Movement Trainer and Real-time Investigator Alert System: A Learning Factory Project
Functional magnetic resonance imaging (fMRI) is arguably the single most prominent tool for examining the inner-workings of the human brain. FMRI has very high spatial and moderate temporal resolution, allowing for precise localization of function to specific brain regions during experimental tasks. Moreover, given that fMRI images the whole brain at one time, it allows for simultaneous examination of function across widely distributed brain regions, enabling the identification and characterization of functional brain networks.
One key element required for usable fMRI data is for participants to remain very still.Head motion can be a particular concern when imaging developmental or clinical populations, resulting in the need for oversampling specific populations or ages, resulting in additional accrued costs (scan time, researcher time and money, participant time, etc.). Researchers have adopted a number of procedures to help avoid excessive head motion in the scanner, including surrounding the participant’s head with pillows in the radio frequency (RF) head coil. However, even with relatively tight packing, movement still occurs (e.g., the chin will slowly move towards the body as the participant fatigues during the session.)
One idea to potentially mitigate some of these issues related to movement would be to train participants how much movement is “too much” and hence the development to design a device that measures that very movement. The goal of this project is to design a device will monitor head translational (x, y, z) and rotational (roll, pitch, yaw) motion and provide real-time feedback to the participant and investigator (e.g., auditory or visual) if movement exceeded some pre-determined threshold.
A team of undergraduate students in the College of Engineering will design, construct, and test the proposed device.