Recipient organisationNIHR Imperial Biomedical Research Centre
NIHR supportRecorded as supported by this research centre
PeriodJan 2025 — Ongoing
In plain English
AI plain-English summary
A stroke patient wearing a headset plays a virtual-reality game that responds to the electrical signals from their own arm muscles, retraining their brain to move. This matters because around two-thirds of stroke survivors are left with a paralysed or weakened arm, and conventional physiotherapy often fails to restore useful movement. The problem is that patients lose the ability to activate their muscles, and standard exercises do not give them the real-time feedback needed to relearn that control. This study tests whether a VR system that reads muscle activity via electrodes on the skin—electromyography, or EMG—can bridge that gap by showing patients exactly when and how their muscles are firing, even if the movement is tiny. If the approach works, it could change how stroke rehabilitation is delivered. Instead of relying solely on a therapist’s hands-on guidance, patients might practise at home with a system that adapts the difficulty of the game to their cognitive load and force output. The researchers will also look for biomarkers in the EMG data that could predict which patients are likely to recover, allowing therapists to personalise treatment from the start. The study involves 58 patients, split into control and intervention groups, with follow-up at six months.
View original technical description
Design: An interventional study conducted in both acute stroke patients and chronic stroke patients, to validate the use of a virtual-reality based rehabilitation therapy. Data from the control group will be collected first (approximately 29 patients), to generate preliminary results. Following this, the intervention group data will be collected (approximately 29 patients) and compared to the control group. We will also complete a sub study using a similar design and recruitment number as the virtual reality intervention where we include functional electrical stimulation.Aims: To validate the use of an EMG-based virtual reality interface for use in the rehabilitation of stroke patients. To determine if there are biomarkers present in the EMG data that can be used to predict and inform on patient recovery. Generating experimental evidence on how to optimise rehabilitation, according to cognitive load, motor task and force generation. Outcome Measures: The primary end point outcome will be the Fugl Meyer Upper Extremity Assessment (FM-UE) at 6months, controlled for baseline. Additional outcome measures will include: The Action Arm Research Test (ARAT), Functional Independence Measure (FIM), Modified Rankin Scale (mRS), Hospital Anxiety and Depression Scale (HADS), Faces Pain Rating Scale (F-PRS), Stanford Fatigue Visual Numeric Scale (SFVNS), Patient Questionnaires (see Appendix), Device Recordings (EMG data, game performance metrics, exercise time). Population: A convenience sample of 58 stroke survivors will be screened and consented by delegated health care practitioners (HCPs) or researchers (i.e. Co-Investigators (Co-Is)). Eligibility: Participants will be 18yrs or over, acute/sub-acute or chronic stroke survivors with UL impairment that resulted from the stroke, fitting inclusion criteria specified herewith.Duration: Participants’ enrolment in the study will last up to 7months. The study recruitment phase will open for up to 24months. The overall research period, including analysis and write up is anticipated to last 43months.
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