For those paralyzed from the neck down (quadriplegic), simple tasks such as short-range transportation can pose a major difficulty. The goal of this research is to provide quadriplegic individuals with independent transportation. By using electroencephalogram (EEG), a noninvasive method to measure electrical activities in the brain, the group can create a brain-computer interface (BCI) that will allow the user to control a wheelchair with his or her own thoughts. Components being integrated into the project include a Raspberry Pi 3 (with Bluetooth) and a Neurosky headset, which allows the user to analyze levels of concentration, meditation, and registers blinks. Success in this research setting will be indicated by the ability of a non-paralyzed user to navigate a GoPiGo (a Raspberry Pi connected to motorized wheels) proof-of-concept wheelchair-like device from rest to an indicated ending point using only their thoughts.
- Alexander Harold Polus
- Contruction of wheelchair prototype
- Bluetooth connection
- Implementing tank drive
- Sandeep Sagoo
- Establishing stable Bluetooth connection
- Implementing tank drive
- Anish Sinha
- Neurosky and EEG signal processing
- Mapping signal value to motor movements
- Establishing stable Bluetooth connection
- Implementing tank drive
- Shuyue (Yvette) Weng
- Mapping signal to individual motors for left/right turning
- Implementing tank drive
- Software
- Raspbian stretch with desktop
- Python
- Hardware
- Neurosky headset (Borrowing from Dr. De Sa's lab)
- Raspberry Pi 3 (With built-in Bluetooth)
- GoPiGo kit (three-wheel motorized car kit meant to connect to Raspberry Pi)
- Portable charging battery
- Connecting Neurosky to Raspberry Pi over Bluetooth
- Printing to the terminal raw EEG values, concentration values, and meditation values of the user wearing the Neurosky
- Building the GoPiGo
- Using Neurosky output values to map forward/backward movements on the GoPiGo
- Mapping Neurosky outputs to individual wheel motors for left/right movements on the GoPiGo