The traditional minimally invasive surgical (MIS) robots generally have bulk leader manipulators with relatively fixed working positions, which limits their further utilization in special scenarios, such as remote surgeries. This study proposes a compact and foldable leader device based on passive binocular near-infrared (NIR) optical navigation technology for MIS robots, which does not need mechanical arm linkage constraints and provides a larger range of position and orientation tracking, enabling the surgeons to perform continuous leader-follower manipulations more steadily. Moreover, the polyhedral and foldable structure of the optical leader device further reduces the spatial footprint of the MIS robot. A prototype of the optical leader devices was constructed with a weight of 186 g. Its performance was then evaluated through testing, and the maximum average absolute error in position and orientation tracking was 0.90 mm and 0.45°, respectively. Additionally, the prototype exhibits acceptable stability and a wide range of position and orientation tracking. The leader device features a compact, foldable structure with enhanced portability and excellent position and orientation tracking capabilities, facilitating precise surgical maneuvers of surgeons in scenarios of remote surgeries.
{"title":"Design and Analysis of a Compact and Foldable Master Device Based on Binocular Near-Infrared Optical Navigation Technology for Minimally Invasive Surgery Robots","authors":"Lizhi Pan;Xu Jiang;Zhikang Ma;Bo Guan;Bo Yi;Jianchang Zhao","doi":"10.1109/TMRB.2025.3550659","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550659","url":null,"abstract":"The traditional minimally invasive surgical (MIS) robots generally have bulk leader manipulators with relatively fixed working positions, which limits their further utilization in special scenarios, such as remote surgeries. This study proposes a compact and foldable leader device based on passive binocular near-infrared (NIR) optical navigation technology for MIS robots, which does not need mechanical arm linkage constraints and provides a larger range of position and orientation tracking, enabling the surgeons to perform continuous leader-follower manipulations more steadily. Moreover, the polyhedral and foldable structure of the optical leader device further reduces the spatial footprint of the MIS robot. A prototype of the optical leader devices was constructed with a weight of 186 g. Its performance was then evaluated through testing, and the maximum average absolute error in position and orientation tracking was 0.90 mm and 0.45°, respectively. Additionally, the prototype exhibits acceptable stability and a wide range of position and orientation tracking. The leader device features a compact, foldable structure with enhanced portability and excellent position and orientation tracking capabilities, facilitating precise surgical maneuvers of surgeons in scenarios of remote surgeries.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"514-527"},"PeriodicalIF":3.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084800","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}
Robotic ultrasound (US) scanning of the spine is becoming an increasingly viable radiation-free alternative to CT scans and fluoroscopy. However, due to the complex shape of the vertebra, three-dimensional (3D) US reconstructions generated from two-dimensional (2D) US scans often lack important anatomic information, such as the spinous process. This paper investigates scanning strategies that reorient the probe during US scanning to improve surface coverage of 3D US reconstructions. A two-scan procedure with a path re-planning algorithm is presented. The proposed algorithm uses information from a first exploratory scan to generate an improved imaging trajectory whereby the US probe is near-perpendicular to the targeted bone surface. The results show a 30.4%, 42.3%, and 75.0% improvement in surface coverage on a synthetic phantom, cadaver, and human volunteers, respectively, achieving up to 56% surface coverage on human volunteers. These results emphasise the value of exploiting information about the underlying anatomy to optimise the scanning trajectory. The increased surface coverage of the 3D US reconstructions will provide higher quality radiation-free visualisation, extending the role of US as a complementary imaging modality for safe and effective diagnosis and spine interventions.
{"title":"Robotic Path Re-Planning for US Reconstruction of the Spine","authors":"Kaat Van Assche;Ruixuan Li;Ayoob Davoodi;Matthias Tummers;Mouloud Ourak;Gianni Borghesan;Nicola Cavalcanti;Philipp Fürnstahl;Emmanuel Vander Poorten","doi":"10.1109/TMRB.2025.3550662","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550662","url":null,"abstract":"Robotic ultrasound (US) scanning of the spine is becoming an increasingly viable radiation-free alternative to CT scans and fluoroscopy. However, due to the complex shape of the vertebra, three-dimensional (3D) US reconstructions generated from two-dimensional (2D) US scans often lack important anatomic information, such as the spinous process. This paper investigates scanning strategies that reorient the probe during US scanning to improve surface coverage of 3D US reconstructions. A two-scan procedure with a path re-planning algorithm is presented. The proposed algorithm uses information from a first exploratory scan to generate an improved imaging trajectory whereby the US probe is near-perpendicular to the targeted bone surface. The results show a 30.4%, 42.3%, and 75.0% improvement in surface coverage on a synthetic phantom, cadaver, and human volunteers, respectively, achieving up to 56% surface coverage on human volunteers. These results emphasise the value of exploiting information about the underlying anatomy to optimise the scanning trajectory. The increased surface coverage of the 3D US reconstructions will provide higher quality radiation-free visualisation, extending the role of US as a complementary imaging modality for safe and effective diagnosis and spine interventions.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"755-767"},"PeriodicalIF":3.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949130","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}
At-home stroke rehabilitation robots could improve access to rehabilitation therapies for stroke survivors. However, as the home is a challenging environment for design, it is essential that such designs are closely linked to stakeholder needs. This paper continues previous work by the authors linking stakeholder needs to the design of an at-home stroke rehabilitation robot for the upper limb. The proposed design is a constrained cable robot with a vertical workspace, capable of supporting and measuring the motion of a stroke survivor’s arm and hand during therapy activities, with a modular end effector design to simulate a variety of activities of daily living. The technical requirements of the design are described and linked to research on therapy activities, activities of daily living, and anthropometry. The kinematic and dynamic requirements for the design are validated in experiments. Potential improvements for the design include adding powered hand modules to assist users with hand impairments, adding a third rotational degree of freedom, and investigating parallel-spring motor designs that could reduce power consumption.
{"title":"Design and Prototyping of a Cable-Driven Parallel Robot for At-Home Upper Extremity Rehabilitation","authors":"Shane Forbrigger;Shammas Mohyaddin;Ashkan Rashvand;Andrew Jerabek;Matt Robertson;Vincent DePaul;Keyvan Hashtrudi-Zaad","doi":"10.1109/TMRB.2025.3552975","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3552975","url":null,"abstract":"At-home stroke rehabilitation robots could improve access to rehabilitation therapies for stroke survivors. However, as the home is a challenging environment for design, it is essential that such designs are closely linked to stakeholder needs. This paper continues previous work by the authors linking stakeholder needs to the design of an at-home stroke rehabilitation robot for the upper limb. The proposed design is a constrained cable robot with a vertical workspace, capable of supporting and measuring the motion of a stroke survivor’s arm and hand during therapy activities, with a modular end effector design to simulate a variety of activities of daily living. The technical requirements of the design are described and linked to research on therapy activities, activities of daily living, and anthropometry. The kinematic and dynamic requirements for the design are validated in experiments. Potential improvements for the design include adding powered hand modules to assist users with hand impairments, adding a third rotational degree of freedom, and investigating parallel-spring motor designs that could reduce power consumption.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"743-754"},"PeriodicalIF":3.4,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949156","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}
Pub Date : 2025-03-14DOI: 10.1109/TMRB.2025.3563286
{"title":"IEEE Transactions on Medical Robotics and Bionics Society Information","authors":"","doi":"10.1109/TMRB.2025.3563286","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3563286","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"C3-C3"},"PeriodicalIF":3.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11004174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949202","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}
Pub Date : 2025-03-14DOI: 10.1109/TMRB.2025.3563288
{"title":"IEEE Transactions on Medical Robotics and Bionics Information for Authors","authors":"","doi":"10.1109/TMRB.2025.3563288","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3563288","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"C4-C4"},"PeriodicalIF":3.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11004177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949214","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}
Pub Date : 2025-03-14DOI: 10.1109/TMRB.2025.3563284
{"title":"IEEE Transactions on Medical Robotics and Bionics Publication Information","authors":"","doi":"10.1109/TMRB.2025.3563284","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3563284","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"C2-C2"},"PeriodicalIF":3.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11004175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084733","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}
Pub Date : 2025-03-12DOI: 10.1109/TMRB.2025.3550646
Shengcai Duan;Le Wu;Aiping Liu;Xun Chen
Hand Gesture Recognition (HGR) employing surface electromyography (sEMG) and accelerometer (ACC) signals has garnered increasing interest in areas of bionic prostheses and human-machine interaction. However, existing multimodal approaches predominantly extract global specificity at a single temporal scale, which neglects local dynamic characteristics. This limitation hinders the effective capture of global-local temporal information, resulting in restricted performance and frequent misclassification of dynamic gestures. To this end, we propose a novel global-local Fusion model, termed Temporal-spatial Dependence Fusion (TsdFusion), for sEMG-ACC-based HGR. TsdFusion harnesses temporal-spatial dependencies (Tsd) from multi-time scale handcrafted features and employs a Convolution-Transformer framework for global-local fusion, thus enriching local dynamic information while preserving global insights. Specifically, the Tsd inputs are independently constructed from sEMG and ACC through multi-time scale window segmentation and feature engineering. Furthermore, the global and local temporal-spatial correlations within unimodal Tsd inputs are characterized by the unimodal transformer and dimension-wise convolution modules, respectively. Subsequently, a Convolution-coupled-transformer progressive hierarchical fusion module effectively integrates intramodal specificity and intermodal hierarchical relationship for final prediction. Evaluations on four public datasets, including transradial amputees and healthy subjects, demonstrate TsdFusion outperforms the state-of-the-art multimodal HGR methods. The TsdFusion effectively recognizes dynamic gestures, facilitating promising HGR-based interaction for prostheses or assistance robotics.
{"title":"A Global–Local Fusion Model Exploring Temporal–Spatial Dependence for Multimodal Hand Gesture Recognition","authors":"Shengcai Duan;Le Wu;Aiping Liu;Xun Chen","doi":"10.1109/TMRB.2025.3550646","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550646","url":null,"abstract":"Hand Gesture Recognition (HGR) employing surface electromyography (sEMG) and accelerometer (ACC) signals has garnered increasing interest in areas of bionic prostheses and human-machine interaction. However, existing multimodal approaches predominantly extract global specificity at a single temporal scale, which neglects local dynamic characteristics. This limitation hinders the effective capture of global-local temporal information, resulting in restricted performance and frequent misclassification of dynamic gestures. To this end, we propose a novel global-local Fusion model, termed Temporal-spatial Dependence Fusion (TsdFusion), for sEMG-ACC-based HGR. TsdFusion harnesses temporal-spatial dependencies (Tsd) from multi-time scale handcrafted features and employs a Convolution-Transformer framework for global-local fusion, thus enriching local dynamic information while preserving global insights. Specifically, the Tsd inputs are independently constructed from sEMG and ACC through multi-time scale window segmentation and feature engineering. Furthermore, the global and local temporal-spatial correlations within unimodal Tsd inputs are characterized by the unimodal transformer and dimension-wise convolution modules, respectively. Subsequently, a Convolution-coupled-transformer progressive hierarchical fusion module effectively integrates intramodal specificity and intermodal hierarchical relationship for final prediction. Evaluations on four public datasets, including transradial amputees and healthy subjects, demonstrate TsdFusion outperforms the state-of-the-art multimodal HGR methods. The TsdFusion effectively recognizes dynamic gestures, facilitating promising HGR-based interaction for prostheses or assistance robotics.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"723-733"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949155","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}
Despite continuous advances in three-dimensional (3D) fusion imaging, two-dimensional (2D) X-ray-based fluoroscopy is still the gold standard intra-operative image guidance tool in endovascular interventions. The adoption of robotic technology offers the potential to bring intra-operative radiation exposure down to a minimum, or even eliminate it. Non-ionizing approaches, such as Intravascular Ultrasound (IVUS), are progressively explored as standalone or fluoroscopy-adjunct techniques for 3D vasculature reconstruction. We have previously demonstrated the feasibility of real-time 3D Main Vessel (MV) modeling from the fusion of IVUS and EM pose data obtained from sensors embedded at the tip of a robotic catheter. This paper proposes to advance MV modeling towards a comprehensive radiation-free 3D guidance framework by means of intra-operative Side Branch (SB) detection and modeling. Two models are proposed to approximate the geometry of SB vessel ostia: a sphere and a cylinder. An Unscented Kalman Filter (UKF) recursively estimates the state of these models considering the MV model, while the catheters navigates through the vessel. In silico and in vitro validation results show the potential clinical value of the proposed strategy for facilitating safer robotic catheter steering.
{"title":"Intra-Operative 3-D Modeling of Side Branch Vessels for IVUS-Guided Catheter Navigation","authors":"Beatriz Farola Barata;Wim-Alexander Beckers;Gianni Borghesan;Diego Dall'Alba;Johan Bennett;Keir McCutcheon;Paolo Fiorini;Jos Vander Sloten;Emmanuel Vander Poorten","doi":"10.1109/TMRB.2025.3550709","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550709","url":null,"abstract":"Despite continuous advances in three-dimensional (3D) fusion imaging, two-dimensional (2D) X-ray-based fluoroscopy is still the gold standard intra-operative image guidance tool in endovascular interventions. The adoption of robotic technology offers the potential to bring intra-operative radiation exposure down to a minimum, or even eliminate it. Non-ionizing approaches, such as Intravascular Ultrasound (IVUS), are progressively explored as standalone or fluoroscopy-adjunct techniques for 3D vasculature reconstruction. We have previously demonstrated the feasibility of real-time 3D Main Vessel (MV) modeling from the fusion of IVUS and EM pose data obtained from sensors embedded at the tip of a robotic catheter. This paper proposes to advance MV modeling towards a comprehensive radiation-free 3D guidance framework by means of intra-operative Side Branch (SB) detection and modeling. Two models are proposed to approximate the geometry of SB vessel ostia: a sphere and a cylinder. An Unscented Kalman Filter (UKF) recursively estimates the state of these models considering the MV model, while the catheters navigates through the vessel. In silico and in vitro validation results show the potential clinical value of the proposed strategy for facilitating safer robotic catheter steering.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"443-454"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084787","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}
Pub Date : 2025-03-12DOI: 10.1109/TMRB.2025.3550674
Anna Bicchi;Xiu Zhang;Benjamín Ignacio Fortuño Jara;Vanessa Cannizzaro;Angela Peloso;Elena De Momi
Minimally invasive mitral valve repair offers significant advantages over traditional open-heart surgery, yet it remains a complex procedure that exposes both patients and medical staff to radiation. To address these challenges, a significant research interest is growing in automating these manual procedures. Continuum robots represent a promising approach, thanks to their ability to navigate confined spaces. However, their nonlinear behavior presents challenges in modeling and control. In this study, we developed a robust position control method for a variable-length tendon-driven continuum robot. We designed a control system that effectively tracks the desired target positions by employing a constant curvature model and a Jacobian-based control algorithm with real-time position feedback. We assessed the stability of our system through Lyapunov analysis, demonstrating reliable convergence to these target positions. Experimental validation conducted in a cardiovascular phantom demonstrated significant improvements with respect to the state of the art. Our method achieved a trajectory following error of approximately 2.43 mm [1.63, 3.23] and a target position error of about 1.92 mm [1.73, 3.13]. Moreover, the computation time per trajectory point was reduced to approximately 0.04 seconds, highlighting enhanced computational efficiency. These results showcase improved accuracy and efficiency in minimally invasive mitral valve repair procedures.
{"title":"Model-Based Position Control of a Tendon-Driven Variable-Length Continuum Robot for Minimally Invasive Mitral Valve Repair","authors":"Anna Bicchi;Xiu Zhang;Benjamín Ignacio Fortuño Jara;Vanessa Cannizzaro;Angela Peloso;Elena De Momi","doi":"10.1109/TMRB.2025.3550674","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550674","url":null,"abstract":"Minimally invasive mitral valve repair offers significant advantages over traditional open-heart surgery, yet it remains a complex procedure that exposes both patients and medical staff to radiation. To address these challenges, a significant research interest is growing in automating these manual procedures. Continuum robots represent a promising approach, thanks to their ability to navigate confined spaces. However, their nonlinear behavior presents challenges in modeling and control. In this study, we developed a robust position control method for a variable-length tendon-driven continuum robot. We designed a control system that effectively tracks the desired target positions by employing a constant curvature model and a Jacobian-based control algorithm with real-time position feedback. We assessed the stability of our system through Lyapunov analysis, demonstrating reliable convergence to these target positions. Experimental validation conducted in a cardiovascular phantom demonstrated significant improvements with respect to the state of the art. Our method achieved a trajectory following error of approximately 2.43 mm [1.63, 3.23] and a target position error of about 1.92 mm [1.73, 3.13]. Moreover, the computation time per trajectory point was reduced to approximately 0.04 seconds, highlighting enhanced computational efficiency. These results showcase improved accuracy and efficiency in minimally invasive mitral valve repair procedures.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"562-571"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084734","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}
Pub Date : 2025-03-12DOI: 10.1109/TMRB.2025.3550642
Jairo Y. Maldonado-Contreras;Cole Johnson;Sixu Zhou;Hanjun Kim;Ian Knight;Kinsey R. Herrin;Aaron J. Young
This study introduces a novel continual learning algorithm that incrementally improves the performance of deep-learning-based walking speed estimators during level-ground walking with a powered knee-ankle prosthesis. While user-dependent (DEP) estimators generally outperform user-independent (IND) estimators, they require the pre-collection of DEP training data. In contrast, our real-time algorithm adapts IND estimators to self-labeled DEP data generated during walking, eliminating the need for pre-collected datasets. The algorithm also features a biomimetic scaling mechanism that adjusts prosthetic assistance based on speed estimates. We evaluated our algorithm on novel subjects (N=10) with unilateral above-knee amputations during treadmill and overground walking. For treadmill trials, when adapted with estimated and ground truth labels, estimators achieved mean absolute errors (MAEs) of 0.074 [0.023] (mean, [standard deviation]) and 0.074 [0.018] m/s, respectively, reflecting a significant 28% (p ¡ 0.05) reduction in MAE compared to non-adapted estimators. For overground trials, treadmill-adapted estimators demonstrated a significant 18% (p ¡ 0.05) reduction in MAE compared to non-adapted estimators. Our algorithm significantly reduced speed estimation errors within one minute of walking and delivered biomimetic assistance (r ${=}0.91$ ) across speeds. This approach allows off-the-shelf powered prostheses to seamlessly adapt to new users, delivering biomimetic assistance through precise, real-time walking speed estimation.
{"title":"Real-Time Adaptation of Deep Learning Walking Speed Estimators Enables Biomimetic Assistance Modulation in an Open-Source Bionic Leg","authors":"Jairo Y. Maldonado-Contreras;Cole Johnson;Sixu Zhou;Hanjun Kim;Ian Knight;Kinsey R. Herrin;Aaron J. Young","doi":"10.1109/TMRB.2025.3550642","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3550642","url":null,"abstract":"This study introduces a novel continual learning algorithm that incrementally improves the performance of deep-learning-based walking speed estimators during level-ground walking with a powered knee-ankle prosthesis. While user-dependent (DEP) estimators generally outperform user-independent (IND) estimators, they require the pre-collection of DEP training data. In contrast, our real-time algorithm adapts IND estimators to self-labeled DEP data generated during walking, eliminating the need for pre-collected datasets. The algorithm also features a biomimetic scaling mechanism that adjusts prosthetic assistance based on speed estimates. We evaluated our algorithm on novel subjects (N=10) with unilateral above-knee amputations during treadmill and overground walking. For treadmill trials, when adapted with estimated and ground truth labels, estimators achieved mean absolute errors (MAEs) of 0.074 [0.023] (mean, [standard deviation]) and 0.074 [0.018] m/s, respectively, reflecting a significant 28% (p ¡ 0.05) reduction in MAE compared to non-adapted estimators. For overground trials, treadmill-adapted estimators demonstrated a significant 18% (p ¡ 0.05) reduction in MAE compared to non-adapted estimators. Our algorithm significantly reduced speed estimation errors within one minute of walking and delivered biomimetic assistance (r <inline-formula> <tex-math>${=}0.91$ </tex-math></inline-formula>) across speeds. This approach allows off-the-shelf powered prostheses to seamlessly adapt to new users, delivering biomimetic assistance through precise, real-time walking speed estimation.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"711-722"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073147","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}
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