Article
Chemistry, Multidisciplinary
Sofia Straudi, Marco Tramontano, Emanuele Francesco Russo, Luca Perrero, Michela Agostini, Marialuisa Gandolfi, Irene Aprile, Matteo Paci, Emanuela Casanova, Dario Marino, Giuseppe La Rosa, Federica Bressi, Silvia Sterzi, Daniele Giansanti, Alberto Battistini, Sandra Miccinilli, Serena Filoni, Monica Sicari, Salvatore Petrozzino, Claudio Marcello Solaro, Stefano Gargano, Paolo Benanti, Paolo Boldrini, Donatella Bonaiuti, Enrico Castelli, Francesco Draicchio, Vincenzo Falabella, Silvia Galeri, Francesca Gimigliano, Mauro Grigioni, Stefano Mazzoleni, Stefano Mazzon, Franco Molteni, Maurizio Petrarca, Alessandro Picelli, Federico Posteraro, Michele Senatore, Giuseppe Turchetti, Giovanni Morone
Summary: This review systematically reports the evidence on the clinical applications and functional recovery effects of robotic-assisted arm training (RAT) in patients with Multiple Sclerosis (PwMS). The study found that RAT improved shoulder range of motion, handgrip strength, and proximal arm impairment, as well as manual dexterity, arm function, and daily life use. However, the high clinical heterogeneity of treatment programs and the variety of robot devices call for standardization of intervention types in future studies. Overall, robot-assisted treatment appears safe and useful for improving manual dexterity and movement execution quality in PwMS with moderate to severe disability. Further studies with larger sample sizes and rigorous methodologies are needed to draw definitive conclusions.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Maoqin Li, Jiaji Zhang, Guokun Zuo, Guang Feng, Xueliang Zhang
Summary: This paper proposes a new structure for upper limb rehabilitation robots and introduces an adaptive assistance control strategy that can provide different assistance to patients during rehabilitation training. The experiments demonstrate that this control strategy can effectively enhance patients' rehabilitation outcomes.
Article
Clinical Neurology
Takashi Takebayashi, Kayoko Takahashi, Satoru Amano, Masahiko Gosho, Masahiro Sakai, Koichi Hashimoto, Kenji Hachisuka, Yuki Uchiyama, Kazuhisa Domen
Summary: This study found that robotic self-training did not improve upper-extremity function more than conventional self-training, but it may be effective when combined with conventional therapy in certain populations.
Article
Multidisciplinary Sciences
Adriana Cancrini, Paolo Baitelli, Matteo Lavit Nicora, Matteo Malosio, Alessandra Pedrocchi, Alessandro Scano
Summary: This study investigates the effect of robot assistance on task performance and muscle synergies in healthy individuals. The results show that assistance improves task performance but has limited impact on muscle synergies.
Article
Medicine, General & Internal
Rocco Salvatore Calabro, Giovanni Morone, Antonino Naro, Marialuisa Gandolfi, Vitalma Liotti, Carlo D'aurizio, Sofia Straudi, Antonella Focacci, Sanaz Pournajaf, Irene Aprile, Serena Filoni, Claudia Zanetti, Maria Rosaria Leo, Lucia Tedesco, Vincenzo Spina, Carmelo Chisari, Giovanni Taveggia, Stefano Mazzoleni, Nicola Smania, Stefano Paolucci, Marco Franceschini, Donatella Bonaiuti
Summary: Robot-assisted upper limb training may improve outcomes for stroke patients, with exoskeleton robots shown to be more effective in the subacute phase and end-effector robots more effective in the chronic phase. Additional pragmatic and high methodological studies are needed to confirm the effectiveness of these devices.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Automation & Control Systems
Ran Jiao, Wenjie Liu, Ramy Rashad, Jianfeng Li, Mingjie Dong, Stefano Stramigioli
Summary: A novel end-effector bilateral rehabilitation robotic system (EBReRS) is developed for upper limb rehabilitation of patients with hemiplegia, providing simulations of multiple bimanual coordinated training modes, showing potential for application in home rehabilitation.
Article
Engineering, Biomedical
Christian Tamantini, Francesca Cordella, Clemente Lauretti, Francesco Scotto di Luzio, Benedetta Campagnola, Laura Cricenti, Marco Bravi, Federica Bressi, Francesco Draicchio, Silvia Sterzi, Loredana Zollo
Summary: This paper presents a psychophysiological-aware control strategy for upper limb robot-aided orthopedic rehabilitation, which can adapt treatments to patients' needs. The strategy has three main features: i) generating point-to-point trajectories inside an adaptable workspace, ii) providing assistance in guiding patients' limbs, allowing them to move with spatial and temporal autonomy, and iii) tuning control parameters based on patients' kinematics performance and psychophysiological state. The strategy has been validated in a clinical setting and shown to have a positive impact on participants, leading to improved motor functions.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Shuang Li, Zhanli Wang, Zaixiang Pang, Moyao Gao, Zhifeng Duan
Summary: This paper presents an assisted upper limb rehabilitation robot for stroke patients in the middle and late stages of rehabilitation. By completing the adduction and abduction motion of the shoulder joint in one step, the robot saves time and improves the efficiency of rehabilitation training. The robot's kinematics model is established, and simulation and workspace analysis are conducted.
Article
Geriatrics & Gerontology
Congcong Huo, Zhifang Sun, Gongcheng Xu, Xinglou Li, Hui Xie, Ying Song, Zengyong Li, Yonghui Wang
Summary: This study focused on the brain functional responses induced by robotic-assisted therapy (RAT) in stroke patients with different degrees of motor impairment. The results showed that patients with severe impairment had extensive cortical response during RAT, while patients with moderate impairment had limited cortical response. Adjusting training intensity according to the brain functional state is crucial for patients with moderate impairment. The assessment of brain functional response using functional near-infrared spectroscopy (fNIRS) is important for customization of appropriate therapy protocols.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Pei-Cheng Shih, Christopher J. Steele, Dennis Hoepfel, Toni Muffel, Arno Villringer, Bernhard Sehm
Summary: The study investigated how patients with left and right hemispheric stroke are differentially affected in individual-limb control and inter-limb coordination during bilateral movements. Results showed that RHS patients exhibited greater impairment in both individual- and inter-limb control during anti-phase movements, while LHS patients showed greater impairment in individual-limb control during in-phase movements alone. Additionally, LHS patients demonstrated a swap in hand dominance during in-phase movements.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2023)
Article
Automation & Control Systems
Chen Wang, Liang Peng, Zeng-Guang Hou
Summary: In this article, a control framework for robot-assisted motor learning is proposed, which focuses on detecting human intention, generating reference trajectories, and modifying robotic assistance. The results showed that the difficulty level of reference trajectories can be modulated according to the intention of the patients, and the robotic assistance can be optimized flexibly during trajectory tracking tasks.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Guang Feng, Jiaji Zhang, Guokun Zuo, Maoqin Li, Dexin Jiang, Lei Yang
Summary: This paper proposes a dual-modal hybrid self-switching control strategy (DHSS) to determine the exercise mode of patients in rehabilitation training. The experimental results demonstrate that DHSS is effective in assisting patients with training independently without therapists.
Article
Medicine, Research & Experimental
Mary Ellen Stoykov, Olivia M. Biller, Alexandra Wax, Erin King, Jacob M. Schauer, Louis F. Fogg, Daniel M. Corcos
Summary: This study investigates the effects of bilateral motor priming in combination with task-specific training on motor impairment, bimanual motor function, and interhemispheric inhibition in stroke patients. The study uses a randomized controlled trial design with an experimental group receiving bilateral motor priming and a control group receiving a different priming technique. Outcome measures are collected at multiple time points.
Review
Rehabilitation
Xinwei Yang, Xiubo Shi, Xiali Xue, Zhongyi Deng
Summary: This study systematically evaluated the effect of robot-assisted training on upper limb function recovery in stroke patients and found that it significantly improved upper limb motor function and activities of daily life. Subgroup analysis also showed significant differences in motor function and functional recovery for acute and chronic stroke patients.
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
(2023)
Article
Engineering, Mechanical
Xinbo Chen, Shuai Zhang, Kaibin Cao, Chunjie Wei, Wumian Zhao, Jiantao Yao
Summary: A novel soft wearable upper limb rehabilitation robot with reinforced soft pneumatic actuators (RSPAs) has been developed. This robot allows for rehabilitation training that enhances flexibility, comfort, and safety.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Chunsheng He, Kang Huang, Han Zhao, Yunjun Zheng, Shengquan Xie
Summary: This article presents a novel optimal constraint-following controller for uncertain mechanical systems, which guarantees some deterministic performances. By employing the Udwadia-Kalaba theory, a robust controller with tunable control gains is designed. An iterative feedback tuning method is introduced for optimizing the proposed controller, achieving a balance between system performance and control cost.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Automation & Control Systems
Jie Zuo, Quan Liu, Wei Meng, Qingsong Ai, Sheng Q. Xie
Summary: This study proposes a novel high-order modified dynamic model of the pneumatic muscle actuator (PMA) based on its physical properties and working principle to accurately describe its nonlinear, time-varying, and hysteresis characteristics. A global fast terminal sliding mode controller with a modified model-based radial basis function (RBF) neural network disturbance compensator (RBF-GFTSMC) is designed to address the PMA's nonlinear hysteresis problem in high-frequency movements. Experimental studies on a designed PMA platform show that the RBF-GFTSMC exhibits superior trajectory tracking performance and disturbance compensation capability under wide-ranging frequencies and external loads, making it potentially suitable for achieving precise control of PMA-actuated robots.
Article
Robotics
Kun Qian, Zhenhong Li, Zhiqiang Zhang, Guqiang Li, Sheng Quan Xie
Summary: This letter proposes a data-driven adaptive iterative learning controller (DDAILC) for a compliant ankle rehabilitation robot (CARR) with the use of four pneumatic muscle (PM) actuators. The DDAILC utilizes compact form dynamic linearization (CFDL) with estimated pseudo-partial derivative (PPD) to overcome the nonlinearity of the PM actuators. Experimental studies demonstrate significant improvement in tracking performance compared to other data-driven methods.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Engineering, Biomedical
Yihui Zhao, Zhenhong Li, Zhiqiang Zhang, Kun Qian, Shengquan Xie
Summary: This paper proposes an electromyography (EMG)-driven musculoskeletal model to estimate the wrist joint kinematics involving wrist flexion/extension and radial/ulnar deviation. The proposed approach computes the internal force/joint torque and integrates the wrist kinematics using the forward dynamics. Experiments demonstrate that the proposed model-based approach provides high estimation accuracy in contralateral case with mean coefficient of determination of 0.86 and 0.82 for wrist flexion/extension and radial/ulnar deviation, respectively.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Review
Engineering, Electrical & Electronic
Nian Peng, Wei Meng, Qin Wei, Qingsong Ai, Quan Liu, Shengquan Xie
Summary: With the increasing demand for rehabilitation of the elderly population and patients with limb injuries, it is essential to develop new wearable health monitoring systems and assistive rehabilitation equipment. Optical fiber sensing, with its advantages of lightweight, anti-electromagnetic interference, higher strain and elastic limit, safety, and dependableness, has been significantly used in engineering prospecting, building structure monitoring, and medical and health fields. However, the discussion and summary of the key theories and technologies of optical fiber sensing in medical rehabilitation are still insufficient. This review details the different types of optical fiber sensing mechanisms and devices, as well as the measurement of physical parameters and application examples in the field of medical rehabilitation. It also discusses the challenges and provides a research direction for the future realization of flexible, comfortable, safe, stable monitoring of human biomechanical parameters and real-time precise control of rehabilitation equipment.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Jie Zuo, Quan Liu, Wei Meng, Qingsong Ai, Sheng Quan Xie
Summary: A novel event-triggered adaptive hybrid torque-position control scheme is proposed in this article for a developed ankle rehabilitation robot. The scheme can adaptively adjust the assistive torque according to the patient's recovery state and correct the robotic assistance output based on patient's performance, achieving fast trajectory tracking and adjustable assistance capacity.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Yihui Zhao, Kun Qian, Sheng Bo, Zhiqiang Zhang, Zhenhong Li, Gu-Qiang Li, Abbas Ali Dehghani-Sanij, Sheng Quan Xie
Summary: This article proposes an adaptive cooperative control strategy for a wrist exoskeleton based on a real-time joint impedance estimation approach. By interpreting the underlying transformation in the muscular and skeletal systems, the proposed approach estimates the motion intention and the joint impedance of a human subject simultaneously without additional calibration procedures. Results indicate the proposed method outperforms other training protocols and enhances the training effectiveness and the interaction safety.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Engineering, Multidisciplinary
Asim Ghaffar, Abbas A. Dehghani-Sanij, Sheng Quan Xie, Abdullah Tahir, Awais Hafeez
Summary: The selection of an actuation system for assistive robotic exoskeletons involves careful consideration of various design factors, including lightweight and power-efficient requirements. This paper explores the exploitation of actuation redundancy in a study comparing the design optimization of rigid and elastic systems. A multi-factor optimization technique is developed for a redundant elastic actuation system, evaluating different actuator choices to determine the optimal motor and transmission system combination. The results show that the optimal redundant actuation system significantly reduces power requirements, with the variable parallel elastic actuators (V-PEA) outperforming variable series elastic actuators (V-SEA) in the case study.
JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS
(2023)
Article
Automation & Control Systems
Shangliang Wu, Guangyu Liu, Yanxin Zhang, Anke Xue
Summary: The application of artificial intelligence tools has led to the development of collision detectors with better computational efficiency than kinematics-and-geometry based collision detectors (KCD) for improving robot motion planning strategies. However, the new detectors lack accuracy in certain cases. To enhance accuracy, a trade-off between efficiency and accuracy is needed. We propose a novel compound collision detector (CCD) that modifies the planners of rapidly-exploring random tree (RRT) to improve the classical probabilistic collision detector (PCD). This CCD consists of an exact collision detector (ECD), an inference collision detector (ICD), and a strategy to determine the use of ECD or ICD based on certain conditions. Experimental evaluation on a Kinova Jaco assistive robotic arm demonstrates improved accuracy with a slight reduction in speed compared to PCD, making the CCD a promising tool in robot motion planning.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2023)
Review
Multidisciplinary Sciences
Bo Sheng, Jianyu Zhao, Yanxin Zhang, Shengquan Xie, Jing Tao
Summary: Recently, various hand rehabilitation systems, especially commercial devices, have been developed for stroke patients. A systematic review of articles from 2010 to 2022 was conducted to explore the existing commercial training systems and evaluate their clinical effectiveness. The review found that most devices were effective in improving hand function, and game-based training protocols were appealing in reducing boredom. However, technical drawbacks and the lack of commercially available game-based training protocols specifically targeting hand rehabilitation were identified.
Review
Engineering, Industrial
Tiejun Ma, Yanxin Zhang, Sang D. Choi, Shuping Xiong
Summary: The development of industrial exoskeletons aims to reduce physical demands and ergonomic issues in the workplace. Modelling is considered a powerful tool for the design and evaluation of these exoskeletons, providing a safe and economical alternative to empirical methods. This systematic review demonstrates that existing modelling methods can evaluate the biomechanical and physiological effects of industrial exoskeletons, but fail to cover certain evaluation metrics supported by experimental assessments.
APPLIED ERGONOMICS
(2023)
Proceedings Paper
Automation & Control Systems
Bo Sheng, Jianyu Zhao, Junjun Zheng, Chaoqun Duan, Sheng Quan Xie, Jing Tao
Summary: Currently, there is a lack of objective and precise evaluation methods for assessing hand function in stroke patients. To address this, we proposed a new assessment method that utilizes hand movement data collected from the Leap motion device. By analyzing and ranking the selected sensitive metrics, we were able to determine the most sensitive kinematic metrics to distinguish differences in hand function between normal individuals and stroke patients. The experimental results showed that the proposed method was effective, scientifically objective, and could assist with the evaluation of hand function in stroke-induced hemiplegia.
2023 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, AIM
(2023)
Article
Engineering, Electrical & Electronic
Jie Zhang, Yihui Zhao, Tianzhe Bao, Zhenhong Li, Kun Qian, Alejandro F. Frangi, Sheng Quan Xie, Zhi-Qiang Zhang
Summary: This article proposes an active physics-informed deep transfer learning framework to enhance the dynamic tracking capability of the musculoskeletal model on unseen data. The framework embeds physics-based domain knowledge into the data-driven model as soft constraints and fine-tunes subject-specific inference parameters. Experimental results demonstrate the effectiveness and generalization of the proposed framework.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Automation & Control Systems
Qingsong Ai, Zemin Liu, Wei Meng, Quan Liu, Sheng Q. Xie
Summary: This paper proposes an uncertainty compensated high-order adaptive iterative learning controller (UCHAILC) to address the uncertainties and disturbances faced by upper limb rehabilitation robots. By converting the nonlinear system into a dynamic linearization model and using a high-order learning scheme to update parameters, the proposed controller enables high-performance trajectory tracking for the robot.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Review
Health Care Sciences & Services
Bo Sheng, Zheyu Wang, Yujiao Qiao, Sheng Quan Xie, Jing Tao, Chaoqun Duan
Summary: This review provides a quantitative analysis of digital twins (DT) in healthcare, focusing on specific study contents, research focus, and trends. It reveals that the research predominantly concentrates on technology development and application scenarios, highlighting the significance and potential of DT in healthcare.
