4.Armagan, O., Tascioglu, F., Oner, C.: Electromyographic biofeedback in the treatment of the hemiplegic hand: a placebo-controlled study. Am. J. Phys. Med. Rehabil. 82, 856–861 (2003). https://doi.org/10.1097/01.PHM.0000091984.72486.E0CrossRefGoogle Scholar
8.Spicer, R., Anglin, J., Krum, D.M., Liew, S.L.: REINVENT: a low-cost, virtual reality brain-computer interface for severe stroke upper limb motor recovery. In: Proceedings of IEEE Virtual Reality, pp. 385–386 (2017). https://doi.org/10.1109/vr.2017.7892338
10.Kothe, C.: Lab Streaming Layer (LSL). https://github.com/sccn/labstreaminglayer
Posts Tagged biofeedback
[ARTICLE] Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback – Full Text
Add-on robot-mediated therapy has proven to be more effective than conventional therapy alone in post-stroke gait rehabilitation. Such robot-mediated interventions routinely use also visual biofeedback tools. A better understanding of biofeedback content effects when used for robotic locomotor training may improve the rehabilitation process and outcomes.
This randomized cross-over pilot trial aimed to address the possible impact of different biofeedback contents on patients’ performance and experience during Lokomat training, by comparing a novel biofeedback based on online biological electromyographic information (EMGb) versus the commercial joint torque biofeedback (Rb) in sub-acute non ambulatory patients.
12 patients were randomized into two treatment groups, A and B, based on two different biofeedback training. For both groups, study protocol consisted of 12 Lokomat sessions, 6 for each biofeedback condition, 40 min each, 3 sessions per week of frequency. All patients performed Lokomat trainings as an add-on therapy to the conventional one that was the same for both groups and consisted of 40 min per day, 5 days per week. The primary outcome was the Modified Ashworth Spasticity Scale, and secondary outcomes included clinical, neurological, mechanical, and personal experience variables collected before and after each biofeedback training.
Lokomat training significantly improved gait/daily living activity independence and trunk control, nevertheless, different effects due to biofeedback content were remarked. EMGb was more effective to reduce spasticity and improve muscle force at the ankle, knee and hip joints. Robot data suggest that Rb induces more adaptation to robotic movements than EMGb. Furthermore, Rb was perceived less demanding than EMGb, even though patient motivation was higher for EMGb. Robot was perceived to be effective, easy to use, reliable and safe: acceptability was rated as very high by all patients.
Specific effects can be related to biofeedback content: when muscular-based information is used, a more direct effect on lower limb spasticity and muscle activity is evidenced. In a similar manner, when biofeedback treatment is based on joint torque data, a higher patient compliance effect in terms of force exerted is achieved. Subjects who underwent EMGb seemed to be more motivated than those treated with Rb.
Stroke is the leading cause of acquired disability throughout the world, with increasing survival rates as medical care and treatment techniques improve . Post-stroke disability often affects mobility, balance, and walking . The majority of stroke survivors rank walking recovery among their top rehabilitation goals [3,4,5]. Furthermore, the ability to walk is one of the most important determining factors for returning home after stroke .
Recovery of walking mainly occurs within the first 11 weeks after a stroke ; indeed, further recovery after that time is rare . Overall, between 30 and 40% of stroke survivors are not able to regain a functional gait after rehabilitation [4, 8]. These data have stimulated advances in many different innovative technological approaches to improve the gait rehabilitation efficacy.
Modern concepts favour task-specific repetitive rehabilitation approaches , with high intensity  and early multisensory stimulation . These requirements are met by robot assisted gait training (RAGT) approaches. Recent studies on stroke patients have reported that when conventional therapy and RAGT are combined, compared to conventional therapy alone, gait recovery significantly improves  and patients are more likely to recover independent walking . In particular, non-ambulatory patients in the sub-acute phase are the group most likely to benefit from this type of training .
This high interest in robotic therapy has attracted attention to human robot interactions in the rehabilitation framework, and a consensus is forming on the importance of top-down approaches in rehabilitation, particularly when dealing with robotic devices . The critical aspects of top-down approaches are multifarious and include motivation, active participation , learning skills  and error-driven-learning , evidencing the key aspects of biofeedback information to guide and improve patient robot interactions.
Thus, biofeedback is, at present, the main approach to guide top-down control mechanisms, which represents a powerful tool to drive recovery. To this aim, the patient has to be aware of the differences between on-line performance and the desired performance . In this scenario, many different error signals can be used, and at present, no indication exists for their specific effects on performances [18, 19]. Many biological parameters have been used to feed biofeedback information to patients in different stroke gait rehabilitation scenarios .
In general, in spite of the information content, biofeedback has been associated with improved outcomes in several gait pathologies [21,22,23,24]. Among diverse types of biofeedback, the most generally employed in gait rehabilitation paradigms have been electromyographic (EMG), kinematic as well as robot generated indexes , although no comparisons have been made among these approaches.
At present, many robotic devices for gait rehabilitation in stroke are commercially available . Two main classes can be identified, those based on body weight support systems (BWSS) and over ground exoskeletons. Overall, BWSS are the most widely used in rehabilitation centres, with Lokomat, Gait Trainer and GEO systems being the most popular. The present study focuses on the biofeedback content effects during Lokomat gait training in stroke survivors. Commercially available Lokomat biofeedback tools are based either on navigational or robot-generated information. The latter approach focuses on the forces that assist patients to follow the predefined gait pattern due to force transducers built into the robot drives .
Generally effectiveness of Lokomat training is assessed with gait functional outcome measures. Specific data about spasticity effects of Lokomat training are rare, and mainly focused on spinal cord injury (SCI) patients and on ankle muscles. In this framework few studies addressed positive effects of Lokomat training on reducing spasticity and improving volitional control of the spastic ankle in persons with incomplete SCI , and on reducing the abnormal modulation of neuromuscular properties that arises as secondary effects after SCI [28, 29]. To our knowledge, as concern stroke population, a single study compared conventional rehabilitation versus Lokomat add-on training selecting spasticity as a secondary outcome, demonstrating no significant robotic gait training effects .
Furthermore, no studies have either analysed the use of an electromyographic -based biofeedback (EMGb) of hip, knee and ankle muscles during training with the Lokomat robot, or compared the impact of different biofeedback types on Lokomat robotic gait training. To this end, we designated a randomized controlled trial, because this type of study is the most rigorous and robust research method of determining whether a cause-effect relation exists between an intervention and an outcome . In this pilot study we compared two different types of biofeedback: a robot generated joint torque biofeedback (Rb) versus a novel on-line EMGb. Thus, a randomized cross-over clinical trial using the Lokomat RAGT device, was conducted focusing on patients’ performances, personal experience and robot forces data in sub-acute non ambulatory patients. In particular the main outcome measure was considered the lower limb spasticity. Considering that in stroke population, spasticity may affect quality-of-life and can be highly detrimental to daily function , we also analysed patients’ personal experience related to training gait with the Lokomat system.[…]
Continue —> Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback | Journal of NeuroEngineering and Rehabilitation | Full Text
[Abstract + References] Electromyography as a Suitable Input for Virtual Reality-Based Biofeedback in Stroke Rehabilitation – Conference paper
Virtual reality (VR)-based biofeedback of brain signals using electroencephalography (EEG) has been utilized to encourage the recovery of brain-to-muscle pathways following a stroke. Such models incorporate principles of action observation with neurofeedback of motor-related brain activity to increase sensorimotor activity on the lesioned hemisphere. However, for individuals with existing muscle activity in the hemiparetic arm, we hypothesize that providing biofeedback of muscle signals, to strengthen already established brain-to-muscle pathways, may be more effective. In this project, we aimed to understand whether and when feedback of muscle activity (measured using surface electromyography (EMG)) might more effective compared to EEG biofeedback. To do so, we used a virtual reality (VR) training paradigm we developed for stroke rehabilitation (REINVENT), which provides EEG biofeedback of ipsilesional sensorimotor brain activity and simultaneously records EMG signals. We acquired 640 trials over eight 1.5-h sessions in four stroke participants with varying levels of motor impairment. For each trial, participants attempted to move their affected arm. Successful trials, defined as when their EEG sensorimotor desynchronization (8–24 Hz) during a time-limited movement attempt exceeded their baseline activity, drove a virtual arm towards a target. Here, EMG signals were analyzed offline to see (1) whether EMG amplitude could be significantly differentiated between active trials compared to baseline, and (2) whether using EMG would have led to more successful VR biofeedback control than EEG. Our current results show a significant increase in EMG amplitude across all four participants for active versus baseline trials, suggesting that EMG biofeedback is feasible for stroke participants across a range of impairments. However, we observed significantly better performance with EMG than EEG for only the three individuals with higher motor abilities, suggesting that EMG biofeedback may be best suited for those with better motor abilities.
The article describes an innovative mechatronic device for the hand rehabilitation, which enables diagnostics, comprehensive exercises and reporting of the results of rehabilitation of individual fingers of people who have lost their full efficiency as a result of past illnesses (i.a. stroke) and orthopedic injuries. The basic purpose of the device is to provide controlled, active exercises of the individual fingers, to widen the range of their movements, and to increase their precision of movement. The developed mechatronic device works with original software for PCs containing a diagnostic module, reporting module and a set of virtual reality exercises using biofeedback. The device uses auditory and visual biofeedback, and electromyography (EMG).
A neuromuscular interface (NI) that can be employed to operate external robotic devices (RD), including commercial ones, was proposed. Multichannel electromyographic (EMG) signal is used in the control loop. Control signal can also be supplemented with electroencephalography (EEG), limb kinematics, or other modalities. The multiple electrode approach takes advantage of the massive resources of the human brain for solving nontrivial tasks, such as movement coordination. Multilayer artificial neural network was used for feature classification and further to provide command and/or proportional control of three robotic devices. The possibility of using biofeedback can compensate for control errors and implement a fundamentally important feature that has previously limited the development of intelligent exoskeletons, prostheses, and other medical devices. The control system can be integrated with wearable electronics. Examples of technical devices under control of the neuromuscular interface (NI) are presented.
Development of neurointerface technology is a topical scientific focus, with the demand for such systems driven by the need for humans to communicate with numerous electronic computing and robotic devices (RD), for example, in medical applications such as prosthetic limbs and exoskeletons. At present, multichannel recording of neuromuscular activity and the development of neurointerface applications that implement unique mechanisms for high-dimensional data processing are areas of major interest.
One of the most suitable signals aiming at controlling external RDs is electromyographic (EMG) activity. Multichannel signals from the human peripheral nervous system have been previously successfully used to control external devices and novel methods of EMG acquisition and control strategies have recently been implemented [1–8]. When controlling anthropomorphic RD, the human pilot independently coordinates and plans the trajectory of motion using the massive computing power of the human brain [9, 10]. The use of afferent neural pathways allows the activation of biological feedback; using this principle is fundamentally important to the development of rehabilitation exoskeletons, prostheses, and various other medical applications.
The disadvantages of using EMG interfaces in rehabilitation are the presence of muscle fatigue and insufficient residual muscle activity. On the other hand electroencephalographic (EEG) interfaces proved to be the best due to a direct link to the nervous system by measurement of brain activity during therapy [11, 12]. The brain mechanisms that enable humans to facilitate the control of external devices remain largely unknown. However, despite this knowledge gap, appropriate collection, detection, and classification can enable brain-controlled signals from the human body to be utilized for highly efficient and even intelligent control of multiparameter RDs. But brain-machine interfaces (BMI) have some limitations such as low reliability and accuracy when it comes to complex functional task training.
A possible solution to these problems is the combined use of the advantages of both types of interfaces. Such interfaces are called hybrid, for example, hybrid BMI (hBMI); the use of EMG input here can lead to a more accurate classification of EEG patterns [13–15]. However, the task of developing an EMG interface is still relevant.
Considering the problem of motion recognition and decoding of EMG signals, note that there are several generally applicable methods of software signal processing: linear discriminant analysis (LDA) , support vector machines (SVM) , artificial neural networks (ANN) , fuzzy algorithms [22, 23], etc.
Despite significant progress in the field of machine learning and its application in medical tasks , algorithms are still based on applying ANN technologies and solving optimization problems. Creation of a universal algorithm that can adapt to different conditions in a technical control system was proven theoretically impossible, at least in the context of existing theories [25, 26]. Compared to traditionally controlled electronic devices, neurocontrolled devices may offer the advantage of adapting due to human brain plasticity.
The present study focuses on the development of methods and technologies for remote control of RDs in specific applications. The objective was to integrate human bioelectrical signals into a control loop. Online collection and interpretation of multisite EMG signals were performed to control a variety of robotic systems. Technical solutions were developed to associate patterns of muscular activity (and human brain, if possible) with the commands to the controlled object by employing a user-defined translation algorithm. EMG interface solution is driven by multilayer ANN feature classifier. User-defined programmable function translates sensory signals into motor commands to successfully control a variety of existing commercial RDs.[…]
Children are the group most frequently diagnosed with new cases of epilepsy. In the United States, 300,000 children under 14 are affected by the condition. Some may outgrow the disorder, but most will not. The number of senior citizens with epilepsy is also 300,000.
People with epilepsy have a range of treatment options, including alternative therapies.
The illness is a complex condition, however, and all alternative treatment options must be looked at carefully, to ensure they are effective.
It is essential to work with a doctor when making changes in treatment, as every epileptic seizure can cause brain damage, and the effects build up. So, any treatment must work to avoid seizures.
Contents of this article:
Causes of epilepsy
Infections, which can cause scarring on the brain that leads to seizures, are among the more common causes of epilepsy.
In the over 65s, strokes are the most common cause of new seizures. Family history and brain injuries account for other cases.
However, the Epilepsy Foundation say the cause is unknown in 60 percent of people.
Eight natural remedies for epilepsy
People with epilepsy and their doctors are expressing growing interest in alternative therapies.
Although antiepileptic drugs (AEDs) help most people control their symptoms, these do not work for everyone. Furthermore, some people are concerned about the long-term safety of these drugs.
Complementary health practices for epilepsy, such as the eight natural remedies discussed here, are designed for use in combination with AEDs.
After talking to a doctor, and before beginning natural treatments, people with epilepsy should ensure they are working with a well-qualified and informed therapist.
Common complementary treatments for epilepsy include the following:
Cannabis sativa, or marijuana, as it is commonly known, has been used to treat convulsions for centuries. Today, it is attracting increasing attention from people with epilepsy, clinicians, and researchers.
Interest in the use of medical marijuana is particularly strong for the roughly 1 million U.S. residents whose seizures are not controlled by AEDs. Some families with young children, suffering from severe seizures, have moved to one of the 22 states where medical marijuana use is legal.
Charlotte’s Web is a strain of cannabis bred to contain high levels of CBD, a part of the plant showing promise against seizures. It is named after a child whose convulsions dropped from more than 300 a week to 2-3 a month with this treatment.
However, since broad-based, well-designed scientific studies have yet to prove the effectiveness of marijuana in treating epilepsy, doctors do not generally recommend its use.
Diet is one of the earliest forms of treatment for epilepsy and is used with contemporary variations to make it easier for children and adults to adopt.
The ketogenic diet is a high-fat, low-carbohydrate diet that has had some success in reducing seizures in children who cannot tolerate or benefit from AEDs. It requires extensive commitment and monitoring.
The Atkins diet is a high-protein, low-carbohydrate diet that is less restrictive and has shown positive effects.
Low glycemic index treatment (LGIT) is similar but allows for a targeted level of carbohydrate consumption.
Herbs are used for many illnesses by 80 percent of the world’s population. Remedies drawing on Chinese traditions have shown promise in treating epilepsy.
Some herbs, such as chamomile, passionflower, and valerian, may make AEDs more effective and calming.
However, ginkgo, ginseng, and stimulating herbs containing caffeine and ephedrine can make seizures worse.
St. John’s wort can interfere with medications and make seizures more likely, similarly to evening primrose and borage.
Caution is advised when working with all these herbs.
It is important to remember that herbs are not monitored by the U.S. Food and Drug Administration (FDA). If any herbs are used, they should be researched and bought from reputable sources.
Low levels of the B6 vitamin have been known to trigger seizures.
Magnesium, vitamin E, and other vitamins and nutritional supplements, have been identified as either promising or problematic for treating epilepsy.
Along with vitamin B6, magnesium, and vitamin E, which have been found to be helpful in treating epilepsy, doctors have found treatment with manganese and taurine reduced seizures, as well.
Thiamine may help improve the ability to think in people with epilepsy.
When AEDs do not work, some people have successfully used biofeedback to reduce seizures.
With the use of extensive training and a machine that detects electrical activity in the brain, the technique teaches individuals to recognize the warning signs of seizures, and train their brains to prevent a full-blown attack.
There are many different practices that people with epilepsy can follow on their own to help them feel calmer, relax their muscles, get better sleep, and enjoy a better state of mind.
All these actions taken together can help reduce seizures and make it easier for people to manage their epilepsy.
People should be cautious if trying meditation, as this can change the electrical signals in the brain.
Some essential oils used in aromatherapy, such as lavender, chamomile, jasmine, and ylang-ylang, have been found to be effective in preventing seizures when used with relaxation techniques.
However, the Epilepsy Society report that others may provoke seizures. These include spike lavender, eucalyptus, camphor, sage, rosemary, hyssop, and fennel.
Acupuncture and chiropractic
While acupuncture does not seem to be helpful in preventing seizures, people with epilepsy find it can reduce the stress of living with the condition.
There is little evidence on chiropractic care, but it also may be among the natural treatments people with epilepsy find useful.
Education and avoiding triggers
Education and avoidance can have a big impact on quality of life for people with this condition.
Many of those with epilepsy find that their seizures develop in response to specific triggers. This is the case for people with photosensitive epilepsy.
Learning how to avoid situations and stimuli that could spark a seizure can be very helpful. Some children may learn to avoid using video games in dark rooms, for example, or to cover one eye when exposed to flashing lights.
Do natural treatments for epilepsy work?
For many practices, there has not been enough study to give a definite answer to this question, one way or the other.
The following overview of the top natural treatments for epilepsy offers a quick summary of their reported effectiveness:
- Diet: The ketogenic diet, usually prescribed for children whose epilepsy does not respond to AEDs, has been shown to cut their seizures by half and eliminate seizures completely for 10-15 percent of those studied.
- Herbal treatments: Two studies of Chinese herbal compounds found them effective at reducing seizures in children and adults. But some herbs, such as St. John’s wort, can make seizures worse.
- Vitamins: Many studies have linked low levels of vitamin B6, magnesium, and vitamin E to seizures. Treating people with supplemental doses helped reduce the frequency of seizures.
- Biofeedback: Researchers in 10 different studies showed that 74 percent of people whose epilepsy could not be treated with medication, reported fewer seizures after they learned this technique.
- Relaxation: Fewer seizures and a better quality of life were reported by children who took part in trials, according to research.
- Acupuncture and chiropractic: Scientific studies have not found acupuncture to be effective for people with epilepsy. However, positive outcomes were reported for some children with drug-resistant epilepsy who tried chiropractic therapy.
- Education: After learning more about epilepsy, coping strategies for it, and how to take medication, improved quality of life was observed for people of all ages with epilepsy.
Many reports on the effectiveness of complementary treatments for epilepsy come from personal experience, and from studies that are not considered conclusive.
Most importantly, people should always talk to their doctor before trying natural treatments to help ease their symptoms.
[ARTICLE] The effects of training using EMG biofeedback on stroke patients upper extremity functions – Full Text PDF
[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
[ARTICLE] Can Short-Term Constraint-Induced Movement Therapy Combined With Visual Biofeedback Training Improve Hemiplegic Upper Limb Function of Subacute Stroke Patients? – Full Text
Most stroke survivors have upper limb motor impairments, along with difficulties in performing activities of daily living . Currently, there are several known intervention treatments for functional recovery of the upper limb after stroke.
Constraint-induced movement therapy (CIMT) has been shown to enhance hemiplegic upper limb functions at both early and late stages of post-stroke . The test was developed by Taub et al.  to improve the function of the affected upper limb by limiting the motion of the intact upper limb and induce affected upper limb movement [4, 5]. The original CIMT program consisted of 2 weeks of restraining the unaffected upper limb for 90% of waking hours combined with forced use of the affected upper limb for approximately 6 hours per day during task-oriented activities. However, Page et al.  reported that 68% of 208 stroke patients said that they were disinterested in participating in CIMT. One domestic research study showed that 12 out of 46 patients dropped out when they participated in CIMT lasting for 14 hours daily for 2 weeks. The most common reason for dropping out in this study was the lack of participation in training time . Therefore, in a clinical setting, various modified CIMT methods have been developed to improve participation rates.
Recently visual biofeedback training (VBT) has been studied and introduced as a therapeutic option because VBT might improve motor performance by effectively tuning the control structure . Also, Kim et al.  reported a significant effect of spatial target reaching training based on visual biofeedback of the upper limb function in hemiplegic subjects. In their previous article, VBT group showed more significant improvement than the control group in the Wolf Motor Function Test (WMFT) and the Fugl-Meyer Assessment (FMA).
Several other studies have also been developed that recognize the effect of CIMT combined with other treatments [10, 11, 12]. In these trials, unaffected upper limbs were restrained for several hours daily, even when participants were not taking other combined therapies. However, it is not easy to apply restraint for more than 5 to 6 hours daily in a clinical setting and longer restraint times can compromise a patient’s therapeutic compliance. To overcome these limitations, it is necessary to find out whether there is any modified therapies have any effects such as a reduced restraint time in CIMT during combined therapy.
In this study, we applied a new CIMT protocol in a clinical setting, while maintaining the existing concept of CIMT. Both CIMT and VBT were performed simultaneously for 1 hour daily for 2 weeks. CMT is hereafter referred to as ‘short-term’ CIMT. We examined the effects of short-term CIMT combined with VBT on gross and fine motor functions and daily functions in patients with subacute hemiplegic strokes. We hypothesized that study participant who received short-term CIMT with VBT would demonstrate more improved outcomes than patients who received VBT alone.
[Abstract] Effects of ankle biofeedback training on strength, balance, and gait in patients with stroke – PEDro
|Effects of ankle biofeedback training on strength, balance, and gait in patients with stroke|
|Kim S-J, Cho H-Y, Kim K-H, Lee S-M|
|Journal of Physical Therapy Science 2016 Sep;28(9):2596-2600|
|PURPOSE: This study aimed to investigate the effects of ankle biofeedback training on muscle strength of the ankle joint, balance, and gait in stroke patients. SUBJECTS AND METHODS: Twenty-seven subjects who had had a stroke were randomly allocated to either the ankle biofeedback training group (n = 14) or control group (n = 13). Conventional therapy, which adhered to the neurodevelopmental treatment approach, was administered to both groups for 30 minutes. Furthermore, ankle strengthening exercises were performed by the control group and ankle biofeedback training by the experimental group, each for 30 minutes, 5 days a week for 8 weeks. To test muscle strength, balance, and gait, the Biodex isokinetic dynamometer, functional reach test, and 10 m walk test, respectively, were used. RESULTS: After the intervention, both groups showed a significant increase in muscle strength on the affected side and improved balance and gait. Significantly greater improvements were observed in the balance and gait of the ankle biofeedback training group compared with the control group, but not in the strength of the dorsiflexor and plantar flexor muscles of the affected side. CONCLUSION: This study showed that ankle biofeedback training significantly improves muscle strength of the ankle joint, balance, and gait in patients with stroke.
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[Abstract] Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans