IEEE ... International Conference on Rehabilitation Robotics : [proceedings]最新文献_第6页

Improved Fascicle Length Estimates From Ultrasound Using a U-net-LSTM Framework. 基于U-net-LSTM框架的超声束束长度估计改进。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10328385

Letizia Gionfrida, Richard W Nuckols, Conor J Walsh, Robert D Howe

{"title":"Improved Fascicle Length Estimates From Ultrasound Using a U-net-LSTM Framework.","authors":"Letizia Gionfrida, Richard W Nuckols, Conor J Walsh, Robert D Howe","doi":"10.1109/ICORR58425.2023.10328385","DOIUrl":"10.1109/ICORR58425.2023.10328385","url":null,"abstract":"Brightness-mode (B-mode) ultrasound has been used to measure in vivo muscle dynamics for assistive devices. Estimation of fascicle length from B-mode images has now transitioned from time-consuming manual processes to automatic methods, but these methods fail to reach pixel-wise accuracy across extended locomotion. In this work, we aim to address this challenge by combining a U-net architecture with proven segmentation abilities with an LSTM component that takes advantage of temporal information to improve validation accuracy in the prediction of fascicle lengths. Using 64,849 ultrasound frames of the medial gastrocnemius, we semi-manually generated ground-truth for training the proposed U-net-LSTM. Compared with a traditional U-net and a CNNLSTM configuration, the validation accuracy, mean square error (MSE), and mean absolute error (MAE) of the proposed U-net-LSTM show better performance (91.4%, MSE =0.1± 0.03 mm, MAE =0.2± 0.05 mm). The proposed framework could be used for real-time, closed-loop wearable control during real-world locomotion.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10802115/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138447461","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

Individualized Three-Dimensional Gait Pattern Generator for Lower Limbs Rehabilitation Robots. 下肢康复机器人个性化三维步态模式生成器。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304753

Pablo Romero-Sorozabal, Gabriel Delgado-Oleas, Alvaro Gutierrez, Eduardo Rocon

{"title":"Individualized Three-Dimensional Gait Pattern Generator for Lower Limbs Rehabilitation Robots.","authors":"Pablo Romero-Sorozabal, Gabriel Delgado-Oleas, Alvaro Gutierrez, Eduardo Rocon","doi":"10.1109/ICORR58425.2023.10304753","DOIUrl":"10.1109/ICORR58425.2023.10304753","url":null,"abstract":"In the field of robotic gait rehabilitation, controlling robotic devices to follow specific human-like trajectories is often required. In recent years, various gait generator models have been proposed, providing customized gait patterns adjustable to a range of heights and gait speeds. However, these models were developed with a focus on gait rehabilitation devices designed to control the angular trajectories of the subject's joints, e.g. exoskeletons. Similar devices, e.g. end-effector robots, control the orientation and also the 3D position of the subject's joints and cannot easily implement these models. In this study, it is proposed a new individualized three-dimensional gait pattern generator for gait rehabilitation robots. The generator employs multi-variable regression models to predict the joint angular trajectories of the pelvis, hip, and ankle along the gait cycle. The 3D joints positions are then reconstructed by applying the predicted angular trajectories over a human model inspired on the inverted pendulum analogy using inverse kinematics. The generator's performance was statistically evaluated against real gait patterns from 42 participants walking at 8 different velocities. The predicted trajectories matched the measured ones with an average Root Mean Squared Error of 25.73 mm for all joints at all Cartesian axes, with better results between 3.3 - 5.4 km/h. Suggesting to be a good solution to be applied in end-effector gait robotic rehabilitation devices.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523554","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

A Tailorable Robotic Hand Orthosis to Support Children with Neurological Hand Impairments: a Case Study in a Child's Home. 一种可定制的机器人手部矫形器，用于支持患有神经性手部损伤的儿童：儿童之家的案例研究。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304752

Jan Dittli, Gaizka Goikoetxea-Sotelo, Jan Lieber, Roger Gassert, Andreas Meyer-Heim, Hubertus J A Van Hedel, Olivier Lambercy

{"title":"A Tailorable Robotic Hand Orthosis to Support Children with Neurological Hand Impairments: a Case Study in a Child's Home.","authors":"Jan Dittli, Gaizka Goikoetxea-Sotelo, Jan Lieber, Roger Gassert, Andreas Meyer-Heim, Hubertus J A Van Hedel, Olivier Lambercy","doi":"10.1109/ICORR58425.2023.10304752","DOIUrl":"10.1109/ICORR58425.2023.10304752","url":null,"abstract":"Neurological disorders such as traumatic brain injuries (TBI) can lead to hand impairments in children, negatively impacting their quality of life. Fully wearable robotic hand orthoses (RHO) have been proposed to actively support children and promote the use of the impaired limb in daily life. Here we report a case study on the feasibility of using the pediatric RHO PEXO for assistance at home in a 13- year-old child with hand impairment after TBI. The size and functionalities of the RHO were first fully tailored to the child's needs. We trained the child and their parent on independently using the RHO before taking it home for a period of two weeks. The use of the RHO improved hand ability. Additionally, the tailoring and training benefited the unimanual capacity (Box and Block Test score +2 after tailoring) and bimanual performance (Assisting Hand Assessment score +4) of the child with PEXO. Further, it increased device acceptance by the child and the parent. The child used PEXO at home for 76 minutes distributed over three days during eating and drinking tasks. Personal and environmental factors caused the moderate use. No adverse events or safety-related issues occurred. This study highlights the value of tailoring an assistive RHO and, for the first time, demonstrates the feasibility of home use of a pediatric RHO by children with neurological hand impairments.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523584","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

Comparison of Lower Arm Weight and Passive Elbow Joint Impedance Compensation Strategies in Non-Disabled Participants. 非残疾参与者下臂重量和被动肘关节阻抗补偿策略的比较。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304707

Suzanne Filius, Mariska Janssen, Herman van der Kooij, Jaap Harlaar

{"title":"Comparison of Lower Arm Weight and Passive Elbow Joint Impedance Compensation Strategies in Non-Disabled Participants.","authors":"Suzanne Filius, Mariska Janssen, Herman van der Kooij, Jaap Harlaar","doi":"10.1109/ICORR58425.2023.10304707","DOIUrl":"10.1109/ICORR58425.2023.10304707","url":null,"abstract":"People with severe muscle weakness in the upper extremity are in need of an arm support to enhance arm function and improve their quality of life. In addition to weight support, compensation of passive joint impedance (pJimp) seems necessary. Existing devices do not compensate for pJimp yet, and the best way to compensate for it is still unknown. The aim of this study is to 1) identify pJimp of the elbow, and 2) compare four different compensation strategies of weight and combined weight and pJimp in an active elbow support system. The passive elbow joint moments, including gravitational and pJimp contributions, were measured in 12 non-disabled participants. The four compensation strategies (scaled-model, measured, hybrid, and fitted-model) were compared using a position-tracking task in the near vertical plane. All four strategies showed a significant reduction (20-47%) in the anti-gravity elbow flexor activity measured by surface electromyography. The pJimp turned out to contribute to a large extent to the passive elbow joint moments (range took up 60%) in non-disabled participants. This underlines the relevance of compensating for pJimp in arm support systems. The parameters of the scaled-model and hybrid strategy seem to overestimate the gravitational component. Therefore, the measured and fitted-model strategies are expected to be most promising to test in people with severe muscle weakness combined with elevated pJimp.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523606","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

Human-Centered Functional Task Design for Robotic Upper-Limb Rehabilitation. 机器人上肢康复的以人为中心的功能任务设计。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304738

Anna Bucchieri, Federico Tessari, Stefano Buccelli, Giacinto Barresi, Elena De Momi, Matteo Laffranchi, Lorenzo De Michieli

引用次数: 0

1D-Convolutional Neural Networks can Quantify Therapy Content of Children and Adolescents Walking in a Robot-Assisted Gait Trainer. 1D卷积神经网络可以量化儿童和青少年在机器人辅助步态训练器中行走的治疗内容。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304726

Florian van Dellen, Cristina Gallego Vazquez, Rob Labruyere

{"title":"1D-Convolutional Neural Networks can Quantify Therapy Content of Children and Adolescents Walking in a Robot-Assisted Gait Trainer.","authors":"Florian van Dellen, Cristina Gallego Vazquez, Rob Labruyere","doi":"10.1109/ICORR58425.2023.10304726","DOIUrl":"10.1109/ICORR58425.2023.10304726","url":null,"abstract":"Therapy content, consisting of device parameter settings and therapy instructions, is crucial for an effective robot-assisted gait therapy program. Settings and instructions depend on the therapy goals of the individual patient. While device parameters can be recorded by the robot, therapeutic instructions and associated patient responses are currently difficult to capture. This limits the transferability of successful therapeutic approaches between clinics. Here, we propose that 1D-convolutional neural networks can be used to relate patient behavior during individual steps to the instructions given as a surrogate for the patient's intent. Our model takes the surface electromyography patterns of two leg muscles as input and predicts the given instruction as output. We tested this approach with data from 20 healthy children walking in a robot-assisted gait trainer with 5 different instructions. Our model performs well, with a classification accuracy of almost 90%, when the instruction targets specific aspects of gait, such as step length. This shows that 1D-convolutional neural networks are a viable tool for quantifying therapy content. Thus, they could help compare therapy approaches and identify effective strategies.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523578","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

A Case Series in Position-Aware Myoelectric Prosthesis Control Using Recurrent Convolutional Neural Network Classification with Transfer Learning. 位置感知肌电假体控制中的一个案例系列，使用带有迁移学习的递归卷积神经网络分类。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304787

Heather E Williams, Jacqueline S Hebert, Patrick M Pilarski, Ahmed W Shehata

{"title":"A Case Series in Position-Aware Myoelectric Prosthesis Control Using Recurrent Convolutional Neural Network Classification with Transfer Learning.","authors":"Heather E Williams, Jacqueline S Hebert, Patrick M Pilarski, Ahmed W Shehata","doi":"10.1109/ICORR58425.2023.10304787","DOIUrl":"10.1109/ICORR58425.2023.10304787","url":null,"abstract":"Position-aware myoelectric prosthesis controllers require long, data-intensive training routines. Transfer Learning (TL) might reduce training burden. A TL model can be pre-trained using forearm muscle signal data from many individuals to become the starting point for a new user. A recurrent convolutional neural network (RCNN)-based classifier has already been shown to benefit from TL in offline analysis (95% accuracy). The present real-time study tested whether an RCNN-based classification controller with TL (RCNN-TL) could reduce training burden, offer improved device control (per functional task performance metrics), and mitigate what is known as the \"limb position effect\". 27 participants without amputation were recruited. 19 participants performed wrist/hand movements across multiple limb positions, with resulting forearm muscle signal data used to pre-train RCNN-TL. 8 other participants donned a simulated prosthesis, retrained (calibrated) and tested RCNN-TL, plus trained and tested a conventional linear discriminant analysis classification controller (LDA-Baseline). Results confirmed that TL reduces user training burden. RCNN-TL yielded improved task performance durations over LDA-Baseline (in specific Grasp and Release phases), yet other metrics worsened. Overall, this work contributes training condition factors necessary for TL success, identifies metrics needed for comprehensive control analysis, and contributes insights towards improved position-aware control.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523579","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: 1

Design of a Self-Aligning Four-Finger Exoskeleton for Finger Abduction/Adduction and Flexion/Extension Motion. 用于手指外展/内收和屈伸运动的自对准四指外骨骼的设计。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304720

Ruipeng Ge, Yuan Liu, Zhe Yan, Qian Cheng, Shiyin Qiu, Dong Ming

{"title":"Design of a Self-Aligning Four-Finger Exoskeleton for Finger Abduction/Adduction and Flexion/Extension Motion.","authors":"Ruipeng Ge, Yuan Liu, Zhe Yan, Qian Cheng, Shiyin Qiu, Dong Ming","doi":"10.1109/ICORR58425.2023.10304720","DOIUrl":"10.1109/ICORR58425.2023.10304720","url":null,"abstract":"For wearable four-finger exoskeletons, it is still a challenge to design the metacarpophalangeal (MCP)joint abduction/adduction (a/a) kinematic chain and achieve axes self-aligning. This paper proposes a novel exoskeleton for four fingers that features a high degree of dexterity enabling MCP joint flexion/extension (f/e) and a/a motion. Other features of the exoskeleton include a self-aligning mechanism that absorbs misalignment between the exoskeleton and human joints, the ability to accommodate fingers of different sizes, and a compact design that allows simultaneous a/a motion without interference. This paper presents the exoskeleton's kinematic model, optimizes the range of motion (ROM), and length of the exoskeleton linkage using the Genetic Algorithm. We compare the four-finger MCP joint's ROM and fingertip workspace with and without the exoskeleton. Our experiments show that the proposed exoskeleton has no significant impact on the natural ROM of the four-finger MCP joint, enables the fingers to cover an average of 82.96% of the original workspace, and can reach a significant portion of the fingertip workspace.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523619","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

Hybrid Functional Electrical Stimulation and Robotic Assistance for Wrist Motion Training After Stroke: Preliminary Results. 脑卒中后手腕运动训练的混合功能电刺激和机器人辅助：初步结果。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304736

Lucille Cazenave, Aaron Yurkewich, Chiara Hohler, Thierry Keller, Carmen Krewer, Klaus Jahn, Sandra Hirche, Satoshi Endo, Etienne Burdet

{"title":"Hybrid Functional Electrical Stimulation and Robotic Assistance for Wrist Motion Training After Stroke: Preliminary Results.","authors":"Lucille Cazenave, Aaron Yurkewich, Chiara Hohler, Thierry Keller, Carmen Krewer, Klaus Jahn, Sandra Hirche, Satoshi Endo, Etienne Burdet","doi":"10.1109/ICORR58425.2023.10304736","DOIUrl":"10.1109/ICORR58425.2023.10304736","url":null,"abstract":"This work presents preliminary results of a clinical study with sub-acute stroke patients using a hybrid system for wrist rehabilitation. The patients trained their wrist flexion/extension motion through a target tracking task, where electrical stimulation and robotic torque assisted them proportionally to their tracking error. Five sub-acute stroke patients have completed the training for 3 sessions on separate days. The preliminary results show hybrid assistance improves tracking performance and motion smoothness in most participants. In each session, patients' tracking performances before and after training were evaluated in unassisted tracking trials, without assistance. Their unassisted performance was compared across sessions and the results suggest that moderately to severely impaired patients might benefit more from hybrid training with our system than mildly impaired patients. Subjective assessments from all sessions show that the patients found the use of the device very comfortable and the training enjoyable. More data is being collected and future work will aim at verifying these trends.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71523646","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

Hybrid Rehabilitation System with Motion Estimation Based on EMG Signals. 基于肌电信号的运动估计混合康复系统。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2023-09-01 DOI: 10.1109/ICORR58425.2023.10304746

Kensuke Takenaka, Keisuke Shima, Koji Shimatani

引用次数: 0