{"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}
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}
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}
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}
{"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}
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}
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}
{"title":"Preliminary Assessment of Accurate Motion Detection via Magnetic Tracking Toward Wearable Technologies","authors":"Federico Masiero;Valerio Ianniciello;Roberto Raeli;Edoardo Sinibaldi;Lorenzo Masia;Christian Cipriani","doi":"10.1109/TMRB.2024.3504003","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3504003","url":null,"abstract":"Tracking permanent magnets represents a low-footprint and passive approach to monitoring objects or human motion by attaching or embedding magnets therein. Recent tracking techniques achieved high-bandwidth detection considering a simplified model for the magnetic sources, i.e., the dipole model. Nonetheless, such a model can lead to inaccurate results any time a non-spherical magnet approaches the sensor array. Here, we present a novel tracking algorithm based on an analytical model for permanent magnet cylinders with uniform arbitrary magnetization. By means of a physical system mounting 20 magnetometers, we compared the tracking accuracy obtained with our algorithm vs. results obtained by using the dipole model and with respect to a ground-truth reference. With a single magnetic target, our algorithm can significantly lower position (up to 0.68 mm) and orientation errors (up to 2.5°) while enabling online tracking (computation time below 19 ms). We also accurately tracked two magnets, by obtaining a reduction in position error (up to 0.92 mm) vs. the dipole-based algorithm. These findings broaden the applicability of accurate magnetic tracking to real-time applications, facilitating the tracking of multiple magnetic targets in proximity of the magnetic sensors. This advancement opens avenues for applications in wearable devices, advancing the field of motion detection beyond traditional inertial measurement units.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"59-65"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759804","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529895","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}
{"title":"Design and Overground Testing of a Portable Hip Exosuit for Enhancing Running Efficiency","authors":"Alessandro Ciaramella;Tommaso Bagneschi;Enrica Tricomi;Francesco Missiroli;Xiaohui Zhang;Antonio Frisoli;Lorenzo Masia","doi":"10.1109/TMRB.2024.3503905","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503905","url":null,"abstract":"Over the past decade, considerable steps have been made in designing wearable assistive devices that reduce the metabolic cost of walking. As the field continues to advance, a growing emphasis is extending to human running, driven by the goal of improving efficiency and reducing metabolic strain. In our study, we developed a portable active exosuit to support hip extension during endurance running. The exosuit, featuring custom linear actuators and a control system synchronous with the wearer’s kinematics, initially underwent bench testing and, finally, a field evaluation with users running at their self-selected pace on an athletics track. Results from seven participants showed a significant reduction in the metabolic cost of transport when the exosuit was active. Specifically, we observed a 9.6% decrease with respect to the unpowered condition, with a 4.3% net saving compared to not wearing the device. Additionally, kinematic assessments revealed no alteration of the participants’ motion after toe-off, indicating transparency to physiological movement pattern during hip flexion. These findings highlight the potential of the exosuit to enhance athletic performance, opening new possibilities for running assistance in real-world scenarios.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"33-42"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529898","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}
{"title":"AR and MR in Dentistry: Developments, Applications, and Prospects","authors":"Faizan Ahmad;Waheed Ahmad;Jing Xiong;Zeyang Xia","doi":"10.1109/TMRB.2024.3503999","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3503999","url":null,"abstract":"Augmented Reality (AR) and Mixed Reality (MR) are cutting-edge technologies that are substantially impacting digital dentistry. These innovations not only propel dentistry into the digital age, but also introduce novel, non-invasive, and immersive treatment methodologies. This review collates and summarizes the latest developments and applications of AR and MR in digital dentistry. In contemporary practice, digital information, such as CT scans, is predominantly used for presurgical verification. However, integrating patients digital 3D information into real-world environments through AR and MR allows dental professionals to visualize diagnostic and therapeutic data using a Head-Mounted Display (HMD). This integration enhances not only efficiency and safety, but also elevates surgical training. Despite these benefits, further enhancements are required for these technologies to achieve broader acceptance in clinical dentistry. In this review, we have dedicated a separate section discussing the prospective applications and future directions of AR and MR, including optimizing HMD technology, developing intraoperative feedback navigation technology, advancing human-machine interaction (HMI) technology, and improving soft-tissue visualization technology. The literature suggests that AR and MR applications are particularly advantageous in dentistry, despite some limitations. With ongoing developments in areas such as haptics and robotics, it is expected that AR and MR will become increasingly integral to dental practices in the near future.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 1","pages":"171-188"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529899","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}