen (HLA) genes and peptides in the development of IBD. Two types of HLA genes, HLA DRB1∗ 13:01 and HLA DRB1*15:01 were considered which are highly important for presenting peptides to T-cells as one of their immunological activities, therefore, it is necessary to study their interaction with peptides. An improved version of deep learning models based on convolutional, recurrent neural networks and a hybrid of both models were proposed in this study by utilizing an embedding matrix as part of the model architecture for better encoding of amino acid features, this technique has proven to be highly effective when compared to the state of the art models. The different deep model architectures were trained and tested to predict HLA DRB1*13:01 and HLA DRB1*15:01 peptide interactions. The hybrid method gave the best performance with 0.987 as the Spearman correlation. The models proposed in this work will give better insight into the interaction between peptides and HLA genes in the development of IBD. © 2022 IEEE.

关键词： Peptides

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A bionic approach for the mechanical and electrical decoupling of an MEMS capacitive sensor in ultralow force measurement

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Frontiers of Mechanical engineering 2023年第2期18卷 297-317页

作者： Wendi GAO Bian TIAN Cunlang LIU Yingbiao MI Chen JIA Libo ZHAO Tao LIU Nan ZHU Ping YANG Qijing LIN Zhuangde JIANG Dong SUN State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265599China State Key Laboratory of Robotics and Systems(HIT) Harbin 150006China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Department of Biomedical Engineering City University of Hong KongHong KongChina

Capacitive sensors are efficient tools for biophysical force measurement,which is essential for the exploration of cellular ***,attention has been rarely given on the influences of external mechanical and internal electrical interferences on capacitive *** this work,a bionic swallow structure design norm was developed for mechanical decoupling,and the influences of structural parameters on mechanical behavior were fully analyzed and optimized.A bionic feather comb distribution strategy and a portable readout circuit were proposed for eliminating electrostatic *** instability was evaluated,and electrostatic decoupling performance was verified on the basis of a novel measurement method utilizing four complementary comb arrays and applicationspecific integrated circuit *** electrostatic pulling experiment showed that the bionic swallow structure hardly moved by 0.770 nm,and the measurement error was less than 0.009% for the area-variant sensor and 1.118% for the gap-variant sensor,which can be easily compensated in *** proposed sensor also exhibited high resistance against electrostatic rotation,and the resulting measurement error dropped below 0.751%.The rotation interferences were less than 0.330 nm and(1.829×10^(-7))°,which were 35 times smaller than those of the traditional differential *** on the proposed bionic decoupling method,the fabricated sensor exhibited overwhelming capacitive sensitivity values of 7.078 and 1.473 pF/μm for gap-variant and area-variant devices,respectively,which were the highest among the current *** immunity to mechanical disturbances was maintained simultaneously,i.e.,less than 0.369% and 0.058% of the sensor outputs for the gap-variant and area-variant devices,respectively,indicating its great performance improvements over existing devices and feasibility in ultralow biomedical force measurement.

关键词： micro-electro-mechanical system capacitive sensor bionics operation instability mechanical and electrical decoupling biomedical force measurement

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Localization of the Upper Extremity Area on the Primary Motor Cortex with Transcranial Magnetic Stimulation Figure-of-Eight Coil: A Clinical Study

Localization of the Upper Extremity Area on the Primary Moto...

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Rehabilitation engineering and Assistive Technology (i-CREATe), International Convention on

作者： Daral Maesincee Jackrit Suthakorn Sorayouth Chumnanvej (BART LAB) Faculty of Engineering Center for Biomedical and Robotics Technology Mahidol University Nakhon Pathom Thailand Department of Surgery Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand

ISBN: (数字)9798350355154

ISBN: (纸本)9798350355161

Although stroke has always been a major cause of long-term disability, mostly occurring in the upper extremities, the current conventional rehabilitative options remain both insufficient and ineffective in restoring full motor functions. As a promising alternative solution, transcranial magnetic stimulation (TMS) can non-invasively alter the excitability of and modulate the connections within the lesioned area with electromagnetic fields through a stimulating coil. Nevertheless, identifying the upper extremity area on the primary motor cortex (M1) in different patients remains a challenge due to the heterogeneous nature of the anatomy both in terms of size and location. Therefore, this study offers a method for localizing the region of interest (ROI) through an integrated method of TMS, electromyography (EMG), and optical tracking, supported by data from a clinical study, to provide an accurate and personalized ground truth for future stimulations of the same location in each patient.

关键词： Primary motor cortex Integrated optics Location awareness Coils Target tracking Transcranial magnetic stimulation Stimulated emission Stroke (medical condition) Electromyography Extremities

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Design and evaluation of a multi-finger skin-stretch tactile interface for hand rehabilitation robots

arXiv

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arXiv 2024年

作者： Ratschat, Alexandre L. Martín-Rodríguez, Rubén Vardar, Yasemin Ribbers, Gerard M. Marchal-Crespo, Laura The Department of Cognitive Robotics Delft University of Technology Delft Netherlands The Department of Rehabilitation Medicine Erasmus MC University Medical Center Rotterdam Rotterdam Netherlands The ARTORG Center for Biomedical Engineering Research University of Bern Switzerland

Object properties perceived through the tactile sense, such as weight, friction, and slip, greatly influence motor control during manipulation tasks. However, the provision of tactile information during robotic training in neurorehabilitation has not been well explored. Therefore, we designed and evaluated a tactile interface based on a two-degrees-of-freedom moving platform mounted on a hand rehabilitation robot that provides skin stretch at four fingertips, from the index through the little finger. To accurately control the rendered forces, we included a custom magnetic-based force sensor to control the tactile interface in a closed loop. The technical evaluation showed that our custom force sensor achieved measurable shear forces of ± 8 N with accuracies of 95.2-98.4% influenced by hysteresis, viscoelastic creep, and torsional deformation. The tactile interface accurately rendered forces with a step response steady-state accuracy of 97.5-99.4% and a frequency response in the range of most activities of daily living. Our sensor showed the highest measurement-range-to-size ratio and comparable accuracy to sensors of its kind. These characteristics enabled the closed-loop force control of the tactile interface for precise rendering of multi-finger two-dimensional skin stretch. The proposed system is a first step towards more realistic and rich haptic feedback during robotic sensorimotor rehabilitation, potentially improving therapy outcomes. © 2024, CC BY.

关键词： Frequency response

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