EMG-Controlled Device for Stroke Rehabilitation
Recruiting in Palo Alto (17 mi)
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: VA Office of Research and Development
Must not be taking: Seizure threshold-lowering drugs
Disqualifiers: Hemorrhagic stroke, Seizures, Epilepsy, others
No Placebo Group
Trial Summary
What is the purpose of this trial?Stroke is a medically relevant problem for the aging population. Individuals with stroke experience a high amount of arm functional deficits despite receiving rehabilitation. Functional deficits can be improved by combining rehabilitation with innovative rehabilitative tools that target the brain mechanisms that guide the recovery early after stroke. This study aims to explore the feasibility of implementing an EMG controlled device in the acute rehabilitation for stroke survivors with severe arm deficit. This study will determine if adding such a technology improve the clinical outcomes for subjects with severe arm impairments beyond the levels achieved by standard care in attempt to increase their chances to independently perform activities of daily living.
Will I have to stop taking my current medications?
The trial does not specify if you need to stop taking your current medications, but it excludes those currently taking medications that lower the threshold for seizures.
What data supports the effectiveness of the treatment MARK for stroke rehabilitation?
Research shows that using surface electromyography (EMG) to monitor muscle activity can help track recovery and improve rehabilitation for stroke patients. EMG feedback has been shown to enhance control and movement in stroke-affected limbs, suggesting that EMG-controlled devices like MARK could be effective in stroke rehabilitation.
12345Is the EMG-Controlled Device for Stroke Rehabilitation safe for humans?
Research on similar technologies like surface electromyography (sEMG) and MIRA has shown that they are generally safe for use in humans, with no adverse events reported in studies. These technologies are non-invasive and have been used comfortably in clinical settings to monitor muscle activity and aid rehabilitation.
12678How does the EMG-controlled device treatment for stroke rehabilitation differ from other treatments?
The EMG-controlled device for stroke rehabilitation is unique because it uses electromyography (EMG) signals, which are the electrical signals from muscle contractions, to control rehabilitation devices. This allows for personalized and real-time feedback, enabling stroke patients to engage in rehabilitation exercises at home without needing a therapist present, which is different from traditional rehabilitation methods that often require in-person supervision.
19101112Eligibility Criteria
This trial is for veterans over 18 who've had an ischemic stroke within the last 6 months, can understand English, and follow directions. They should be medically stable with a certain level of muscle stiffness in their arm but able to move it enough to wear a device. They must not have severe arm contractures, involuntary movements, or conditions that could interfere with the study.Inclusion Criteria
I had a stroke caused by a clot between 2 days and 6 months ago.
You can consistently and intentionally produce detectable muscle signals in your upper and lower arm with your wrist in a normal or bent position, as detected by the Myopro software.
I can move my elbow, forearm, wrist, and hand well enough to wear a device.
+5 more
Exclusion Criteria
My family has a history of epilepsy that doesn't respond well to medication.
I have had a stroke that affected my ability to move the opposite side of my body.
I can't lift my arm sideways or in front above shoulder level.
+15 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Treatment
Participants receive acute rehabilitation with an EMG controlled device for stroke survivors with severe arm deficit
6 weeks
Follow-up
Participants are monitored for changes in arm function and impairment after treatment
4 weeks
Participant Groups
The trial tests if using an EMG controlled device during early rehabilitation helps stroke survivors with severe arm deficits improve more than standard care alone. The goal is to see if this technology increases their ability to perform daily activities independently.
1Treatment groups
Experimental Treatment
Group I: FeasibilityExperimental Treatment1 Intervention
To explore if the feasibility of adding an EMG controlled device to the acute rehabilitation for stroke subjects with severe arm deficit.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Louis Stokes VA Medical Center, Cleveland, OHCleveland, OH
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Who Is Running the Clinical Trial?
VA Office of Research and DevelopmentLead Sponsor
References
Muscle Activity After Stroke: Perspectives on Deploying Surface Electromyography in Acute Care. [2020]After a stroke, clinicians and patients struggle to determine if and when muscle activity and movement will return. Surface electromyography (EMG) provides a non-invasive window into the nervous system that can be used to monitor muscle activity, but is rarely used in acute care. In this perspective paper, we share our experiences deploying EMG in the clinic to monitor stroke survivors. Our experiences have demonstrated that deploying EMG in acute care is both feasible and useful. We found that current technology can be used to comfortably and non-obtrusively monitor muscle activity, even for patients with no detectable muscle activity by traditional clinical assessments. Monitoring with EMG may help clinicians quantify muscle activity, track recovery, and inform rehabilitation. With further research, we perceive opportunities in using EMG to inform prognosis, enable biofeedback training, and provide metrics necessary for supporting and justifying care. To leverage these opportunities, we have identified important technical challenges and clinical barriers that need to be addressed. Affordable wireless EMG system that can provide high-quality data with comfortable, secure interfaces that can be worn for extended periods are needed. Data from these systems need to be quickly and automatically processed to create round-ready results that can be easily interpreted and used by the clinical team. We believe these challenges can be addressed by integrating and improving current methods and technology. Deploying EMG in the clinic can open new pathways to understanding and improving muscle activity and recovery for individuals with neurologic injury in acute care and beyond.
"It's All Sort of Cool and Interesting…but What Do I Do With It?" A Qualitative Study of Stroke Survivors' Perceptions of Surface Electromyography. [2023]Background: Stroke is one of the most common neurologic injuries worldwide. Over decades, evidence-based neurorehabilitation research and advancements in wireless, wearable sensor design have supported the deployment of technologies to facilitate recovery after stroke. Surface electromyography (sEMG) is one such technology, however, clinical application remains limited. To understand this translational practice gap and improve clinical uptake, it is essential to include stakeholder voices in an analysis of neurorehabilitation practice, the acceptability of current sEMG technologies, and facilitators and barriers to sEMG use in the clinic and the community. The purpose of this study was to foreground the perspectives of stroke survivors to gain a better understanding of their experiences in neurorehabilitation, the technologies they have used during their recovery, and their opinions of lab-designed and commercially-available sEMG systems. Methods: A qualitative, phenomenological study was completed. In-depth, semi-structured interviews were conducted with eight stroke survivors (age range 49-78 years, 6 months to 12 years post-stroke) and two caregivers from a large metropolitan region. A demonstration of four sEMG systems was provided to gather perceptions of sensor design, features and function, and user interface. Interviews were audio-recorded, transcribed verbatim, and coded for analysis using constant comparison until data saturation was reached. Results: Three themes emerged from the data: (1) "Surface EMG has potential….but…" highlights the recognition of sEMG as a valuable tool but reveals a lack of understanding and need for clear meaning from the data; (2) "Tracking incremental progress over days or years is important" highlights the persistence of hope and potential benefit of sEMG in detecting small changes that may inform neurorehabilitation practice and policy; and (3) "Neurorehabilitation technology is cumbersome" highlights the tension between optimizing therapy time and trying new technologies, managing cost, logistics and set-up, and desired technology features. Conclusion: Further translation of sEMG technology for neurorehabilitation holds promise for stroke survivors, but sEMG system design and user interface needs refinement. The process of using sEMG technology and products must be simple and provide meaningful insight to recovery. Including stroke survivors directly in translational efforts is essential to improve uptake in clinical environments.
Effects of electromyography-driven robot-aided hand training with neuromuscular electrical stimulation on hand control performance after chronic stroke. [2022]An electromyography-driven robot system integrated with neuromuscular electrical stimulation (NMES) was developed to investigate its effectiveness on post-stroke rehabilitation.
Visually displayed EMG feedback: single case studies of hemiplegic upper extremity rehabilitation. [2019]The efficacy of visually displayed EMG feedback in treating hemiplegic upper limb motor disorders was investigated in 5 patients (0.5-4 years poststroke). A single case experimental method "multiple-baseline across target behaviors" was used to compare performance during the feedback phase to that occurring in the monitored baseline phase. The nonfeedback baseline phase was followed by the staggered introduction of audiovisual feedback for each of the targeted pairs of muscles. EMG feedback obtained from muscle pairs (shoulder: anterior deltoid and upper trapezius; elbow: brachial triceps and biceps; digits: extensor digitorum communis and digit flexors) was displayed as two distinct waveforms on a videomonitor during therapy. Nonfeedback assessment of each of the three pairs was performed during each session. The effects of feedback were not uniformly distributed. Elbow control responded best, and statistical tests confirmed the effects of intervention observed clinically in all 5 patients. Clinical improvements in shoulder flexion were observed in 4 patients but could be statistically attributed to EMG gains in just 1. Improvement in finger extension observed clinically in 3 patients was statistically attributable to EMG gains in 2. All patients regained control of at least one target activity. EMG gains were accompanied by increases in active range of motion and by varying functional improvement. Marked functional gains in 3 patients were obtained with recovery of finger control.
Using surface electromyography to guide the activation during motor-evoked potential measurement: An activation control method for follow-up studies. [2016]This study evaluated the reliability and validity of a convenient method that uses the real-time feedback surface electromyography (sEMG) to control muscle activation while measuring the MEP recorded from the quadriceps muscle in patients with stroke.
"Look, Your Muscles Are Firing!": A Qualitative Study of Clinician Perspectives on the Use of Surface Electromyography in Neurorehabilitation. [2023]To examine the perceived value, benefits, drawbacks, and ideas for technology development and implementation of surface electromyography recordings in neurologic rehabilitation practice from clinical stakeholder perspectives.
Feasibility of using MIRA with adult patients presenting with upper limb motor dysfunction post neurological damage. [2017]Computer-based technology is an emerging modality to facilitate upper limb rehabilitation post neurological damage. A feasibility project using MIRA technology in an adult outpatient neurophysiotherapy service was conducted. Ten patients trialled nine MIRA games that promoted discrete and continuous unilateral and bilateral upper limb movements. The effect of MIRA use on usual service operation as well as any adverse events was noted. Patient views of using MIRA were explored through self-reported questionnaires. For six patients, comparison of amount and frequency of active upper limb exercises using MIRA and typical prescribed upper limb exercises was made. Use of MIRA did not negatively affect service operation and was not associated with any adverse event reporting. The majority of patients enjoyed using MIRA and felt that it was a useful modality to supplement existing prescribed upper limb exercises. Those with previous experience of technology expressed the most positive feedback. There is evidence that MIRA tasks may facilitate intensive repetitive upper limb movements, although some patients reported in-exercise discomfort. In conclusion, it was feasible to use MIRA with adult patients post neurological damage presenting with upper limb motor dysfunction, particularly those patients with proximal upper limb motor dysfunction previously familiar with computer use or gaming experience.
Progress toward motor recovery with active neuromuscular stimulation: muscle activation pattern evidence after a stroke. [2019]Chronic cerebrovascular accident individuals with partial paralysis in an upper extremity typically demonstrate difficulty in voluntarily controlling movement initiation. This study investigated patterns of electromyogram (EMG) activation levels while stroke subjects voluntarily initiated their impaired wrist and finger extensor muscles. Twenty subjects were randomly assigned to either a unilateral movement/stimulation group or a bilateral movement/stimulation group. Participants completed 4 days (6 h over 2 weeks) of active neuromuscular stimulation (i.e., 5 s/trial, 90 trials/day, biphasic waveform) on the wrist and finger extensors according to group assignments. The EMG activation levels were analyzed with a three-factor mixed design Motor recovery protocol x Session block x Trial block (2 x 2 x 3) ANOVA with repeated measures on the second and third factors. This robust analysis revealed higher EMG activation levels for the coupled bilateral movement/stimulation group than the unilateral movement/stimulation group. In addition, higher muscle activation levels were found for the second session block as well as trial blocks 2 and 3. Overall, these findings indicated improved motor capabilities of the impaired muscles as evidenced by the higher voluntary EMG activation levels.
Myoelectric control in neurorehabilitation. [2019]A myoelectric signal, or electromyogram (EMG), is the electrical manifestation of a muscle contraction. Through advanced signal processing techniques, information on the neural control of muscles can be extracted from the EMG, and the state of the neuromuscular system can be inferred. Because of its easy accessibility and relatively high signal-to-noise ratio, EMG has been applied as a control signal in several neurorehabilitation devices and applications, such as multi-function prostheses and orthoses, rehabilitation robots, and functional electrical stimulation/therapy. These EMG-based neurorehabilitation modules, which constitute muscle-machine interfaces, are applied for replacement, restoration, or modulation of lost or impaired function in research and clinical settings. The purpose of this review is to discuss the assumptions of EMG-based control and its applications in neurorehabilitation.
High-density myoelectric pattern recognition toward improved stroke rehabilitation. [2016]Myoelectric pattern-recognition techniques have been developed to infer user's intention of performing different functional movements. Thus electromyogram (EMG) can be used as control signals of assisted devices for people with disabilities. Pattern-recognition-based myoelectric control systems have rarely been designed for stroke survivors. Aiming at developing such a system for improved stroke rehabilitation, this study assessed detection of the affected limb's movement intention using high-density surface EMG recording and pattern-recognition techniques. Surface EMG signals comprised of 89 channels were recorded from 12 hemiparetic stroke subjects while they tried to perform 20 different arm, hand, and finger/thumb movements involving the affected limb. A series of pattern-recognition algorithms were implemented to identify the intended tasks of each stroke subject. High classification accuracies (96.1% ± 4.3%) were achieved, indicating that substantial motor control information can be extracted from paretic muscles of stroke survivors. Such information may potentially facilitate improved stroke rehabilitation.
Several practical issues toward implementing myoelectric pattern recognition for stroke rehabilitation. [2016]High density surface electromyogram (sEMG) recording and pattern recognition techniques have demonstrated that substantial motor control information can be extracted from neurologically impaired muscles. In this study, a series of pattern recognition parameters were investigated in classification of 20 different movements involving the affected limb of 12 chronic stroke subjects. The experimental results showed that classification performance could be improved with spatial filtering and be maintained with a limited number of electrodes. It was also found that appropriate adjustment of analysis window length, sampling rate, and high-pass cut-off frequency in sEMG conditioning and processing would be potentially useful in reducing computational cost and meanwhile ensuring classification performance. The quantitative analyses are useful for practical myoelectric control toward improved stroke rehabilitation.
Development of an EMG-Controlled Knee Exoskeleton to Assist Home Rehabilitation in a Game Context. [2023]As a leading cause of loss of functional movement, stroke often makes it difficult for patients to walk. Interventions to aid motor recovery in stroke patients should be carried out as a matter of urgency. However, muscle activity in the knee is usually too weak to generate overt movements, which poses a challenge for early post-stroke rehabilitation training. Although electromyography (EMG)-controlled exoskeletons have the potential to solve this problem, most existing robotic devices in rehabilitation centers are expensive, technologically complex, and allow only low training intensity. To address these problems, we have developed an EMG-controlled knee exoskeleton for use at home to assist stroke patients in their rehabilitation. EMG signals of the subject are acquired by an easy-to-don EMG sensor and then processed by a Kalman filter to control the exoskeleton autonomously. A newly-designed game is introduced to improve rehabilitation by encouraging patients' involvement in the training process. Six healthy subjects took part in an initial test of this new training tool. The test showed that subjects could use their EMG signals to control the exoskeleton to assist them in playing the game. Subjects found the rehabilitation process interesting, and they improved their control performance through 20-block training, with game scores increasing from 41.3 ± 15.19 to 78.5 ± 25.2. The setup process was simplified compared to traditional studies and took only 72 s according to test on one healthy subject. The time lag of EMG signal processing, which is an important aspect for real-time control, was significantly reduced to about 64 ms by employing a Kalman filter, while the delay caused by the exoskeleton was about 110 ms. This easy-to-use rehabilitation tool has a greatly simplified training process and allows patients to undergo rehabilitation in a home environment without the need for a therapist to be present. It has the potential to improve the intensity of rehabilitation and the outcomes for stroke patients in the initial phase of rehabilitation.