Posts Tagged EMG

[WEB SITE] How Virtual Avatars Help Stroke Patients Improve Motor Function

At USC, Dr. Sook-Lei Liew is testing whether watching a virtual avatar that moves in response to brain commands can activate portions of the brain damaged by stroke.
Dr. Sook-Lei Liew (Photo: Nate Jensen)

Photo: Nate Jensen

I am hooked up to a 16-channel brain machine interface with 12 channels of EEG on my head and ears and four channels of electromyography (EMG) on my arms. An Oculus Rift occludes my vision.

Two inertial measurement units (IMU) are stuck to my wrists and forearms, tracking the orientation of my arms, while the EMG monitors my electrical impulses and peripheral nerve activity.

Dr. Sook-Lei Liew, Director of USC’s Neural Plasticity and Neurorehabilitation Laboratory, and Julia Anglin, Research Lab Supervisor and Technician, wait to record my baseline activity and observe a monitor with a representation of my real arm and a virtual limb. I see the same image from inside the Rift.

“Ready?” asks Dr. Liew. “Don’t move—or think.”

I stay still, close my eyes, and let my mind go blank. Anglin records my baseline activity, allowing the brain-machine interface to take signals from the EEG and EMG, alongside the IMU, and use that data to inform an algorithm that drives the virtual avatar hand.

“Now just think about moving your arm to the avatar’s position,” says Dr. Liew.

I don’t move a muscle, but think about movement while looking at the two arms on the screen. Suddenly, my virtual arm moves toward the avatar appendage inside the VR world.

VR rehab at USC

Something happened just because I thought about it! I’ve read tons of data on how this works, even seen other people do it, especially inside gaming environments, but it’s something else to experience it for yourself.

“Very weird isn’t it?” says David Karchem, one of Dr. Liew’s trial patients. Karchem suffered a stroke while driving his car eight years ago, and has shown remarkable recovery using her system.

“My stroke came out of the blue and it was terrifying, because I suddenly couldn’t function. I managed to get my car through an intersection and call the paramedics. I don’t know how,” Karchem says.

He gets around with a walking stick today, and has relatively normal function on the right side of his body. However, his left side is clearly damaged from the stroke. While talking, he unwraps surgical bandages and a splint from his left hand, crooked into his chest, to show Dr. Liew the progress since his last VR session.

As a former software engineer, Karchem isn’t fazed by using advanced technology to aid the clinical process. “I quickly learned, in fact, that the more intellectual and physical stimulation you get, the faster you can recover, as the brain starts to fire. I’m something of a lab rat now and I love it,” he says.

REINVENT Yourself

Karchem is participating in Dr. Liew’s REINVENT (Rehabilitation Environment using the Integration of Neuromuscular-based Virtual Enhancements for Neural Training) project, funded by the American Heart Association, under a National Innovative Research Grant. It’s designed to help patients who have suffered strokes reconnect their brains to their bodies.

VR rehab at USC (Photo: Nate Jensen)“My PhD in Occupational Science, with a concentration in Cognitive Neuroscience, focused on how experience changes brain networks,” explains Dr. Liew. “I continued this work as a Postdoctoral Fellow at the National Institute of Neurological Disorders and Stroke at the National Institutes of Health, before joining USC, in my current role, in 2015.

“Our main goal here is to enhance neural plasticity or neural recovery in individuals using noninvasive brain stimulation, brain-computer interfaces and novel learning paradigms to improve patients’ quality of life and engagement in meaningful activities,” she says.

Here’s the science bit: the human putative mirror neuron system (MNS) is a key motor network in the brain that is active both when you perform an action, like moving your arm, and when you simply watch someone else—like a virtual avatar—perform that same action. Dr. Liew hypothesizes that, for stroke patients who can’t move their arm, simply watching a virtual avatar that moves in response to their brain commands will activate the MNS and retrain damaged or neighboring motor regions of the brain to take over the role of motor performance. This should lead to improved motor function.

“In previous occupational therapy sessions, we found many people with severe strokes got frustrated because they didn’t know if they were activating the right neural networks when we asked them to ‘think about moving’ while we physically helped them to do so,” Dr. Liew says. “If they can’t move at all, even if the right neurological signals are happening, they have no biological feedback to reinforce the learning and help them continue the physical therapy to recover.”

For many people, the knowledge that there’s “intent before movement”—in that the brain has to “think” about moving before the body will do so, is news. We also contain a “body map” inside our heads that predicts our spacetime presence in the world (so we don’t bash into things all the time and know when something is wrong). Both of these brain-body elements face massive disruption after a stroke. The brain literally doesn’t know how to help the body move.

What Dr. Liew’s VR platform has done is show patients how this causal link works and aid speedier, and less frustrating, recovery in real life.

From the Conference Hall to the Lab

She got the idea while geeking out in Northern California one day.

“I went to the Experiential Technology Conference in San Francisco in 2015, and saw demos of intersections of neuroscience and technology, including EEG-based experiments, wearables, and so on. I could see the potential to help our clinical population by building a sensory-visual motor contingency between your own body and an avatar that you’re told is ‘you,’ which provides rewarding sensory feedback to reestablish brain-body signals.

“Inside VR you start to map the two together, it’s astonishing. It becomes an automatic process. We have seen that people who have had a stroke are able to ’embody’ an avatar that does move, even though their own body, right now, cannot,” she says.

VR rehab at USC

Dr. Liew’s system is somewhat hacked together, in the best possible Maker Movement style; she built what didn’t exist and modified what did to her requirements.

“We wanted to keep costs low and build a working device that patients could actually afford to buy. We use Oculus for the [head-mounted display]. Then, while most EEG systems are $10,000 or more, we used an OpenBCI system to build our own, with EMG, for under $1,000.

“We needed an EEG cap, but most EEG manufacturers wanted to charge us $200 or more. So, we decided to hack the rest of the system together, ordering a swim cap from Amazon, taking a mallet and bashing holes in it to match up where the 12 positions on the head electrodes needed to be placed (within the 10-10 international EEG system). We also 3D print the EEG clips and IMU holders here at the lab.

VR rehab at USC

“For the EMG, we use off-the-shelf disposable sensors. This allows us to track the electromyography, if they do have trace muscular activity. In terms of the software platform, we coded custom elements in C#, from Microsoft, and implemented them in the Unity3D game engine.”

Dr. Liew is very keen to bridge the gap between academia and the tech industry; she just submitted a new academic paper with the latest successful trial results from her work for publication. Last year, she spoke at SXSW 2017 about how VR affects the brain, and debuted REINVENT at the conference’s VR Film Festival. It received a “Special Jury Recognition for Innovative Use of Virtual Reality in the Field of Health.”

Going forward, Dr. Liew would like to bring her research to a wider audience.

RELATED

“I feel the future of brain-computer interfaces splits into adaptive, as with implanted electrodes, and rehabilitative, which is what we work on. What we hope to do with REINVENT is allow patients to use our system to re-train their neural pathways, [so they] eventually won’t need it, as they’ll have recovered.

“We’re talking now about a commercial spin-off potential. We’re able to license the technology right now, but, as researchers, our focus, for the moment, is in furthering this field and delivering more trial results in published peer-reviewed papers. Once we have enough data we can use machine learning to tailor the system precisely for each patient and share our results around the world.”

If you’re in L.A., Dr. Liew and her team will be participating in the Creating Reality VR Hackathon from March 12-15 at USC. Details here.

via How Virtual Avatars Help Stroke Patients Improve Motor Function | News & Opinion | PCMag.com

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[Abstract+References] Forced Use of the Paretic Leg Induced by a Constraint Force Applied to the Nonparetic Leg in Individuals Poststroke During Walking

Background. Individuals with stroke usually show reduced muscle activities of the paretic leg and asymmetrical gait pattern during walking. Objective. To determine whether applying a resistance force to the nonparetic leg would enhance the muscle activities of the paretic leg and improve the symmetry of spatiotemporal gait parameters in individuals with poststroke hemiparesis. Methods. Fifteen individuals with chronic poststroke hemiparesis participated in this study. A controlled resistance force was applied to the nonparetic leg using a customized cable-driven robotic system while subjects walked on a treadmill. Subjects completed 2 test sections with the resistance force applied at different phases of gait (ie, early and late swing phases) and different magnitudes (10%, 20%, and 30% of maximum voluntary contraction [MVC] of nonparetic leg hip flexors). Electromyographic (EMG) activity of the muscles of the paretic leg and spatiotemporal gait parameters were collected. Results. Significant increases in integrated EMG of medial gastrocnemius, medial hamstrings, vastus medialis, and tibialis anterior of the paretic leg were observed when the resistance was applied during the early swing phase of the nonparetic leg, compared with baseline. Additionally, resistance with 30% of MVC induced the greatest level of muscle activity than that with 10% or 20% of MVC. The symmetry index of gait parameters also improved with resistance applied during the early swing phase. Conclusion. Applying a controlled resistance force to the nonparetic leg during early swing phase may induce forced use on the paretic leg and improve the spatiotemporal symmetry of gait in individuals with poststroke hemiparesis.

References

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via Forced Use of the Paretic Leg Induced by a Constraint Force Applied to the Nonparetic Leg in Individuals Poststroke During WalkingNeurorehabilitation and Neural Repair – Chao-Jung Hsu, Janis Kim, Elliot J. Roth, William Z. Rymer, Ming Wu, 2017

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[Abstract] A Longitudinal EMG Study of Complex Upper-limb Movements in Post-stroke Therapy. 1: Heterogeneous EMG Changes despite Consistent Improvements in Clinical Assessments

Post-stroke weakness on the more-affected side may arise from reduced corticospinal drive, disuse muscle atrophy, spasticity, and abnormal co-ordination. This study investigated changes in muscle activation patterns to understand therapy-induced improvements in motor-function in chronic stroke compared to clinical assessments, and to identify the effect of motor-function level on muscle activation changes.

Electromyography (EMG) was recorded from 5 upper-limb muscles on the more-affected side of 24 patients during early- and late-therapy sessions of an intensive 14-day program of Wii-based Movement Therapy, and for a subset of 13 patients at 6-month follow-up. Patients were classified according to residual voluntary motor capacity with low, moderate or high motor-function. The area under the curve was calculated from EMG amplitude and movement duration. Clinical assessments of upper-limb motor-function pre- and post-therapy included the Wolf Motor Function Test, Fugl-Meyer Assessment and Motor Activity Log Quality of Movement scale.

Clinical assessments improved over time (p<0.01) with an effect of motor-function level (p<0.001). The pattern of EMG change by late-therapy was complex and variable, with differences between patients with low compared to moderate or high motor-function. The area under the curve (p=0.028) and peak amplitude (p=0.043) during Wii-tennis backhand increased for patients with low motor-function whereas EMG decreased for patients with moderate and high motor-function. The reductions included: movement duration during Wii-golf (p=0.048, moderate; p=0.026, high), and Wii-tennis backhand (p=0.046, moderate; p=0.023, high) and forehand (p=0.009, high); and the area under the curve during Wii-golf (p=0.018, moderate) and Wii-baseball (p=0.036, moderate). For the pooled data over time there was an effect of motor-function (p=0.016) and an interaction between time and motor-function (p=0.009) for Wii-golf movement duration. Wii-baseball movement duration decreased as a function of time (p=0.022). There was an effect on Wii-tennis forehand duration for time (p=0.002) and interaction of time and motor-function (p=0.005); and an effect of motor-function level on the area under the curve (p=0.034) for Wii-golf.

This study demonstrated different patterns of EMG changes according to residual voluntary motor-function levels despite heterogeneity within each level that was not evident following clinical assessments alone. Thus, rehabilitation efficacy might be underestimated by analyses of pooled data.

Source: Frontiers | A Longitudinal EMG Study of Complex Upper-limb Movements in Post-stroke Therapy. 1: Heterogeneous EMG Changes despite Consistent Improvements in Clinical Assessments | Neurology

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[ARTICLE] The effects of training using EMG biofeedback on stroke patients upper extremity functions – Full Text PDF

Abstract

[Purpose] While electromyography (EMG) biofeedback has been recently used in diverse therapeutic interventions for stroke patients, research on its effects has been lacking. Most existing studies are confined to functions
of the lower extremities, and research on upper extremity functional recovery using EMG biofeedback training is limited. Therefore, this study examined the effects of training using EMG biofeedback on stroke patients’
upper extremity functions.

[Subjects and Methods] The subjects of this study included 30 hemiplegia patients whose disease duration was longer than six months. They were randomly divided into a control group (n=15) receiving traditional rehabilitation therapy and an experimental group (n=15) receiving both traditional rehabilitation therapy and training using EMG biofeedback. The program lasted for a total of four weeks. In order to examine the subjects’
functional recovery, the author measured their upper limb function using the Fugl-Meyer Assessment and Manual Function Test, and activities of daily living using the Functional Independence Measure before and after training.

[Results] A comparison of the study groups revealed that those in the experimental group experienced greater improvement in upper extremity function after training in all tests compared to the control group; however, there was no significant difference in terms of the activities of daily living between the two groups. The results of this study were as follows.

[Conclusion] Thus, stroke patients receiving intensive EMG biofeedback showed more significant upper extremity functional recovery than those who only received traditional rehabilitation therapy.
Full Text PDF

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[Abstract] A Longitudinal EMG Study of Complex Upper-limb Movements in Post-stroke Therapy: 2 Changes in Co-ordinated Muscle Activation

Fine motor control is achieved through the co-ordinated activation of groups of muscles, or ‘muscle synergies’. Muscle synergies change after stroke as a consequence of the motor deficit. We investigated the pattern and longitudinal changes in upper-limb muscle synergies during therapy in a largely unconstrained movement in patients with a broad spectrum of post-stroke residual voluntary motor capacity.Electromyography (EMG) was recorded using wireless telemetry from 6 muscles acting on the more-affected upper body in 24 stroke patients at early- and late-therapy during formal Wii-based Movement Therapy sessions, and in a subset of 13 patients at 6-month follow-up. Patients were classified with low, moderate or high motor-function. The Wii-baseball swing was analysed using a non-negative matrix factorisation (NMF) algorithm to extract muscle synergies from EMG recordings based on the temporal activation of each synergy and the contribution of each muscle to a synergy. Motor-function was clinically assessed immediately pre- and post-therapy and at 6-month follow-up using the Wolf Motor Function Test, upper-limb motor Fugl-Meyer Assessment and Motor Activity Log Quality of Movement scale.Clinical assessments and game performance demonstrated improved motor-function for all patients at post-therapy (p0.05). NMF analysis revealed fewer muscle synergies (mean±SE) for patients with low motor-function (3.38±0.2) than those with high motor-function (4.00±0.3) at early-therapy (p=0…

Source: A Longitudinal EMG Study of Complex Upper-limb Movements in Post-stroke Therapy: 2 Changes in Co-ordinated Muscle Activation

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[WEB SITE] One step at a time

IMAGE: DR. KIM (LEFT) WITH DR. SHARMA AND A HYBRID EXOSKELETON PROTOTYPE IN THE NEUROMUSCULAR CONTROL AND ROBOTICS LABORATORY IN THE SWANSON SCHOOL OF ENGINEERING. view more CREDIT: SWANSON SCHOOL OF ENGINEERING

PITTSBURGH (March 7, 2017) … The promise of exoskeleton technology that would allow individuals with motor impairment to walk has been a challenge for decades. A major difficulty to overcome is that even though a patient is unable to control leg muscles, a powered exoskeleton could still cause muscle fatigue and potential injury.

However, an award from the National Science Foundation’s Cyber-Physical Systems (CPS) program will enable researchers at the University of Pittsburgh to develop an ultrasound sensor system at the heart of a hybrid exoskeleton that utilizes both electrical nerve stimulation and external motors.

Principal investigator of the three year, $400,000 award is Nitin Sharma, assistant professor of mechanical engineering and materials science at Pitt’s Swanson School of Engineering. Co-PI is Kang Kim, associate professor of medicine and bioengineering. The Pitt team is collaborating with researchers led by Siddhartha Sikdar, associate professor of bioengineering and electrical and computer engineering at George Mason University, who also received a $400,000 award for the CPS proposal, “Synergy: Collaborative Research: Closed-loop Hybrid Exoskeleton utilizing Wearable Ultrasound Imaging Sensors for Measuring Fatigue.”

This latest funding furthers Dr. Sharma’s development of hybrid exoskeletons that combine functional electrical stimulation (FES), which uses low-level electrical currents to activate leg muscles, with powered exoskeletons, which use electric motors mounted on an external frame to move the wearer’s joints.

“One of the most serious impediments to developing a human exoskeleton is determining how a person who has lost gait function knows whether his or her muscles are fatigued. An exoskeleton has no interface with a human neuromuscular system, and the patient doesn’t necessarily know if the leg muscles are tired, and that can lead to injury,” Dr. Sharma explained. “Electromyography (EMG), the current method to measure muscle fatigue, is not reliable because there is a great deal of electrical “cross-talk” between muscles and so differentiating signals in the forearm or thigh is a challenge.”

To overcome the low signal-to-noise ratio of traditional EMG, Dr. Sharma partnered with Dr. Kim, whose research in ultrasound focuses on analyzing muscle fatigue.

“An exoskeleton biosensor needs to be noninvasive, but systems like EMG aren’t sensitive enough to distinguish signals in complex muscle groups,” Dr. Kim said. “Ultrasound provides image-based, real-time sensing of complex physical phenomena like neuromuscular activity and fatigue. This allows Nitin’s hybrid exoskeleton to switch between joint actuators and FES, depending upon the patient’s muscle fatigue.”

In addition to mating Dr. Sharma’s hybrid exoskeleton to Dr. Kim’s ultrasound sensors, the research group will develop computational algorithms for real-time sensing of muscle function and fatigue. Human subjects using a leg-extension machine will enable detailed measurement of strain rates, transition to fatigue, and full fatigue to create a novel muscle-fatigue prediction model. Future phases will allow the Pitt and George Mason researchers to develop a wearable device for patients with motor impairment.

“Right now an exoskeleton combined with ultrasound sensors is just a big machine, and you don’t want to weigh down a patient with a backpack of computer systems and batteries,” Dr. Sharma said. “The translational research with George Mason will enable us to integrate a wearable ultrasound sensor with a hybrid exoskeleton, and develop a fully functional system that will aid in rehabilitation and mobility for individuals who have suffered spinal cord injuries or strokes.”

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Source: One step at a time | EurekAlert! Science News

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[ARTICLE] Long-Term Plasticity in Reflex Excitability Induced by Five Weeks of Arm and Leg Cycling Training after Stroke – Full Text HTML

Abstract:

Neural connections remain partially viable after stroke, and access to these residual connections provides a substrate for training-induced plasticity. The objective of this project was to test if reflex excitability could be modified with arm and leg (A & L) cycling training. Nineteen individuals with chronic stroke (more than six months postlesion) performed 30 min of A & L cycling training three times a week for five weeks. Changes in reflex excitability were inferred from modulation of cutaneous and stretch reflexes. A multiple baseline (three pretests) within-subject control design was used. Plasticity in reflex excitability was determined as an increase in the conditioning effect of arm cycling on soleus stretch reflex amplitude on the more affected side, by the index of modulation, and by the modulation ratio between sides for cutaneous reflexes. In general, A & L cycling training induces plasticity and modifies reflex excitability after stroke.

1. Introduction

The arms and the legs are coupled in the human nervous system such that activity in the arms affects activity in the legs and vice versa. In quadrupeds, forelimb–hindlimb coordination is well documented and has been attributed to propriospinal linkages between cervical and lumbosacral spinal central pattern-generating networks [1,2,3,4,5,6]. Bipedal human locomotion is likely built upon elements of quadrupedal coordination [2,5], where it involves coordination of all four limbs. Only indirect evidence for quadrupedal locomotor linkages exists, however.
The modulation of reflex amplitudes can be used to probe for changes in interlimb neural activity [4,7]. Investigations of soleus stretch and H-reflex modulation during rhythmic arm movement provide evidence of neuronal coupling between the arms and the legs [2,3,8,9,10]. Examining cutaneous reflexes during rhythmic movements can also probe for interactions between the limbs. In this context, a widespread interlimb network is revealed by the extensive distribution of reflexes across many muscles in both the arms and the legs regardless of which limb is directly stimulated [4,11,12]. In addition, phase-dependent modulation found in muscles of all four limbs during rhythmic movement is suggestive of coupling between segmental spinal networks [12,13,14,15,16]. Regulation of rhythmic arm and leg movement is supported by somatosensory linkages in the form of interlimb reflexes [12,17,18] and neural coupling between lumbar and cervical spinal cord networks [10,19,20,21,22]. …

Figure 1. Illustration of the testing and training protocols. A multiple baseline within-subject control design was used for this study. An A & L cycle ergometer (Sci-Fit Pro 2) was used for training. The setups for stretch reflex and cutaneous reflex testing are shown. Muscles of interest are shown with a gray oval, and electrical stimulation is shown with a black lightning bolt. For the stretch reflex setup, a brief vibration was delivered to the triceps surae tendon and the reflex was recorded from the soleus (SOL) muscle, separately for each side. For the cutaneous reflex setup, simultaneous electrical stimulation was applied to the superficial radial (SR) and the superficial peroneal (SP) nerves, and reflexes were recorded bilaterally from the soleus (SOL), tibialis anterior (TA), flexor carpi radialis (FCR), and the posterior deltoid (PD) muscles.

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[ARTICLE] An EMG Interface for the Control of Motion and Compliance of a Supernumerary Robotic Finger – Full Text 

In this paper, we present an electromyographic (EMG) control interface for a supernumerary robotic finger. This novel wearable robot can be used to compensate the missing grasping abilities in chronic stroke patients or to augment human healthy hand so to enhance its grasping capabilities and workspace. The proposed EMG interface controls the motion of the robotic extra finger and its joint compliance. In particular, we use a commercial EMG armband for gesture recognition to be associated with the motion control of the robotic device and surface one channel EMG electrodes interface to regulate the compliance of the robotic device. We also present an updated version of a robotic extra finger where the adduction/abduction motion is realized through ball bearing and spur gears mechanism. We validated the proposed interface with two sets of experiments related to compensation and augmentation. In the first set of experiments, different bi-manual tasks have been performed with the help of the robotic device and simulating a paretic hand. In the second set, the robotic extra finger is used to enlarge the workspace and manipulation capability of healthy hands. In both the sets, the same EMG control interface has been used. The obtained results demonstrate that the proposed control interface is intuitive and can successfully be used for both compensation and augmentation purposes. The proposed approach can be exploited also for the control of different wearable devices that has to actively cooperate with the human limbs.

Continue —> Frontiers | An EMG Interface for the Control of Motion and Compliance of a Supernumerary Robotic Finger | Frontiers in Neurorobotics

Figure 1. On left, the exploded cad view, whereas on right, the prototype of the robotic extra finger. Four modules are used for the flexion/extension motion, while the revolute joint based on bearings and spur gears mechanism at the finger base is used for the adduction/abduction motion. The device can be worn on the forearm through an elastic band.

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[ARTICLE] Wearable System for Device Control using Bio-Electrical Signal – Full Text PDF

Abstract

In today’s world, wearable devices are progressively being used for the enhancement of the nature of the life of individuals. Human Machine Interface (HMI) has been studied for dominant the mechanical device rehabilitation aids through biosignals like EOG and EMG etc., and so on. EMG signals have been studied in detail due to the occurrence of a definite signal pattern. The current proposal focuses on the advancement of a Wearable Device control by using EMG signals of hand movements for controlling the electronic devices. EMG signals are utilized for the production of the control indicators to develop the device control. Also, an EMG sign procurement framework was produced. To create different control signals relying on the sufficiency and length of time of signal segments, the obtained EMG signals were then prepared for device control.

1. Introduction

1.1 Need for Rehabilitation Techniques

A major a part of our society is littered with one or the opposite reasonably disabilities owing to accidents and neuro-logic disorders. These patients rely upon the members of the family or care takers for his or her day to day activities like quality, communication with atmosphere, mistreatment the home instrumentation, etc1,2.

Rehabilitation devices facilitate the patients with disabilities to measure, work, play or study severally. Moreover, they improve the standard of life led by these individuals and maintain their shallowness.

1.2 EMG based Methods

Electrical potentials generated during muscle contraction are measured by EMG. The contraction of somatic cell takes place once it receives associate degree impulse. The myogram ascertained is that the add of all the action potentials that occur round the conductor site. In most of the cases, the amplitude of the myogram will increase as a result of contraction. Myogram signals is used for a range of applications together with clinical applications, HCI and interactive gaming. They’re non-heritable simply and are comparatively high in magnitude than alternative bio-signals. On the opposite hand, myogram signals area unit simply liable to noise. myogram signals contain difficult styles of noise as a result of inherent instrumentation noise, non-particulate
radiation, motion artifacts, and therefore the interaction of various tissues. Hence, to filter the unwanted noise in myogram, preprocessing is critical3. The myogram signals even have completely different signatures counting on age, muscle development, motor unit ways, skin fat layer, and gesture designs. The external appearances of 2 individuals’ gestures would possibly look identical, however the characteristic myogram signals area unit completely different4.

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[Abstract] Detecting voluntary gait intention of chronic stroke patients towards top-down gait rehabilitation using EEG

Abstract:

One of the recent trends in gait rehabilitation is to incorporate bio-signals, such as electromyography (EMG) or electroencephalography (EEG), for facilitating neuroplasticity, i.e. top-down approach. In this study, we investigated decoding stroke patients’ gait intention through a wireless EEG system. To overcome patient-specific EEG patterns due to impaired cerebral cortices, common spatial patterns (CSP) was employed. We demonstrated that CSP filter can be used to maximize the EEG signal variance-ratio of gait and standing conditions. Finally, linear discriminant analysis (LDA) classification was conducted, whereby the average accuracy of 73.2% and the average delay of 0.13 s were achieved for 3 chronic stroke patients. Additionally, we also found out that the inverse CSP matrix topography of stroke patients’ EEG showed good agreement with the patients’ paretic side.

Source: IEEE Xplore Document – Detecting voluntary gait intention of chronic stroke patients towards top-down gait rehabilitation using EEG

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