Article
Mathematics
Md. Mahmudur Rahman, Kok Beng Gan, Noor Azah Abd Aziz, Audrey Huong, Huay Woon You
Summary: In physical therapy, motion-tracking devices using cameras and inertial measurement units (IMUs) are commonly used. This study developed a 3D rigid body to estimate elbow joint angles using three IMUs and a fusion algorithm incorporating the Madgwick filter. The proposed algorithm exhibited higher accuracy and stability compared to the IMU manufacturer's algorithm, with a maximum RMSE of 0.46 degrees.
Article
Automation & Control Systems
Chang He, Xiao-Wei Xu, Xiong-Fei Zheng, Cai-Hua Xiong, Quan-Lin Li, Wen-Bin Chen, Bai-Yang Sun
Summary: This article presents a computational framework for generating anthropomorphic reaching movement with human motion characteristics, imitating the mechanism in the control and realization of human upper limb motions. By establishing a continuous task parametric model using Gaussian mixture regression method, the proposed method achieves smooth trajectory and natural obstacle avoidance in anthropomorphic motion generation.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Chemistry, Analytical
Afonso Castro, Filipe Silva, Vitor Santos
Summary: Human-Robot Collaboration is an important concept for improving human life, aiming to achieve physical interaction and effective task completion. While significant research has been conducted in this field, there are still specific issues that require further investigation.
Article
Automation & Control Systems
Robin Pellois, Olivier Bruls
Summary: This paper proposes an inertial human motion tracking method for robot programming by demonstration. It introduces a new element called "heading reset" to address the issue of magnetic disturbances that prevent the use of magnetometer. The paper also presents specific procedures and algorithms for estimating human arm trajectory and transforming reference frames, and experimental tests validate the effectiveness of the method.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2022)
Article
Automation & Control Systems
Wei Qian, Junbei Liao, Linjun Lu, Letian Ai, Miao Li, Xiaohui Xiao, Zhao Guo
Summary: This article introduces a lightweight, comfortable, cable-driven, and compliant upper limb rehabilitation exoskeleton robot. It features modular series elastic actuators that provide controlled torque for each active joint, with Bowden cables transferring torque to distal joints. The system has a large range of motion and can provide accurate torque control for stroke patients' requirements. A comprehensive rehabilitation strategy, including robot-in-charge mode and human-in-charge mode, was developed for different recovery stages. Finally, a virtual reality training system was developed to assist subjects in efficient upper limb rehabilitation.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Robotics
Shuaishuai Han, Haoping Wang, Haoyong Yu
Summary: The article proposes an assist-as-needed method for upper limb rehabilitation robots driven by series elastic actuators (SEAs) based on human-robot interaction evaluation. The method provides stable human-robot interaction through the design of a controller and the application of an iterative learning algorithm, as well as periodically adjusting the intensity of robotic assistance according to the evaluation results. The method adapts to different participants' abilities and provides adaptive assistance when a specific trainee tries to change their participation.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
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
Automation & Control Systems
Yi Sun, Weitian Wang, Yi Chen, Yunyi Jia
Summary: This article proposes a dual-input deep learning approach to assist humans in assembly tasks and utilizes online automated data labeling to reduce the training efforts.
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
Automation & Control Systems
Silvia Proia, Raffaele Carli, Graziana Cavone, Mariagrazia Dotoli
Summary: The fourth industrial revolution, also known as Industry 4.0, is reshaping the way individuals live and work, with a substantial impact on the manufacturing sector. Collaborative robotics is the key enabling technology behind Industry 4.0 and is evolving as a fundamental pillar of Industry 5.0. The main goals of human-robot collaboration in the industrial setting are to improve employee safety and well-being, while increasing profitability and productivity.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Health Care Sciences & Services
Qing Sun, Shuai Guo, Leigang Zhang
Summary: This study proposed a new analysis index VMEIV for the kinematic dexterity of human-robot interaction, which was validated through simulation and experimental results, providing a reference for the training trajectory selection of rehabilitation robots.
TECHNOLOGY AND HEALTH CARE
(2021)
Article
Automation & Control Systems
Qingcong Wu, Ying Chen
Summary: This paper proposes a new variable admittance time-delay control strategy based on human stiffness estimation for improving the effectiveness of robot-assisted cooperative rehabilitation training. The control strategy utilizes a time-delay approximator to estimate external disturbances and modeling errors, a sliding mode admittance controller to achieve desired admittance characteristics, and an iterative optimization algorithm to estimate human arm stiffness and adjust human-robot interaction compliance. Experimental investigations involving ten subjects are conducted to validate the feasibility of the proposed control scheme, showing its potential to satisfy the specific training requirements of patients with different weakness levels and promote the effectiveness of robot-assisted training.
Article
Chemistry, Analytical
Yupeng Zou, Xiangshu Wu, Baolong Zhang, Qiang Zhang, Andong Zhang, Tao Qin
Summary: This paper studies the stiffness characteristics of the parallel cable-driven upper limb rehabilitation robot (PCUR) and summarizes the motion laws of the moving platform under different stiffness and external forces through the establishment of a simulation model and analysis of data.
Article
Multidisciplinary Sciences
Arsha Ali, Hebert Azevedo-Sa, Dawn M. Tilbury, Lionel P. Robert
Summary: This paper proposes a novel task allocation method for heterogeneous human-robot teams based on artificial trust. By learning agent capabilities and considering task rewards and costs, this method enables teams to maximize their joint performance.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
Yongbai Liu, Keping Liu, Gang Wang, Zhongbo Sun, Long Jin
Summary: This study proposes an upper limb-exoskeleton coupling dynamics model based on human active motion intention to overcome human-robot confrontation and promote active and natural human-robot interaction control. Using the Elman neural network model, the human active motion intention is estimated. A discrete-time controller based on a noise-tolerant zeroing neurodynamic model is proposed to construct the discrete-time human-robot interaction control system. The performance of the system with different controllers is compared and analyzed under ideal and non-ideal conditions using performance indicators such as root mean square errors and coefficient of determination.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Elisa Panero, Ugo Dimanico, Carlo Alberto Artusi, Laura Gastaldi
Summary: The study evaluated the biomechanical analysis of Pisa syndrome, finding significant lateral bending of the trunk in patients, influencing ground reaction forces and limb movements, with differences in proprioception and correction abilities among patients.
Article
Chemistry, Multidisciplinary
Elisa Panero, Valentina Agostini, Laura Gastaldi
Summary: The aim of this study was to compare the throwing kinematics in three different types of shots in water-polo. The results showed significant changes in throwing velocity and shoulder angle during the passing-feint shot. The passing-spontaneous shot led to an increase in players' throwing precision.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Biomedical
Elisa Digo, Elisa Panero, Valentina Agostini, Laura Gastaldi
Summary: The increasing average age highlights the importance of gait analysis in the elderly population. This study compared three IMU setups and algorithms with a gold standard optoelectronic system to estimate gait parameters in healthy elderly subjects. The IMU placed on the trunk showed the best performance, indicating its potential for accurate gait analysis in non-physiological patterns.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE
(2023)
Article
Chemistry, Analytical
Daniele Borzelli, Stefano Pastorelli, Andrea d'Avella, Laura Gastaldi
Summary: This study presents a biomechanical model-based approach to estimate limb stiffness of a multi-joint, multi-muscle system from muscle activations. By projecting the muscle activation vector onto the null space of the linear mapping, the proposed method approximates the generated stiffness. The model provides a good approximation that can be directly implemented in wearable myoelectric controlled devices without additional calibrations.
Review
Chemistry, Multidisciplinary
Elisa Panero, Rossella D'Alessandro, Ilaria Cavallina, Chiara Davico, Tiziana Mongini, Laura Gastaldi, Federica Ricci
Summary: In clinical practice and research, wearable devices, particularly Inertial Measurement Units (IMUs), have been used for the assessment of neuromuscular and movement disorders through objective measures. This review focuses on the use of IMUs for evaluating meaningful outcome measures in individuals with Duchenne muscular dystrophy (DMD). The analysis highlights the regulatory recognition of Stride Velocity 95th Centile as a new endpoint in therapeutic trials for DMD, as well as the limited use of IMUs in non-ambulatory patients and the challenges in identifying reliable outcome measures for the upper body.
APPLIED SCIENCES-BASEL
(2023)
Article
Biotechnology & Applied Microbiology
Daniele Borzelli, Sergio Gurgone, Paolo De Pasquale, Nicola Lotti, Andrea d'Avella, Laura Gastaldi
Summary: This study compared the EMG-to-force mapping estimation performed with standard multiple linear regression and three other algorithms. The results showed that linear regression with anatomical constraints was the best solution.
BIOENGINEERING-BASEL
(2023)
Proceedings Paper
Computer Science, Theory & Methods
Elisa Digo, Laura Gastaldi, Mattia Antonelli, Stefano Pastorelli, Andrea Cereatti, Marco Caruso
Summary: This study validated an IMU-based method for real-time estimation of upper limb kinematics during typical gestures required for industrial assembly tasks. Through the use of IMUs fixed on the upper body of six participants, shoulder and elbow angles were successfully assessed. The results confirmed the suitability of the proposed method for human-robot collaboration in an industrial context.
3RD INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Valeria Rosso, Laura Gastaldi, Stefano Pastorelli
Summary: This study identifies impulsive movements during human-robot interaction by using an inertial sensor and calculating four features based on gesture kinematics. The results show that calculating the features with shorter epoch duration improves the detection of impulsive gestures.
PROCEEDINGS OF I4SDG WORKSHOP 2021: IFTOMM FOR SUSTAINABLE DEVELOPMENT GOALS
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Elisa Digo, Laura Gastaldi, Mattia Antonelli, Valerio Cornagliotto, Stefano Pastorelli
Summary: This study developed a setup for the quantitative evaluation of the force effectiveness and symmetry during upper limbs kranking. The results suggest that the developed setup is adequate to efficaciously identify possible alterations of performance parameters during upper limbs kranking.
PROCEEDINGS OF I4SDG WORKSHOP 2021: IFTOMM FOR SUSTAINABLE DEVELOPMENT GOALS
(2022)
Proceedings Paper
Engineering, Biomedical
Elisa Panero, Elisa Digo, Virginia Ferrarese, Ugo Dimanico, Laura Gastaldi
Summary: The study focused on developing a multi-segments kinematic model of the human spine and validating it during gait trials. Results emphasized the importance of spine segmentation, major angular contributions of spinal regions during gait, and the reliability of the proposed custom model.
2021 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS (IEEE MEMEA 2021)
(2021)
Proceedings Paper
Engineering, Biomedical
Elisa Panero, Elisa Digo, Ugo Dimanico, Carlo Alberto Artusi, Maurizio Zibetti, Laura Gastaldi
Summary: This study evaluated the effects of different DBS stimulation frequencies on gait parameters in PD patients, revealing a connection with age and pathology. The Harmonic Ratio (HR) was found suitable for depicting gait characteristics and monitoring subjective adaptation to DBS stimulation frequency. Poincare analysis of vertical acceleration signal showed greater data dispersion in PD patients compared to healthy subjects, with negligible differences between stimulation frequencies.
2021 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS (IEEE MEMEA 2021)
(2021)
Proceedings Paper
Engineering, Biomedical
Elisa Digo, Elisa Panero, Valentina Agostini, Laura Gastaldi
Summary: The study compared the effects of three different MIMU set-ups and correlated algorithms on single-task and dual-task walking of elderly people, finding significant impacts of cognition on walking speed and temporal parameters, and significant differences in the detection of gait stance and swing phases among the MIMU configurations.
2021 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS (IEEE MEMEA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Mattia Antonelli, Elisa Digo, Stefano Pastorelli, Laura Gastaldi
Summary: The study focused on classifying industrial tasks based on acceleration signals of human upper limbs, using two MIMUs to detect peaks and classify gestures. Results showed that placing at least one MIMU on the upper arm or forearm is suitable for achieving good recognition performances in collaborative robotics contexts.
PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (ICINCO)
(2021)