Relevant bibliographies by topics / EMG-based control strategy

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'EMG-based control strategy'

Author: Grafiati
Published: 8 September 2021
Last updated: 29 July 2025

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Journal articles on the topic "EMG-based control strategy"

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Azad Feyzullayev, Aynur Jabiyeva, Azad Feyzullayev, Aynur Jabiyeva. "STRATEGY FOR REDUCING MUSCLE FATIGUE IN THE USE OF BIOELECTRIC PROSTHESIS BASED ON ELECTROMYOGRAPHIC ANALYSIS." Caucasus-Economic and Social Analysis Journal of Southern Caucasus 63, no. 01 (2025): 25–36. https://doi.org/10.36962/cesajsc63012025-25.

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Muscle fatigue is characterised by a decrease in the ability of muscles to perform required functions, which is accompanied by accumulation of metabolites, changes in ionic balance and electrical properties of muscle tissue. These physiological changes lead to marked transformations of electromyographic (EMG) signals, including a shift of their spectrum to lower frequencies. Such changes affect the quality of signal recognition and control accuracy of bioelectric prostheses, since most myoelectric control algorithms are based on the stability of spectral and amplitude characteristics of EMG si
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Cirelli, Gianmarco, Christian Tamantini, Luigi Pietro Cordella, and Francesca Cordella. "A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis." Robotics 12, no. 6 (2023): 152. http://dx.doi.org/10.3390/robotics12060152.

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Alleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solution to overcome such limitations. In this paper, a novel semiautonomous control system (SCS) for wrist–hand prostheses using a computer vision system (CVS) is proposed and validated. The SCS integrates object detection, grasp selection, and wrist orientation estimation algorithms. By combining CVS
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Chen, Lingling, Xiaotian Liu, Bokai Xuan, Jie Zhang, Zuojun Liu, and Yan Zhang. "Selection of EMG Sensors Based on Motion Coordinated Analysis." Sensors 21, no. 4 (2021): 1147. http://dx.doi.org/10.3390/s21041147.

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The intelligent prosthesis driven by electromyography (EMG) signal provides a solution for the movement of the disabled. The proper position of EMG sensors can improve the prosthesis’s motion recognition ability. To exert the amputee’s action-oriented ability and the prosthesis’ control ability, the EMG spatial distribution and internal connection of the prosthetic wearer is analyzed in three kinds of movement conditions: appropriate angle, excessive angle, and angle too small. Firstly, the correlation characteristics between the EMG channels are analyzed by mutual information to construct a m
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LIU, JIE, XIAOYAN LI, CHRISTINA MARCINIAK, WILLIAM ZEV RYMER, and PING ZHOU. "EXTRACTION OF NEURAL CONTROL COMMANDS USING MYOELECTRIC PATTERN RECOGNITION: A NOVEL APPLICATION IN ADULTS WITH CEREBRAL PALSY." International Journal of Neural Systems 24, no. 07 (2014): 1450022. http://dx.doi.org/10.1142/s0129065714500221.

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This study investigates an electromyogram (EMG)-based neural interface toward hand rehabilitation for patients with cerebral palsy (CP). Forty-eight channels of surface EMG signals were recorded from the forearm of eight adult subjects with CP, while they tried to perform six different hand grasp patterns. A series of myoelectric pattern recognition analyses were performed to identify the movement intention of each subject with different EMG feature sets and classifiers. Our results indicate that across all subjects high accuracies (average overall classification accuracy > 98%) can be achi
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Wang, Qiang, Chunjie Chen, Xinxing Mu, et al. "A Wearable Upper Limb Exoskeleton System and Intelligent Control Strategy." Biomimetics 9, no. 3 (2024): 129. http://dx.doi.org/10.3390/biomimetics9030129.

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Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality
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Sriram, Girish, Alex Jensen, and Steve C. Chiu. "Smart Prosthetic Hand with Object Slippage Detection, Measurement, and Control." International Journal of Handheld Computing Research 5, no. 3 (2014): 25–48. http://dx.doi.org/10.4018/ijhcr.2014070102.

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The human hand along with its fingers possess one of the highest numbers of nerve endings in the human body. It thus has the capacity for the richest tactile feedback for positioning capabilities. This article shares a new technique of controlling slippage. The sensing system used for the detection of slippage is a modified force sensing resistor (FSR®). The control system is a fuzzy logic control algorithm with multiple rules that is designed to be processed on a mobile handheld computing platform and integrated/working alongside a traditional Electromyography (EMG) or Electroencephalography
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Li, Shunchong, Jiayuan He, Xinjun Sheng, Honghai Liu, and Xiangyang Zhu. "Synergy-Driven Myoelectric Control for EMG-Based Prosthetic Manipulation: A Case Study." International Journal of Humanoid Robotics 11, no. 02 (2014): 1450013. http://dx.doi.org/10.1142/s0219843614500133.

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The paper proposes a synergy-based myoelectric control strategy for prosthetic hands. Synergy is first reviewed in the context of hand movement, then postural synergy-based proportional and simultaneous control has been introduced to prosthetic manipulation via the principal component analysis (PCA) framework. Experiments have been comprehensively carried out on lab-developed prosthetic hand called SJU-5 to evaluate the proposed method. It is evident that the synergy driven myoelectric control achieves the targeted objectives and performs well on the SJU-5 prosthetic hand.
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Secciani, N., M. Bianchi, A. Ridolfi, B. Allotta, F. Gerli, and F. Vannetti. "Development and preliminary testing of an EMG-based control strategy for a hand exoskeleton." Gait & Posture 66 (October 2018): S35. http://dx.doi.org/10.1016/j.gaitpost.2018.07.155.

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Asai, Yoshiyuki, Shota Tateyama, and Taishin Nomura. "Learning an Intermittent Control Strategy for Postural Balancing Using an EMG-Based Human-Computer Interface." PLoS ONE 8, no. 5 (2013): e62956. http://dx.doi.org/10.1371/journal.pone.0062956.

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Arora, A. S. "Modified adaptive resonance theory based control strategy for EMG operated prosthesis for below-elbow amputee." Journal of Medical Engineering & Technology 31, no. 3 (2007): 191–201. http://dx.doi.org/10.1080/03091900500481036.

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Dissertations / Theses on the topic "EMG-based control strategy"

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Moreira, Luís Carlos Rodrigues. "Assist-as-needed EMG-based control strategy for wearable powered assistive devices." Master's thesis, 2019. http://hdl.handle.net/1822/69984.

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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)<br>Robotic-based gait rehabilitation and assistance using Wearable Powered Assistive Devices (WPADs), such as orthosis and exoskeletons, has been growing in the rehabilitation area to recover and augment the motor function of neurologically impaired subjects. These WPADs should provide a personalized assistance, since physical condition and muscular fatigue modify from patient to patient. In this field, electromyography (EMG) signals have been used to control WPADs given their ability to inf
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Book chapters on the topic "EMG-based control strategy"

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Li, Guanglin, Oluwarotimi Williams Samuel, Chuang Lin, Mojisola Grace Asogbon, Peng Fang, and Paul Oluwagbengba Idowu. "Realizing Efficient EMG-Based Prosthetic Control Strategy." In Advances in Experimental Medicine and Biology. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2050-7_6.

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Wu, Changcheng, Aiguo Song, and Peng Ji. "A Control Strategy for Prosthetic Hand Based on Attention Concentration and EMG." In Intelligent Robotics and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22879-2_28.

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Secciani, Nicola, Matteo Bianchi, Alessandro Ridolfi, Federica Vannetti, and Benedetto Allotta. "Assessment of a Hand Exoskeleton Control Strategy Based on User’s Intentions Classification Starting from Surface EMG Signals." In Biosystems & Biorobotics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01887-0_85.

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Li, Zihao, Jianmin Li, and Lizhi Pan. "An IMU and EMG-Based Simultaneous and Proportional Control Strategy of 3-DOF Wrist and Hand Movements." In Intelligent Robotics and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13835-5_39.

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Suryanarayanan Srikanth, Reddy Narender P., and Gupta Vineet. "An Intelligent System with EMG-Based Joint Angle Estimation for Telemanipulation." In Studies in Health Technology and Informatics. IOS Press, 1996. https://doi.org/10.3233/978-1-60750-873-1-546.

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Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle
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Conference papers on the topic "EMG-based control strategy"

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Pitzalis, Roberto F., Nicholas Cartocci, Christian Di Natali, Darwin G. Caldwell, Giovanni Berselli, and Jesús Ortiz. "Development of a ML-Control Strategy for a Wrist Exoskeleton Based on EMG and Force Measurements with Sensor Strategy Optimisation." In 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob). IEEE, 2024. http://dx.doi.org/10.1109/biorob60516.2024.10719824.

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Chen, Diansheng, Meng Ning, Benguang Zhang, and Guang Yang. "Control strategy of the lower-limb exoskeleton based on the EMG signals." In 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2014. http://dx.doi.org/10.1109/robio.2014.7090701.

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Delgado, Pablo, Nathan Gonzalez, and Yimesker Yihun. "Integration of EMG-Based Learning and Sliding Mode Control for an Exoskeleton Assist-as-Needed Support System." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-91305.

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Abstract In this study, an electromyography (EMG) signal-based learning is integrated with a Sliding-Mode Control (SMC) law for an effective human-exoskeleton synergy. A modified Recursive Newton-Euler Algorithm (RNEA) with SMC was used to determine and control the inverse dynamics of a highly nonlinear 4 degree-of-freedom exoskeleton designed for the automation of upper-limp therapeutic exercises. The exoskeleton position and velocity, along with the raw EMG signal from the bicep Brachii muscle were used as a feedback. The root mean square (RMS) values of targeted muscles EMG are tracked in a
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Bernal-Torres, Mario G., Hugo I. Medellín-Castillo, and Juan C. Arellano-González. "Development of an Active Biomimetic-Controlled Transfemoral Knee Prosthesis." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-67211.

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Commercial available knee prostheses are still limited because most of them comprise passive elements that store and deliver energy during the gait cycle, but without providing additional energy. This inability to provide additional energy affects the performance of passive prostheses, which in some cases demands up to 60% of additional metabolic energy to perform a gait cycle. Recent research works have focused on the design of active knee prostheses, including the development and implementation of control strategies such as electromyographic (EMG) signals. However, the results of such implem
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