Robotic head-neck brace control through EEG signals and BCI sensors using the Savitzky-Golay filter Available to Purchase

Healthy people take head and neck mobility for granted. But patients of neurological diseases including amyotrophic lateral sclerosis (ALS) and dropped head syndrome (DHS) and may make such simple tasks difficult. Because these patients generally lack the neck muscle ability to maintain their heads standing or move them controlled. Rehabilitation is the first step in treating head and neck movement so patients may up head to eat, drink, and socialize. Brain Computer Interface (BCI) technology lets patients interface with neck brace by brain waves and perform orders movement without muscles movement. The design proposed head neck parallel configuration (3-RRS) manipulator. The designer of all parts neck brace by Solidwork program. The manufacturing the head and neck support parts using 3D printing technology by (Creality Ender 3-pro) device and (Cura) program, by using PLA material and connecting three servomotors. the movement was controlled by brain signals (EEG) after filtering them acquired signals were pre- processed using filter (Savitzky–Golay) and a applying a specific algorithm, for the features extraction by SVM method and accuracy of confusion matrix of EEG signals to classified at apply six classes to the six neck main movements testing and training it to determine the type of movement required for the neck, the reading protocol of EEG was applied by taking six different experiments trials and applying (1875) samples/main movement, to finally (11,250) samples of any trial, by device used (OpenBCI-16 channels), the results of experimental by EEG signals at rotation of the neck to the right and left (± 55°), extension to up and flexion to down (± 42°), while the lateral bending to the right and left was (± 29°).