IEEE transactions on medical robotics and bionics最新文献_第4页

Design and Mathematical Modeling of a Novel Two-Degree-of-Freedom Robot-Assisted Cardiac Catheterization System 一种新型二自由度机器人辅助心导管系统的设计与数学建模

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503911

Naman Gupta;Dhruva Khanzode;Ranjan Jha

{"title":"Design and Mathematical Modeling of a Novel Two-Degree-of-Freedom Robot-Assisted Cardiac Catheterization System","authors":"Naman Gupta;Dhruva Khanzode;Ranjan Jha","doi":"10.1109/TMRB.2024.3503911","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503911","url":null,"abstract":"Cardiovascular diseases, driven by pollution and unhealthy lifestyle factors, are commonly treated with cardiac catheterization. However, this exposes medical staff to harmful X-ray radiation, leading to the development of robot-assisted catheterization systems for safer procedures. Despite their advantages, existing robotic systems are frequently complex and struggle with catheter maneuverability without a guidewire. This paper introduces a novel two-degree-of-freedom robot-assisted cardiac catheterization system, detailing its development, evaluation, and mathematical modeling. The system is designed for precise control of catheter motion through both translational and rotational movements, enhancing procedural efficiency and safety. We provide an in-depth analysis of deformation forces, stress, and strain characteristics based on catheter materials, supported by comprehensive mathematical modeling of applied forces and torques. Simulation results show that the system requires a torque of 1.870 Nm, a displacement of 0.089 m, and a velocity of 1.450 m/s for translational motion. For rotational motion, the system demands 0.915 Nm of torque, an angle of 5.102 rad, and an angular velocity of 88.735 rad/s. These results are validated against pre-existing models to confirm the system’s performance. The study concludes by presenting a three-dimensional (3D) model of the system, demonstrating its ability to improve the safety and precision of cardiac catheterization.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"230-241"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Transparency Assessment of a Gait Rehabilitation Robot With Biomimetic Knee Joints 仿生膝关节步态康复机器人的设计与透明度评估

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3504002

Prashant K. Jamwal;Shyngys Dauletbayev;Daulet Sagidoldin;Darkhan Keikibayev;Aibek Niyetkaliyev;Shahid Hussain;Sunil K. Agrawal

{"title":"Design and Transparency Assessment of a Gait Rehabilitation Robot With Biomimetic Knee Joints","authors":"Prashant K. Jamwal;Shyngys Dauletbayev;Daulet Sagidoldin;Darkhan Keikibayev;Aibek Niyetkaliyev;Shahid Hussain;Sunil K. Agrawal","doi":"10.1109/TMRB.2024.3504002","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3504002","url":null,"abstract":"Robotic exoskeletons are being increasingly used in clinics for the treatment of medicable disabilities. These exoskeletons, which closely couple with patients’ limbs, need to move in harmony with the endoskeleton motions. To achieve coordination, exoskeletons should be transparent; in other words, they should not interfere with natural human motion or their underlying coordination strategies. Transparency can be achieved through a bio-inspired exoskeleton design and also by implementing appropriate force control methods to maneuver exoskeleton motions. A new hybrid active-passive Gait Exoskeleton-Assisted Rehabilitation (GEAR) robot is presented here for the rehabilitation of lower limb disabilities. The GEAR robot is designed to enhance transparency incorporating a flexible hip joint and a biomimetic knee joint. The proposed GEAR robot also integrates a Remote Centered Motion (RCM) based passive mechanism to support torso and pelvic motions in two planes and features actuated exoskeleton legs in the sagittal plane for treadmill-assisted walking. The exoskeleton legs are actuated at their hip and knee joints using backdrivable actuators. To provide a natural walking experience, the hip joints of the exoskeleton legs offer two passive degrees of freedom in the frontal and transverse planes in addition to the actuated sagittal plane motion. The biomimetic design of the exoskeleton knee joint ensures alignment with the human anatomical knee joint by closely tracking the latter’s instantaneous center of rotation (ICR). To evaluate GEAR robot’s transparency, a comparative study was conducted, involving three healthy subjects. The participants walked freely on a treadmill and then with the GEAR robot operated first in a completely backdrivable (i.e., passive) mode and subsequently in an active mode. The sEMG data collected during these experiments were analyzed to assess robot’s transparency.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"290-302"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Robots Can Support Balancing in Healthy People 机器人如何帮助健康人保持平衡

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503913

Eisa Anwar;Sajeeva Abeywardena;Stuart C. Miller;Ildar Farkhatdinov

{"title":"How Robots Can Support Balancing in Healthy People","authors":"Eisa Anwar;Sajeeva Abeywardena;Stuart C. Miller;Ildar Farkhatdinov","doi":"10.1109/TMRB.2024.3503913","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503913","url":null,"abstract":"In manufacturing, construction, logistics, and other industrial tasks, human workers are required to handle and manipulate heavy loads such as loading packages in and out of warehouses, manipulating physical components on assembly lines, and more. However, repetitive manipulation of heavy loads can disrupt balance and lead to strains and injuries on the body, causing issues such as back pain. This concern is particularly significant in jobs involving awkward postures, e.g., aircraft and vehicle assembly and maintenance. To help address this challenge, we present a comprehensive scoping review examining robots capable of supporting physical balance in healthy individuals. Our analysis involved evaluating their capabilities, observing their functionality, and assessing their practicality. The majority of our findings (81%) were lower body exoskeletons, which, though highly mobile, can be constrained by slow control systems. Conversely, supernumerary robotic limbs and wearable gyroscopes allow unrestricted movement with less constrained control systems. Many experiments lack baseline comparisons without the robot, and some have limited participant recruitment, affecting representation. We recommend universally available testing procedures to effectively demonstrate and compare the capabilities of balance-supporting robots.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"213-229"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Musculoskeletal Modeling Based on Muscle Synergy for Prediction of Hand and Wrist Movements 基于肌肉协同作用的肌肉骨骼模型用于预测手部和腕部运动

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503920

Lizhi Pan;Qiyang Li;Jianmin Li

{"title":"Musculoskeletal Modeling Based on Muscle Synergy for Prediction of Hand and Wrist Movements","authors":"Lizhi Pan;Qiyang Li;Jianmin Li","doi":"10.1109/TMRB.2024.3503920","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503920","url":null,"abstract":"Decoding human movements using electromyography (EMG) signals is important for the development of EMG-based human-machine interfaces (HMIs). This study proposed a novel muscle synergy-based musculoskeletal model (MM) for prediction of hand and wrist movements, including wrist flexion/extension, wrist adduction/abduction, wrist pronation/supination, and metacarpophalangeal (MCP) flexion/extension. Ten limb-intact subjects were recruited for the offline experiment, and 15-channel EMG signals from the subject’s forearm were recorded. Using the non-negative matrix factorization (NMF) algorithm, four pairs of excitation signals were extracted from the multi-channel EMG signals. Then the MM driven by the extracted muscle excitations was adopted to predict hand and wrist movements. The proposed method was compared with the NMF algorithm and artificial neural network (ANN), and the prediction performance of the three was evaluated with Pearson’s correlation coefficient (r) and normalized root mean square error (NRMSE). The total average r of the proposed MM was 0.8475 across all subjects and all movement types, approximately 0.123 higher than NMF algorithm and 0.106 higher than ANN. In addition, the total average NRMSE of the proposed MM was 0.16125 across all subjects and all movement types, approximately 0.074 lower than NMF algorithm and 0.037 lower than ANN. In brief, the proposed MM showed significantly improved prediction accuracy over the NMF algorithm and ANN. This study provides a promising approach for the control of robotic arms and prostheses in EMG-based HMIs.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"337-346"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Autonomous Powered Ankle Exoskeleton Improves Foot Clearance and Knee Hyperextension After Stroke: A Case Study 自主动力踝关节外骨骼改善中风后足部间隙和膝关节超伸：一个案例研究

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503893

Kai Pruyn;Rosemarie Murray;Lukas Gabert;Tommaso Lenzi

{"title":"Autonomous Powered Ankle Exoskeleton Improves Foot Clearance and Knee Hyperextension After Stroke: A Case Study","authors":"Kai Pruyn;Rosemarie Murray;Lukas Gabert;Tommaso Lenzi","doi":"10.1109/TMRB.2024.3503893","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503893","url":null,"abstract":"Hemiparetic gait is often characterized by ankle weakness, resulting in decreased propulsion and clearance, as well as knee hyperextension. These gait deviations reduce speed and efficiency while increasing the risk of falls and osteoarthritis. Powered ankle exoskeletons have the potential to address these issues. However, only a handful of studies have investigated their effects on hemiparetic gait. The results are often inconsistent, and the biomechanical analysis rarely includes the knee or hip joint or a direct clearance measure. In this case study, we assess the ankle, knee, and hip biomechanics with and without a new autonomous powered ankle exoskeleton across different speeds and inclines. Exoskeleton assistance resulted in more normative kinematics at the subject’s self-selected walking speed. The paretic ankle angle at heel strike increased from 10° plantarflexed without the exoskeleton to 0.5° dorsiflexed with the exoskeleton, and the peak plantarflexion angle during swing decreased from 28° without the exoskeleton to 12° with the exoskeleton. Furthermore, stance knee flexion increased from 7° without the exoskeleton to 20° with the exoskeleton. Finally, foot clearance increased with the exoskeleton for all conditions between 3.1 cm and 5.4 cm. This case study highlights new mechanisms for powered ankle exoskeletons to improve hemiparetic gait.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"51-58"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759770","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Encoding Desired Deformation Profiles in Endoscope-Like Soft Robots 在类内窥镜软机器人中编码所需的变形轮廓

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503894

Daniel S. Esser;Margaret F. Rox;Robert P. Naftel;D. Caleb Rucker;Eric J. Barth;Alan Kuntz;Robert J. Webster

{"title":"Encoding Desired Deformation Profiles in Endoscope-Like Soft Robots","authors":"Daniel S. Esser;Margaret F. Rox;Robert P. Naftel;D. Caleb Rucker;Eric J. Barth;Alan Kuntz;Robert J. Webster","doi":"10.1109/TMRB.2024.3503894","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503894","url":null,"abstract":"Prior models of continuously flexible robots typically assume uniform stiffness, and in this paper we relax this assumption. Geometrically varying stiffness profiles provide additional design freedom to influence the motions and workspaces of continuum robots. These results are timely, because with recent rapid advancements in multimaterial additive manufacturing techniques, it is now straightforward to create more complex stiffness profiles in robots. The key insight of this paper is to project forces and moments applied to the robot onto its center of stiffness (i.e., the Young’s modulus-weighted center of each cross section). We show how the center of stiffness can be thought of as analogous to a “precurved backbone” in a robot with uniform stiffness. This analogy enables a large body of prior work in Cosserat Rod modeling of such robots to be applied directly to those with stiffness variations. We experimentally validate this approach using multimaterial, soft, tendon-actuated robots. Lastly, to illustrate how these results can be used in practice, we investigate how stiffness variation can improve performance in a neurosurgical task.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"392-403"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759847","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Wearable Electromyography for Personalized Musculoskeletal Trunk Models Using an Inverse Synergy-Based Approach 利用基于反协同作用的方法，为个性化肌肉骨骼躯干模型开发可穿戴肌电图仪

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503900

Jan Willem A. Rook;Massimo Sartori;Mohamed Irfan Refai

{"title":"Toward Wearable Electromyography for Personalized Musculoskeletal Trunk Models Using an Inverse Synergy-Based Approach","authors":"Jan Willem A. Rook;Massimo Sartori;Mohamed Irfan Refai","doi":"10.1109/TMRB.2024.3503900","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503900","url":null,"abstract":"Electromyography (EMG)-driven musculoskeletal models (EMS) of the trunk are used for estimating lumbosacral joint moments and compressive loads during lifting tasks. These models provide personalized estimates of the parameters using information from many sensors. However, to advance technology from labs to workplaces, there is a need for sensor reduction to improve wearability and applicability. Therefore we introduce an EMG sensor reduction approach based on inverse synergy extrapolation, to reconstruct unmeasured EMG signals for different box-lifting techniques. 12 participants performed an array of tasks (squat, stoop, unilateral twist and bilateral twist) with different weights (0 kg, 7.5 kg and 15 kg). We found that two synergies were sufficient to explain the different lifting tasks (median variance accounted for of 0.91). Building upon this, we used two sensors at optimal subject-specific muscle locations to reconstruct the EMG of four unmeasured channels. Evaluation of the reconstructed and reference EMG showed median coefficients of determination <inline-formula> <tex-math>$(R^{2})$ </tex-math></inline-formula> between 0.70 and 0.86, with median root mean squared errors (RMSE) ranging from 0.02 to 0.04 relative to maximal voluntary contraction. This indicates that our proposed method shows promise for sensor reduction for driving a trunk EMS for ambulatory biomechanical risk assessment in occupational settings and exoskeleton control.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"13-19"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and EMG-EEG Fusion-Based Admittance Control of a Hand Exoskeleton With Series Elastic Actuators 基于肌电脑融合的串联弹性外骨骼导纳控制设计

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503899

Haitao Zou;Qingcong Wu;Luo Yang;Yanghui Zhu;Hongtao Wu

{"title":"Design and EMG-EEG Fusion-Based Admittance Control of a Hand Exoskeleton With Series Elastic Actuators","authors":"Haitao Zou;Qingcong Wu;Luo Yang;Yanghui Zhu;Hongtao Wu","doi":"10.1109/TMRB.2024.3503899","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503899","url":null,"abstract":"This paper proposes an underactuated hand exoskeleton designed to assist in recovering lost grasp function. Structurally, the design incorporates a multi-link coupling mechanism driven by a single motor equipped with a series elastic actuator (SEA). The SEA enables bidirectional compliant drive and fore feedback without the need for a force sensor. The connecting rod is optimized to facilitate the natural flexion and extension of the fingers. For control, an admittance control strategy based on real-time fusion of electromyography (EMG) and electroencephalogram (EEG) signals is proposed. EMG signals are used to estimate muscle strength and control the movement of the exoskeleton. EEG signals reflect the active intention of the subjects, and admittance control adjusts the rehabilitation strategy in real-time. For the first time, the degree of concentration is used as a parameter for subject adjustment of rehabilitation training. Finally, experiments on stiffness calibration, muscle force estimation, and admittance control based on EEG-EMG fusion were conducted. The results indicate that the normalized root-mean-square-error (NRMSE) of stiffness calibration is 8.32%. The average inconsistence of concentration and joint torque (ICJT) is 73.18%. The experimental results indicate that the proposed method can enhance the subjective participation of the subjects in the rehabilitation process, thereby improving the overall rehabilitation outcomes.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"347-358"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The PneuHOPE Hand Exoskeleton: A Platform for Studying Brain Activation During Robot-Facilitated Hand Movement Using fMRI PneuHOPE 手部外骨骼：利用 fMRI 研究机器人辅助手部运动时大脑激活情况的平台

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503998

Tess B. Meier;Christopher J. Nycz;Andrew Daudelin;Gregory S. Fischer

{"title":"The PneuHOPE Hand Exoskeleton: A Platform for Studying Brain Activation During Robot-Facilitated Hand Movement Using fMRI","authors":"Tess B. Meier;Christopher J. Nycz;Andrew Daudelin;Gregory S. Fischer","doi":"10.1109/TMRB.2024.3503998","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503998","url":null,"abstract":"Upper motor neuron injuries such as traumatic brain injury and stroke can cause hemiparesis and subsequent hand impairment. Repeated hand movements in physical therapy are shown to maintain flexibility and potentially facilitate regaining functionality. To further understand the impact of hand exoskeletons on motor impairment and recovery, we aim to study brain activation during rehabilitation and assistive hand exoskeleton use. Functional magnetic resonance imaging (fMRI) can be used to measure brain activation with high spatial resolution, but devices used within a magnetic resonance imaging (MRI) machine must be designed within several constraints. We present the design of a pneumatic hand orthosis with powered extension—the PneuHOPE Hand—a wearable MRI conditional research platform to enable the studying of brain activation in the presence of hand spasticity. To demonstrate its use as an MRI compatible platform, we conducted MRI conditionality testing. Additionally, we collected brain activation data from two healthy control subject’s using fMRI to show that the exoskeleton can be comfortably worn in the MRI scanner and that appropriate brain activation data can be collected during use. The results indicate the PneuHOPE Hand platform can be safely used for neuroimaging studies in the MRI with < 12% reduction in SNR for T1 images, < 32% reduction for T2, and no visible paramagnetic artifacts.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"85-93"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep-Learning Estimation of Weight Distribution Using Joint Kinematics for Lower-Limb Exoskeleton Control 利用关节运动学深度学习估计重量分布，实现下肢外骨骼控制

IF 3.4

IEEE transactions on medical robotics and bionics Pub Date : 2024-11-21 DOI: 10.1109/TMRB.2024.3503922

Clément Lhoste;Emek Barış Küçüktabak;Lorenzo Vianello;Lorenzo Amato;Matthew R. Short;Kevin M. Lynch;Jose L. Pons

{"title":"Deep-Learning Estimation of Weight Distribution Using Joint Kinematics for Lower-Limb Exoskeleton Control","authors":"Clément Lhoste;Emek Barış Küçüktabak;Lorenzo Vianello;Lorenzo Amato;Matthew R. Short;Kevin M. Lynch;Jose L. Pons","doi":"10.1109/TMRB.2024.3503922","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503922","url":null,"abstract":"In the control of lower-limb exoskeletons with feet, the phase in the gait cycle can be identified by monitoring the weight distribution at the feet. This phase information can be used in the exoskeleton’s controller to compensate the dynamics of the exoskeleton and to assign impedance parameters. Typically the weight distribution is calculated using data from sensors such as treadmill force plates or insole force sensors. However, these solutions increase both the setup complexity and cost. For this reason, we propose a deep-learning approach that uses a short time window of joint kinematics to predict the weight distribution of an exoskeleton in real time. The model was trained on treadmill walking data from six users wearing a four-degree-of-freedom exoskeleton and tested in real time on three different users wearing the same device. This test set includes two users not present in the training set to demonstrate the model’s ability to generalize across individuals. Results show that the proposed method is able to fit the actual weight distribution with <inline-formula> <tex-math>$R^{2}=0.9$ </tex-math></inline-formula> and is suitable for real-time control with prediction times less than 1 ms. Experiments in closed-loop exoskeleton control show that deep-learning-based weight distribution estimation can be used to replace force sensors in overground and treadmill walking.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"20-26"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0