A new method for reading brain waves improves the usefulness of motor imagery exercises
A*STAR Institute for Infocomm Research (I2R)’s scientists have found a new way to give stroke patients instructive feedback during rehabilitation exercises aimed at restoring mobility.
For stroke patients, the long road to recovery starts with rehabilitation exercises, including visualizations in which people imagine enacting motions they are physically unable to perform. This ‘rewires’ their brains, and leads to real-life bodily improvements. The exercises only work if you’re performing them correctly, and since visualization takes place entirely in the mind’s eye, it has been difficult for clinicians and patients to know if the correct brain connections are being made.
To get a glimpse inside the brain, patients typically wear caps fitted with electrodes that track neural activity via electroencephalography (EEG) readings. Now scientists from the A*STAR Institute for Infocomm Research have validated a more accurate way of turning those EEG signals into clinically meaningful feedback for stroke sufferers.
"This feedback will help stroke patients in rehabilitation restore brain functions and improve motor recovery," says study author, Kai Keng Ang, an A*STAR senior scientist who heads the Neural and Biomedical Technology Department.
This newer machine-learning strategy automatically calibrates the EEG patterns associated with a particular mental exercise to an individual’s unique brain waves while engaged in that task.
It helps to correct brain differences between individuals and avoids the hassle of multiple preparative sessions. It keeps updating its model of how the patient’s EEG patterns match motor imagery exercises as new information comes in after each and every session, thereby correcting for day-to-day changes in neural connectivity.
The A*STAR-affiliated researchers contributing to this research are from the Healthcare team of Institute for Infocomm Research.
A*STAR Research - An Adaptive approach to Stroke Recovery