Traditional transfemoral lower-limb prostheses often overlook the intuitive neuronal connections between the brain and prosthetic actuators. This study bridges this gap by integrating a functional near-infrared spectroscopy (fNIRS) into real-time lower-limb prosthesis control with preliminary clinical tests on the above-knee amputee, enabling a more reliable volitional control of the prosthesis. Cerebral hemodynamic responses were measured using a 56-channel fNIRS headset, and lower-limb kinematics were recorded with a optical motion capture system. Artifacts in fNIRS were mitigated using short-separation regression, and eight features of the fNIRS data were extracted. ANOVA revealed the means, slope, and entropy as top-performing features across all subjects. Among eight classifiers tested, k-nearest neighbor (KNN) emerged as the most accurate. In this study, we recruited eleven healthy subjects and one unilateral transfemoral amputee. Classification rates surpassed 97% for all classes, maintaining an average accuracy of $99.86pm 0.01$ %. Notably, the amputee exhibited higher precision, sensitivity, and F1 scores than healthy subjects. Maximum temporal latencies for healthy subjects were $120.00pm 49.40$ ms during sit-down and $119.09pm 45.71$ ms during stand-up, while the amputee showed maximum temporal latencies of 90 ms and 190 ms, respectively. This study marks the first application of action detection in sit-to-stand tasks for transfemoral amputees via fNIRS, which underscores the potential of fNIRS in neuroprostheses control.
{"title":"fNIRS-Based Action Detection for Lower Limb Amputees in Sit-to-Stand Tasks","authors":"Ruisen Huang;Wenze Shang;Yongchen Li;Guanglin Li;Xinyu Wu;Fei Gao","doi":"10.1109/TMRB.2025.3573411","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573411","url":null,"abstract":"Traditional transfemoral lower-limb prostheses often overlook the intuitive neuronal connections between the brain and prosthetic actuators. This study bridges this gap by integrating a functional near-infrared spectroscopy (fNIRS) into real-time lower-limb prosthesis control with preliminary clinical tests on the above-knee amputee, enabling a more reliable volitional control of the prosthesis. Cerebral hemodynamic responses were measured using a 56-channel fNIRS headset, and lower-limb kinematics were recorded with a optical motion capture system. Artifacts in fNIRS were mitigated using short-separation regression, and eight features of the fNIRS data were extracted. ANOVA revealed the means, slope, and entropy as top-performing features across all subjects. Among eight classifiers tested, k-nearest neighbor (KNN) emerged as the most accurate. In this study, we recruited eleven healthy subjects and one unilateral transfemoral amputee. Classification rates surpassed 97% for all classes, maintaining an average accuracy of <inline-formula> <tex-math>$99.86pm 0.01$ </tex-math></inline-formula>%. Notably, the amputee exhibited higher precision, sensitivity, and F1 scores than healthy subjects. Maximum temporal latencies for healthy subjects were <inline-formula> <tex-math>$120.00pm 49.40$ </tex-math></inline-formula> ms during sit-down and <inline-formula> <tex-math>$119.09pm 45.71$ </tex-math></inline-formula> ms during stand-up, while the amputee showed maximum temporal latencies of 90 ms and 190 ms, respectively. This study marks the first application of action detection in sit-to-stand tasks for transfemoral amputees via fNIRS, which underscores the potential of fNIRS in neuroprostheses control.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1248-1262"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887736","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573436
Lizhi Pan;Tianze Zhang;Yiding Cheng;Zhikang Ma;Jianmin Li
Continuum robots show great potential in the medical field owing to their theoretically infinite degrees of freedom, but they still face challenges in shape sensing. This study focuses on shape sensing of continuum robots and designs a low-cost flexible resistive strain sensor based on multi-walled carbon nanotubes and polydimethylsiloxane. The sensor exhibits high linearity over the bending range of 0°-65° and offers 100% elongation at break and excellent mechanical properties, also showing good biocompatibility and environmental adaptability. A $3{times }3$ array of these sensors is attached to the continuum surgical robot to realize shape sensing. The angle change of the continuum at each position is determined from the resistance change of each sensor during bending. The position information of five key points can be obtained from these angles, and the shape is reconstructed by fitting each point. Experimental results show that the proposed sensor can accurately sense various bending shapes of the continuum within the stable linear bending range, and the position error of the distal end fluctuates about 2% of the overall shape. This study provides a new solution for shape sensing of continuum surgical robots, demonstrating strong application potential.
{"title":"Shape Sensing for Continuum Robots Based on MWCNTs-PDMS Flexible Resistive Strain Sensors","authors":"Lizhi Pan;Tianze Zhang;Yiding Cheng;Zhikang Ma;Jianmin Li","doi":"10.1109/TMRB.2025.3573436","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573436","url":null,"abstract":"Continuum robots show great potential in the medical field owing to their theoretically infinite degrees of freedom, but they still face challenges in shape sensing. This study focuses on shape sensing of continuum robots and designs a low-cost flexible resistive strain sensor based on multi-walled carbon nanotubes and polydimethylsiloxane. The sensor exhibits high linearity over the bending range of 0°-65° and offers 100% elongation at break and excellent mechanical properties, also showing good biocompatibility and environmental adaptability. A <inline-formula> <tex-math>$3{times }3$ </tex-math></inline-formula> array of these sensors is attached to the continuum surgical robot to realize shape sensing. The angle change of the continuum at each position is determined from the resistance change of each sensor during bending. The position information of five key points can be obtained from these angles, and the shape is reconstructed by fitting each point. Experimental results show that the proposed sensor can accurately sense various bending shapes of the continuum within the stable linear bending range, and the position error of the distal end fluctuates about 2% of the overall shape. This study provides a new solution for shape sensing of continuum surgical robots, demonstrating strong application potential.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1286-1296"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887773","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573412
Yuesheng Qu;Chengyu Zhang;Chi Zhang;Siyang Zuo
In robot-assisted endoscopic procedures, a guiding sheath must be flexibly advanced through anatomic paths via natural orifices, while maintaining sufficient rigidity to serve as a base for the surgical instruments used in dexterous diagnostic and therapeutic tasks. Therefore, developing a guiding sheath with the capacity of both flexible access and variable stiffness is imperative and challenging. To address these challenges, we have developed a novel robotic guiding sheath. Its stiffness can be managed using the innovatively-manufactured variable stiffness coating layer (VSCL), which has a thickness of only 1 mm and is composed of polycaprolactone (PCL) and conductive graphene. An active water heating and cooling mechanism was designed to regulate the temperature of the VSCL, thereby controlling the stiffness of the guiding sheath. Through detailed performance evaluation, the guiding sheath achieved a fixed-end bending stiffness gain of 25.76 and a mid-span bending stiffness gain of 25.01, reaching a fixed-end bending stiffness of 739.63 N/m and a mid-span bending stiffness of 5779.33 N/m. The fast switching between the rigid and flexible states was realized with switching times of 6.5 s (from rigid state to flexible state) and 10.0 s (from flexible state to rigid state). The sheath was also validated with phantom and ex-vivo experiments. The capability of this guiding sheath to traverse the tortuous digestive tract in a flexible state was proved. Additionally, the guiding sheath in a rigid state can significantly improve instrument manipulation stability during the ex-vivo trials. The experimental results demonstrated the potential clinical value of this system.
{"title":"A Novel Robotic Guiding Sheath With Variable Stiffness Capability Based on Conductive Graphene and Thermoplastic Polymer","authors":"Yuesheng Qu;Chengyu Zhang;Chi Zhang;Siyang Zuo","doi":"10.1109/TMRB.2025.3573412","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573412","url":null,"abstract":"In robot-assisted endoscopic procedures, a guiding sheath must be flexibly advanced through anatomic paths via natural orifices, while maintaining sufficient rigidity to serve as a base for the surgical instruments used in dexterous diagnostic and therapeutic tasks. Therefore, developing a guiding sheath with the capacity of both flexible access and variable stiffness is imperative and challenging. To address these challenges, we have developed a novel robotic guiding sheath. Its stiffness can be managed using the innovatively-manufactured variable stiffness coating layer (VSCL), which has a thickness of only 1 mm and is composed of polycaprolactone (PCL) and conductive graphene. An active water heating and cooling mechanism was designed to regulate the temperature of the VSCL, thereby controlling the stiffness of the guiding sheath. Through detailed performance evaluation, the guiding sheath achieved a fixed-end bending stiffness gain of 25.76 and a mid-span bending stiffness gain of 25.01, reaching a fixed-end bending stiffness of 739.63 N/m and a mid-span bending stiffness of 5779.33 N/m. The fast switching between the rigid and flexible states was realized with switching times of 6.5 s (from rigid state to flexible state) and 10.0 s (from flexible state to rigid state). The sheath was also validated with phantom and ex-vivo experiments. The capability of this guiding sheath to traverse the tortuous digestive tract in a flexible state was proved. Additionally, the guiding sheath in a rigid state can significantly improve instrument manipulation stability during the ex-vivo trials. The experimental results demonstrated the potential clinical value of this system.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1275-1285"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887829","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573420
Mingyang Liu;Geng Li;Hao Yu;Rui Song;Yibin Li;Max Q.-H. Meng;Zhe Min
In this paper, we propose a novel unsupervised learning-based non-rigid 3D point set registration method, Learning Coherent Point Drift Network (LCNet), for image-guided liver surgery. We reformulate the classical probabilistic registration approach, i.e., Coherent Point Drift (CPD) into a learning-based paradigm. We first utilise the feature extraction module (FEM) to extract the features of two original point sets, which are robust to rigid transformation. Subsequently, we establish reliable correspondences between the point sets using the optimal transport (OT) module by leveraging both original points and learned features. Then, rather than directly regressing displacement vectors, we compute the displacements by solving the involved matrix equation in the transformation module, where the point localization noise is explicitly considered. In addition, we present three variants of the proposed approach, i.e., LCNet, LCNet-ED and LCNet-WD. Among these, LCNet outperforms the other two, demonstrating the superiority of the Chamfer loss. We have extensively evaluated LCNet on the simulated and real datasets. Under experimental conditions with the rotation angle lies in the range of $[{-}45^{circ },45^{circ }]$ and the translation in the range of $[{-}30 mm, 30 mm]$ , LCNet achieves the root-mean-square-error (rmse) value being 3.46 mm on the MedShapeNet dataset, while those using CPD and RoITr are 7.65 mm $(plt 0.001)$ and 6.71 mm $(plt 0.001)$ respectively. Experimental results show that LCNet exhibits significant improvements over existing state-of-the-art registration methods and shed light on its promising use in image-guided liver surgery.
在本文中，我们提出了一种新的基于无监督学习的非刚性三维点集配准方法——学习相干点漂移网络（LCNet），用于图像引导肝脏手术。我们将经典的概率配准方法，即相干点漂移（CPD）重新表述为基于学习的范式。首先利用特征提取模块（FEM）提取两个原始点集的特征，这些特征对刚性变换具有鲁棒性；随后，我们利用最优传输（OT）模块利用原始点和学习特征在点集之间建立可靠的对应关系。然后，我们不是直接回归位移向量，而是通过求解变换模块中所涉及的矩阵方程来计算位移，其中明确考虑了点定位噪声。此外，我们提出了该方法的三种变体，即LCNet， LCNet- ed和LCNet- wd。其中，LCNet的性能优于其他两种，说明了Chamfer损耗的优越性。我们在模拟和真实数据集上对LCNet进行了广泛的评估。在旋转角度为$[{-}45^{circ},45^{circ}]$，平移角度为$[{-}30 mm, 30 mm]$的实验条件下，LCNet在MedShapeNet数据集上获得的均方根误差（rmse）值为3.46 mm，而使用CPD和RoITr的rmse值分别为7.65 mm $(plt 0.001)$和6.71 mm $(plt 0.001)$。实验结果表明，LCNet比现有的最先进的注册方法有了显著的改进，并揭示了其在图像引导肝脏手术中的应用前景。
{"title":"LCNet: A Robust and Accurate Non-Rigid 3-D Point Set Registration Approach for Image-Guided Liver Surgery","authors":"Mingyang Liu;Geng Li;Hao Yu;Rui Song;Yibin Li;Max Q.-H. Meng;Zhe Min","doi":"10.1109/TMRB.2025.3573420","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573420","url":null,"abstract":"In this paper, we propose a novel unsupervised learning-based non-rigid 3D point set registration method, Learning Coherent Point Drift Network (LCNet), for image-guided liver surgery. We reformulate the classical probabilistic registration approach, i.e., Coherent Point Drift (CPD) into a learning-based paradigm. We first utilise the feature extraction module (FEM) to extract the features of two original point sets, which are robust to rigid transformation. Subsequently, we establish reliable correspondences between the point sets using the optimal transport (OT) module by leveraging both original points and learned features. Then, rather than directly regressing displacement vectors, we compute the displacements by solving the involved matrix equation in the transformation module, where the point localization noise is explicitly considered. In addition, we present three variants of the proposed approach, i.e., LCNet, LCNet-ED and LCNet-WD. Among these, LCNet outperforms the other two, demonstrating the superiority of the Chamfer loss. We have extensively evaluated LCNet on the simulated and real datasets. Under experimental conditions with the rotation angle lies in the range of <inline-formula> <tex-math>$[{-}45^{circ },45^{circ }]$ </tex-math></inline-formula> and the translation in the range of <inline-formula> <tex-math>$[{-}30 mm, 30 mm]$ </tex-math></inline-formula>, LCNet achieves the root-mean-square-error (rmse) value being 3.46 mm on the MedShapeNet dataset, while those using CPD and RoITr are 7.65 mm <inline-formula> <tex-math>$(plt 0.001)$ </tex-math></inline-formula> and 6.71 mm <inline-formula> <tex-math>$(plt 0.001)$ </tex-math></inline-formula> respectively. Experimental results show that LCNet exhibits significant improvements over existing state-of-the-art registration methods and shed light on its promising use in image-guided liver surgery.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1073-1086"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887830","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573408
Samuel Bello;Mark M. Iskarous;Sriramana Sankar;Nitish V. Thakor
Palpation is a relatively safe, rapid, and low-cost method used by clinicians for examining diseased tissues. However, depending on the scanning speed and the physician’s experience, the size of the physical features in the body can be miscategorized or overlooked entirely. By designing tactile sensors and signal processing algorithms that mimic the body’s ability to account for variations in speed when scanning an object, we can solve the problem described above in an artificial system. We utilized a piezoresistive tactile sensor attached to a robotic arm to palpate fractures at different speeds. The analog tactile signals generated from the tactile sensor are converted into spike trains which are then scaled in time to encode the sensor data invariant of the speed of palpation. With a few principal components, the scaled dataset achieves a higher classification accuracy compared to the original dataset. Additionally, the scaled data was more robust to both spike timing noise and untrained speed conditions compared to the original data. Lastly, we demonstrated that this system could be applied in a medical setting by discriminating between 3 different fracture conditions (none, transverse, and communicated) in the ulna of a chicken wing with 99.8% accuracy at 3 different speeds.
{"title":"Robotic Palpation of Fractures Using Bioinspired Tactile Sensor and Neuromorphic Encoding Algorithm","authors":"Samuel Bello;Mark M. Iskarous;Sriramana Sankar;Nitish V. Thakor","doi":"10.1109/TMRB.2025.3573408","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573408","url":null,"abstract":"Palpation is a relatively safe, rapid, and low-cost method used by clinicians for examining diseased tissues. However, depending on the scanning speed and the physician’s experience, the size of the physical features in the body can be miscategorized or overlooked entirely. By designing tactile sensors and signal processing algorithms that mimic the body’s ability to account for variations in speed when scanning an object, we can solve the problem described above in an artificial system. We utilized a piezoresistive tactile sensor attached to a robotic arm to palpate fractures at different speeds. The analog tactile signals generated from the tactile sensor are converted into spike trains which are then scaled in time to encode the sensor data invariant of the speed of palpation. With a few principal components, the scaled dataset achieves a higher classification accuracy compared to the original dataset. Additionally, the scaled data was more robust to both spike timing noise and untrained speed conditions compared to the original data. Lastly, we demonstrated that this system could be applied in a medical setting by discriminating between 3 different fracture conditions (none, transverse, and communicated) in the ulna of a chicken wing with 99.8% accuracy at 3 different speeds.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1175-1185"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887792","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573390
Alexander D. Smith;Anant Naik;Suguna Pappu;Paul M. Arnold;Kris Hauser
Objective: This paper proposes a low-cost real-time navigation system to assist a surgeon in placing external ventricular drains. Methods: In our approach, the base of an articulated arm coordinate measuring machine is bolted to the patient’s skull, and a graphical user interface quickly guides the operator through the image registration and 3D navigation to place an external ventricular drain at a desired target specified relative to preoperative imaging. The method can be employed in workflows with and without fiducials embedded in the preoperative imaging. Results: The proposed system is evaluated using precise registration instruments, human phantom models, and ex vivo ovine models, demonstrating less than 2 mm of error with fiducials and less than 4 mm of error without fiducials. Conclusion: The registration procedure takes less than one minute and can be performed intuitively by a single operator without an assistant. Significance: Our proposed system enables real-time image-guided navigation to be used in bedside external ventricular drain placement, with potential to expand access to this procedure.
{"title":"A Low-Cost Articulated Arm Navigation System for External Ventricular Drain Placement","authors":"Alexander D. Smith;Anant Naik;Suguna Pappu;Paul M. Arnold;Kris Hauser","doi":"10.1109/TMRB.2025.3573390","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573390","url":null,"abstract":"Objective: This paper proposes a low-cost real-time navigation system to assist a surgeon in placing external ventricular drains. Methods: In our approach, the base of an articulated arm coordinate measuring machine is bolted to the patient’s skull, and a graphical user interface quickly guides the operator through the image registration and 3D navigation to place an external ventricular drain at a desired target specified relative to preoperative imaging. The method can be employed in workflows with and without fiducials embedded in the preoperative imaging. Results: The proposed system is evaluated using precise registration instruments, human phantom models, and ex vivo ovine models, demonstrating less than 2 mm of error with fiducials and less than 4 mm of error without fiducials. Conclusion: The registration procedure takes less than one minute and can be performed intuitively by a single operator without an assistant. Significance: Our proposed system enables real-time image-guided navigation to be used in bedside external ventricular drain placement, with potential to expand access to this procedure.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1087-1098"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11015586","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887828","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3573416
Tzu-Cheng Hsu;Ming-Chih Ho;Cheng-Wei Chen
This study introduces the Laparoscopic Assistive Robotic Manipulator (LapARM), designed to address limitations in current robotic laparoscope holders. LapARM features a compact 4-degree-of-freedom (4-DoF) design achieved through parallel and telescopic mechanisms, synthesized to navigate spatial interference challenges with the human surgeon during surgical operations. Additionally, it improves image stability when zooming with an oblique-viewing scope by developing a custom laparoscope integrated with an embedded distance sensor, allowing the LapARM to dynamically adjust the scope’s orientation during zooming, ensuring that the imaged object remains centered in the image throughout the zooming process. Furthermore, an eye tracker provides surgeons with a contactless interface for intuitive solo control of the laparoscope via head movements. Experimental results validate LapARM’s effective scope maneuvering for laparoscopic procedures. User studies show that its head movement-based control significantly reduces completion time and user workload, contributing to the success of minimally invasive surgeries.
{"title":"Laparoscopic Assistive Robotic Manipulator (LapARM): Mechanical Design and Contactless Interface for Oblique-Viewing Scope Maneuvers","authors":"Tzu-Cheng Hsu;Ming-Chih Ho;Cheng-Wei Chen","doi":"10.1109/TMRB.2025.3573416","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573416","url":null,"abstract":"This study introduces the Laparoscopic Assistive Robotic Manipulator (LapARM), designed to address limitations in current robotic laparoscope holders. LapARM features a compact 4-degree-of-freedom (4-DoF) design achieved through parallel and telescopic mechanisms, synthesized to navigate spatial interference challenges with the human surgeon during surgical operations. Additionally, it improves image stability when zooming with an oblique-viewing scope by developing a custom laparoscope integrated with an embedded distance sensor, allowing the LapARM to dynamically adjust the scope’s orientation during zooming, ensuring that the imaged object remains centered in the image throughout the zooming process. Furthermore, an eye tracker provides surgeons with a contactless interface for intuitive solo control of the laparoscope via head movements. Experimental results validate LapARM’s effective scope maneuvering for laparoscopic procedures. User studies show that its head movement-based control significantly reduces completion time and user workload, contributing to the success of minimally invasive surgeries.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1062-1072"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887831","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}
Electrical stimulation-based therapies are vital in managing post-spinal cord injury complications, particularly during physical rehabilitation. However, the nonlinear muscle response to electrical stimuli and the subjective, physiological variability make it challenging to predict stimulation levels for precise limb movements. The electromechanical delay (EMD), corresponding to the lag between electrical stimulation and muscle actuation, also alleviates rehabilitation outcomes. We propose a dynamic linearization-based sliding mode controller with Smith predictor configuration, compensating for EMD and regulating limb movement using electrical stimulation. Unlike model-based approaches, the proposed controller relies solely on real-time input/output data, eliminating the need for complex system modelling. Experiments with thirteen healthy and two spinal cord-injured participants demonstrated a root mean square error in the range of 2.31° to 8.63° and 1.22° to 3.21° in stimulus-assisted trajectory tracking and disturbance rejection scenarios, respectively. The proposed controller significantly outperformed (Man-Whitney U Test, p¡0.05) the conventional dynamic linearization-based sliding mode controller with an average (SD) RMSE improvement of 2.13°(0.96°). Additionally, the results indicate the robust performance of the proposed controller during impulsive disturbances during seated knee flexion and extension tasks. The proposed controller may potentially eliminate the need for extensive mathematical modelling of the subject while giving excellent trajectory-tracking performance.
{"title":"Electromechanical Delay Compensation in Neuromuscular Electrical Stimulation via a Data-Driven Approach: Validation in Spinal Cord Injury Patients","authors":"Alif T.;Sirsendu Sekhar Mishra;Kanwaljeet Garg;Deepak Joshi","doi":"10.1109/TMRB.2025.3573415","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573415","url":null,"abstract":"Electrical stimulation-based therapies are vital in managing post-spinal cord injury complications, particularly during physical rehabilitation. However, the nonlinear muscle response to electrical stimuli and the subjective, physiological variability make it challenging to predict stimulation levels for precise limb movements. The electromechanical delay (EMD), corresponding to the lag between electrical stimulation and muscle actuation, also alleviates rehabilitation outcomes. We propose a dynamic linearization-based sliding mode controller with Smith predictor configuration, compensating for EMD and regulating limb movement using electrical stimulation. Unlike model-based approaches, the proposed controller relies solely on real-time input/output data, eliminating the need for complex system modelling. Experiments with thirteen healthy and two spinal cord-injured participants demonstrated a root mean square error in the range of 2.31° to 8.63° and 1.22° to 3.21° in stimulus-assisted trajectory tracking and disturbance rejection scenarios, respectively. The proposed controller significantly outperformed (Man-Whitney U Test, p¡0.05) the conventional dynamic linearization-based sliding mode controller with an average (SD) RMSE improvement of 2.13°(0.96°). Additionally, the results indicate the robust performance of the proposed controller during impulsive disturbances during seated knee flexion and extension tasks. The proposed controller may potentially eliminate the need for extensive mathematical modelling of the subject while giving excellent trajectory-tracking performance.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"1186-1200"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891148","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 : 2025-03-26DOI: 10.1109/TMRB.2025.3553221
Rafael Perez-San Lazaro;Rita Q. Fuentes-Aguilar;Isaac Chairez
Exoskeletons used for rehabilitation must operate together with the patient to adapt to the biomechanical-inspired movements of the regular human gait cycle rather than operate by following a predefined trajectory without considering the human-robot interaction effects. This work presents the assessment of a lower limb exoskeleton whose motion is performed according to a collaborative approach given the movements of the human user and the relative force concerning the exoskeleton structure. The Opensim™ software serves to define the force and position reference trajectories to follow during the gait cycle, which serves as a reference for the hybrid control. These forces and movements are compared to the results of a virtual model that considers the interaction between the user and the exoskeleton in two possible scenarios. The first scenario contemplates the implementation of a position controller to generate interaction-independent movement of the exoskeleton. The second scenario considers the force exerted by the exoskeleton on the patient to trigger a force-based controller after trespassing a predefined value. This leads to a hybrid control scheme, which considers the position restrictions in the closed-loop feedback control strategy. Using this approach, the exoskeleton can collaborate actively with the user and provide motion as required, responding to position-controlled motion if the user is not opposed to the exoskeleton motion. This novel strategy permits the evaluation of a hybrid position-force controller for wearing the active orthosis. Numeric simulations show the performance of the proposed system. These outcomes confirm the supposed advantages of the proposed controller.
{"title":"Human-Robot Cooperative Adaptive Reinforcement Constraint Control for a Lower Limb Rehabilitation Exoskeleton Based on User’s Movement Intention","authors":"Rafael Perez-San Lazaro;Rita Q. Fuentes-Aguilar;Isaac Chairez","doi":"10.1109/TMRB.2025.3553221","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3553221","url":null,"abstract":"Exoskeletons used for rehabilitation must operate together with the patient to adapt to the biomechanical-inspired movements of the regular human gait cycle rather than operate by following a predefined trajectory without considering the human-robot interaction effects. This work presents the assessment of a lower limb exoskeleton whose motion is performed according to a collaborative approach given the movements of the human user and the relative force concerning the exoskeleton structure. The Opensim™ software serves to define the force and position reference trajectories to follow during the gait cycle, which serves as a reference for the hybrid control. These forces and movements are compared to the results of a virtual model that considers the interaction between the user and the exoskeleton in two possible scenarios. The first scenario contemplates the implementation of a position controller to generate interaction-independent movement of the exoskeleton. The second scenario considers the force exerted by the exoskeleton on the patient to trigger a force-based controller after trespassing a predefined value. This leads to a hybrid control scheme, which considers the position restrictions in the closed-loop feedback control strategy. Using this approach, the exoskeleton can collaborate actively with the user and provide motion as required, responding to position-controlled motion if the user is not opposed to the exoskeleton motion. This novel strategy permits the evaluation of a hybrid position-force controller for wearing the active orthosis. Numeric simulations show the performance of the proposed system. These outcomes confirm the supposed advantages of the proposed controller.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 2","pages":"607-620"},"PeriodicalIF":3.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084737","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 : 2025-03-23DOI: 10.1109/TMRB.2025.3573068
S. Arastehfar;A. Jalalian;I. Gibson;F. E. H. Tay;G. Liu
Little attention has been paid to how scoliosis movements deviate from intact spines and the consequent response to surgical instrumentation. Embedding such deviations into scoliosis simulation models can significantly improve their predictive capability for surgical outcome and to mitigate complication risks and thus bring more satisfaction to patients and clinicians. Scoliosis models are mainly intact spine models adapted by merely adjusting model parameters to produce scoliotic-like asymmetry, overlooking that the scoliosis condition results in significant deviations of movements. Thus, these adapted models might provide misleading predictive information. This paper aims to uncover the behaviors emerging out of scoliotic spine movements for simulation. A multibody model with micro-scale motion segments was utilized to study movement of nine adolescent idiopathic scoliosis patients. Statistical analysis was used to identify the shared movement behavior and to test their significance in terms of occurrence and their effects on the simulation results and prediction accuracy. Four movement behaviors were uncovered: (1) negligible change of spinal length, (2) bounded rotational displacements, (3) unilateral rotational displacements of certain vertebrae, (4) negligible rotational displacements around inflection vertebrae. Simulation results were improved significantly by incorporating these findings: location and orientation errors of vertebrae from $2.9pm 2$ .5 mm to $1.1pm 0$ .4 mm and $2.0pm 1.3^{circ }$ to $1.0pm 0.4^{circ }$ , respectively, approximation error of spine curvature from $2.1pm 2$ .0 mm to $0.6pm 0$ .3 mm. Therefore, scoliosis exhibits unique movements, and it is essential that scoliosis models comply for improved predictive capability.
{"title":"Anatomically Accurate Modeling of Spine Movement to Depict the Scoliosis Condition","authors":"S. Arastehfar;A. Jalalian;I. Gibson;F. E. H. Tay;G. Liu","doi":"10.1109/TMRB.2025.3573068","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3573068","url":null,"abstract":"Little attention has been paid to how scoliosis movements deviate from intact spines and the consequent response to surgical instrumentation. Embedding such deviations into scoliosis simulation models can significantly improve their predictive capability for surgical outcome and to mitigate complication risks and thus bring more satisfaction to patients and clinicians. Scoliosis models are mainly intact spine models adapted by merely adjusting model parameters to produce scoliotic-like asymmetry, overlooking that the scoliosis condition results in significant deviations of movements. Thus, these adapted models might provide misleading predictive information. This paper aims to uncover the behaviors emerging out of scoliotic spine movements for simulation. A multibody model with micro-scale motion segments was utilized to study movement of nine adolescent idiopathic scoliosis patients. Statistical analysis was used to identify the shared movement behavior and to test their significance in terms of occurrence and their effects on the simulation results and prediction accuracy. Four movement behaviors were uncovered: (1) negligible change of spinal length, (2) bounded rotational displacements, (3) unilateral rotational displacements of certain vertebrae, (4) negligible rotational displacements around inflection vertebrae. Simulation results were improved significantly by incorporating these findings: location and orientation errors of vertebrae from <inline-formula> <tex-math>$2.9pm 2$ </tex-math></inline-formula>.5 mm to <inline-formula> <tex-math>$1.1pm 0$ </tex-math></inline-formula>.4 mm and <inline-formula> <tex-math>$2.0pm 1.3^{circ }$ </tex-math></inline-formula> to <inline-formula> <tex-math>$1.0pm 0.4^{circ }$ </tex-math></inline-formula>, respectively, approximation error of spine curvature from <inline-formula> <tex-math>$2.1pm 2$ </tex-math></inline-formula>.0 mm to <inline-formula> <tex-math>$0.6pm 0$ </tex-math></inline-formula>.3 mm. Therefore, scoliosis exhibits unique movements, and it is essential that scoliosis models comply for improved predictive capability.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"7 3","pages":"985-992"},"PeriodicalIF":3.8,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887798","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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