A Study on Human Upper-Limb Muscles Activities during Daily Upper-Limb Motions (original) (raw)
Related papers
2021
Stroke is a significant affliction that can affect people with varying degrees of severity. One of the most common consequences of stroke is the impairment of the muscular motor function to some degree with two-thirds of the patients being affected by upper-limb paralysis. For those cases, the most effective forms of regaining muscular motor function are through rehabilitation therapy, traditionally this must be done in a clinical environment. Developments in robotics, batteries and electronics have made accessible the prototyping, production, and utilization of exoskeleton type devices technically adapted for personal and residential rehabilitation. This paper presents and discusses the results of EMG signals from upper limb of brachial biceps muscle, obtained from a cohort of healthy volunteers. The methodology for testing is presented and explained, additionally, a preliminary discussion is made on the obtained data. Some control considerations, variables and methods are also presented and discussed.
A study on muscle activities through surface EMG for lower limb exoskeleton controller
Proceedings - 2013 IEEE Conference on Systems, Process and Control, ICSPC 2013, 2013
The motion of human body is complex but perfect and integrated effort of brain, nerves and muscles. Exoskeleton is a promising idea for human rehabilitation of the lower limb that is weak enough to move. EMG signal contains the information of human movement and can be considered as one of the most powerful input to exoskeleton controller. In this research, the activity of the lower limb muscles that are responsible for human sit to stand and stand to sit movement has been studied. In this regard, the activities of three muscles viz. rectus femoris, vastus lateralis and biceps femoris have been observed and recorded to perceive their activation pattern. The experimental results show that the maximum voltage of vastus lateralis at activation moment is greater or equal to +0.1 mV or lesser or equal to -0.1 mVduring sit to stand and stand to sit movement whereas same throughput was found for biceps femoris during sit to stand and for rectus femoris during stand to sit movement only. © 2013 IEEE. http://ieeexplore.ieee.org/ielx7/6720515/6735086/06735124.pdf?tp=&arnumber=6735124&isnumber=6735086
CLASSIFICATION OF ARM MOVEMENT BASED ON UPPER LIMB MUSCLE SIGNAL FOR REHABILITATION DEVICE
Rehabilitation device is used as an exoskeleton for people who experience limb failure. Arm rehabilitation device may ease the rehabilitation programme for those who suffer arm dysfunctional. The device used to facilitate the tasks of the program should improve the electrical activity in the motor unit by minimising the mental effort of the user. Electromyography (EMG) is the techniques to analyse the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person are failed to contract the muscle for movements. To prevent the muscles from paralysis becomes spasticity or flaccid the force of movements has to minimise the mental efforts. To minimise the used of cerebral strength, analysis on EMG signals from normal people are conducted before it can be implement in the device. The signals are collect according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The implementation of EMG signals is to set the movements' pattern of the arm rehabilitation device. The filtered signal further the process by extracting the features as follows; Standard Deviation(STD), Mean Absolute Value(MAV), Root Mean Square(RMS), Zero Crossing(ZCS) and Variance(VAR). The extraction of EMG data is to have the reduced vector in the signal features for minimising the signals error than can be implement in classifier. The classification of features is by SOM-Toolbox using MATLAB. The features extraction of EMG signals is classified into several degree of arm movement visualize in U-Matrix form.
Control of upper-limb power-assist exoskeleton based on motion intention recognition
2011 IEEE International Conference on Robotics and Automation, 2011
ü ü ü ü Recognizing the user motion intention plays an important role in the study of power-assist robots. An intention-guided control strategy is proposed for the upper-limb power-assist exoskeleton. A force sensor system comprised of force sensing resistors (FSRs) is designed to online estimate the motion intention of user upper limb. A new concept called "intentional reaching direction (IRD)" is proposed to quantitatively describe this intention. Both the state model and the observation model of IRD are obtained by enumerating the upper limb behavior modes and analyzing the relationship between the measured force signals and the motion intention. Based on these two models, the IRD can be online inferred by applying filtering technology. Guided by the estimated IRD, an admittance control strategy is assumed to control the motions of three DC motors in the joints of the robotic arm. The effectiveness of the proposed approaches is finally confirmed by the experiments on a 3-DOF robotic exoskeleton.
Quantitative assessment of the EMG patterns of upper arm muscles during robotic rehabilitation
Human upper limb is involved in many daily human activities. The muscle activities during basic and daily upper-limb motions are an important area of research in rehabilitation field in order to evaluate the recovery of patients affected by congenital or acquired brain injury. Much better results in sensorimotor and cognitive processes are promised by the emerging robot-mediated therapy. Although the shoulder is the most complex joint in the body, both as to freedom range and for the musculartendon structure, not so many research devices have been proposed to study its movements and no study has proposed standardized electromyographic assessment during robot-assisted reaching movements of the upper arm. This study aimed to develop a quantitative assessment of the electromyographic pattern of the arm's muscles involved in reaching movements robot-assisted by means of indices used to describe effectively the main features of the pattern in five normal subjects to implement rehabilitation strategies patients oriented.
Robotics
This article sought to address issues related to human-robot cooperation tasks focusing especially on robotic operation using bio-signals. In particular, we propose to develop a control scheme for a robot arm based on electromyography (EMG) signal that allows a cooperative task between humans and robots that would enable teleoperations. A basic framework for achieving the task and conducting EMG signals analysis of the motion of upper limb muscles for mapping the hand motion is presented. The objective of this work is to investigate the application of a wearable EMG device to control a robot arm in real-time. Three EMG sensors are attached to the brachioradialis, biceps brachii, and anterior deltoid muscles as targeted muscles. Three motions were conducted by moving the arm about the elbow joint, shoulder joint, and a combination of the two joints giving a two degree of freedom. Five subjects were used for the experiments. The results indicated that the performance of the system had...
Estimating arm motion and force using EMG signals: On the control of exoskeletons
2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008
There is a great effort during the last decades towards building robotic devices that are worn by humans. These devices, called exoskeletons, are used mainly for support and rehabilitation, as well as for augmentation of human capabilities. Providing a control interface for exoskeletons, that would guarantee comfort and safety, as well as efficiency and robustness, is still an issue. This paper presents a methodology for estimating human arm motion and force exerted, using electromyographic (EMG) signals from muscles of the upper limb. The proposed method is able to estimate motion of the human arm as well as force exerted from the upper limb to the environment, when the motion is constrained. Moreover, the method can distinguish the cases in which the motion is constrained or not (i.e. exertion of force versus free motion) which is of great importance for the control of exoskeletons. Furthermore, the method provides a continuous profile of estimated motion and force, in contrast to other methods used in the literature that can only detect initiation of movement or intention of force. The system is tested in an orthosis-like scenario, during planar movements, through various experiments. The experimental results prove the system efficiency, making the proposed methodology a strong candidate for an EMG-based control scheme applied in robotic exoskeletons.
The Control Concept for Upper Limb Exoskeleton
2021
Robotic exoskeletons inspired by the animal’s external covering are wearable systems that enhance human power, motor skills, or support the movement. The main difficulty, apart from the mechanical structure design, is the development of an exoskeleton control system, as it should recognize the movement intended by the user and assist in its execution. This work is devoted to the exoskeleton of the upper limbs that supports movement. The method of controlling the exoskeleton by means of electromyograms (EMG) was presented. EMG is a technique for recording and assessing the electrical activity produced by skeletal muscles. The main advantage of EMG based control is the ability to forecast intended motion, even if the user is unable to generate it. This work aims to define strategies for controlling the exoskeleton of the upper limb in children suffering from neuromuscular diseases. Such diseases gradually reduce the mobility of the lower and upper limbs. These children are wheelchair ...
Personalizing the control law of an upper-limb exoskeleton using EMG signal
2021
Implementing an intuitive control law for an upper-limb exoskeleton dedicated to force augmentation is a challenging issue in the field of human-robot collaboration. The goal of this study is to adapt an EMG-based control system to a user based on individual caracteristics. To this aim, a method has been designed to tune the parameters of control using objective criteria, improving user’s feedback. The user’s response time is used as an objective value to adapt the gain of the controller. The proposed approach was tested on 10 participants during a lifting task. Two different conditions have been used to control the exoskeleton: with a generic gain and with a personalized gain. EMG signals was captured on five muscles to evaluate the efficiency of the conditions and the user’s adaptation. Results showed a statistically significant reduction of mean muscle activity of the deltoid between the beginning and the end of each situation (28.6 ± 13.5% to 17.2 ± 7.3% of Relative Maximal Cont...