A Novel sEMG Triggered FES-Hybrid Robotic Lower Limb Rehabilitation System for Stroke Patients

Petersen, Inga Lypunova; Nowakowska, Weronika; Ulrich, Christian; Struijk, Lotte N. S. Andreasen

doi:10.1109/tmrb.2020.3019081

Cited by 17 publications

(9 citation statements)

References 32 publications

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“…The degree of contraction represents the amount of muscle strength generated during the rehabilitation training. Since the rectus femoris muscle is directly involved in the knee and hip joint flexion and extension, we placed an EMG sensor close to the rectus femoris muscle area of the experimenter, as shown in Figure 13a, to collect the muscles' surface EMG signals for knee and hip flexion and extension separately [31][32][33].…”

Section: Methodsmentioning

confidence: 99%

Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance

et al. 2022

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More hemiplegia patients tend to use equipment for rehabilitation training due to the lack of physical therapists and the low effect of manual training. Nowadays, lower limb rehabilitation training devices for patients in grade 2 of the Medical Research Council (MRC-2) scale are still scarce and have some issues of poor autonomy and cannot relieve the muscle weakness of patients. To address these problems, a prototype based on gravity balance was designed with the combination of springs and linkages to enable patients to passively experience the rehabilitation training in the state of balancing the gravity of lower limbs. The motion of the mechanism was analyzed to obtain the functional relation between the motor rotation angle and the joints’ angle. Based on the principle of constant potential energy, a gravity balance mathematical model of the device was established, analyzed, and simulated. Moreover, through the training experiment, the results show that when subjects in three different weights were trained under the rehabilitation device with and without gravity balance, the required torques of the motor and EMG signal strength of the knee and hip joints decreased by a degree of significance, which verified the effectiveness of the device’s gravity balancing characteristics for MRC-2 patients.

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Section: Methodsmentioning

confidence: 99%

Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance

et al. 2022

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“…In [56], the use of an exoskeleton in the form of a glove for hand movements is described. The proposal in [57] combines the generation of electrical impulses to stimulate the exercises provided by an active robot on the patient's legs. Passive mobilisation using robotics is addressed in [58].…”

Section: Integrating Proposals From the Rehabilitation Areamentioning

confidence: 99%

Smart Health-Enhanced Early Mobilisation in Intensive Care Units

Ferre

Batista

Solanas

et al. 2021

Sensors

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Critically ill patients that stay in Intensive Care Units (ICU) for long periods suffer from Post-Intensive Care Syndrome or ICU Acquired Weakness, whose effects can decrease patients’ quality of life for years. To prevent such issues and aiming at shortening intensive care treatments, Early Mobilisation (EM) has been proposed as an encouraging technique: the literature includes numerous examples of the benefits of EM on the prevention of post-operative complications and adverse events. However, the appropriate application of EM programmes entails the use of scarce resources, both human and technical. Information and Communication Technologies can play a key role in reducing cost and improving the practice of EM. Although there is rich literature on EM practice and its potential benefits, there are some barriers that must be overcome, and technology, i.e., the use of sensors, robotics or information systems, can contribute to that end. This article reviews the literature and analyses on the use of technology in the area of EM, and moreover, it proposes a smart health-enhanced scenario.

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“…Electromyography (EMG) signal offers a promising solution given its ability to decode motion intention at the spinal cord level and can be detected prior to the initiation of movement [5], [6]. State-of-the-art EMG-based approaches mainly employ regression algorithms that map EMG signals to the motion intention through numerical functions [7].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Cooperative Control Strategy for a Wrist Exoskeleton Using Model-Based Joint Impedance Estimation

Zhao

Qian

Sheng

et al. 2023

IEEE/ASME Trans. Mechatron.

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Wrist rehabilitation exoskeletons have gained much attention over the last decades, striving to restore motor functions for patients with neuromuscular disorders. Electromyography (EMG) signal has been employed to estimate the motion intention to achieve interactive training schemes. However, it is a challenging task to estimate the joint impedance in realtime, as it is a crucial parameter for control of exoskeletons. This paper proposes an adaptive cooperative control strategy for a wrist exoskeleton based on a real-time joint impedance estimation approach. By explicitly 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 and regulates the training trajectories and assistance accordingly. Results indicate the proposed method outperforms other training protocols, including the trajectory tracking control and the fixed cooperative control. The proposed control strategy provides an additional 66.25% motion deviation when estimated joint torque increases 12.36%, which enhances the training effectiveness and the interaction safety and promotes subjects' active engagement.

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A Novel sEMG Triggered FES-Hybrid Robotic Lower Limb Rehabilitation System for Stroke Patients

Cited by 17 publications

References 32 publications

Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance

Model Analysis and Experimental Study of Lower Limb Rehabilitation Training Device Based on Gravity Balance

Smart Health-Enhanced Early Mobilisation in Intensive Care Units

Adaptive Cooperative Control Strategy for a Wrist Exoskeleton Using Model-Based Joint Impedance Estimation

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