A simple 5-DoF MR-compatible motion signal measurement system

Abstract

The purpose of this study was to develop a simple motion measurement system with magnetic resonance (MR) compatibility and safety. The motion measurement system proposed here can measure 5-DoF motion signals without deteriorating the MR images, and it has no effect on the intense and homogeneous main magnetic field, the temporalgradient magnetic field (which varies rapidly with time), the transceiver radio frequency (RF) coil, and the RF pulse during MR data acquisition. A three-axis accelerometer and a twoaxis gyroscope were used to measure 5-DoF motion signals, and Velcro was used to attach a sensor module to a finger or wrist. To minimize the interference between the MR imaging system and the motion measurement system, nonmagnetic materials were used for all electric circuit components in an MR shield room. To remove the effect of RF pulse, an amplifier, modulation circuit, and power supply were located in a shielded case, which was made of copper and aluminum. The motion signal was modulated to an optic signal using pulse width modulation, and the modulated optic signal was transmitted outside the MR shield room using a high-intensity light-emitting diode and an optic cable. The motion signal was recorded on a PC by demodulating the transmitted optic signal into an electric signal. Various kinematic variables, such as angle, acceleration, velocity, and jerk, can be measured or calculated by using the motion measurement system developed here. This system also enables motion tracking by extracting the position information from the motion signals. It was verified that MR images and motion signals could reliably be measured simultaneously.

Development of an fMRI-compatible driving simulator with simultaneous measurement of physiological and kinematic signals: The multi-biosignal measurement system for driving (MMSD)

“…Angle information is extracted by numerically integrating the angular velocity signals from the 2-axis gyrosensor by the Runge-Kutta method [24]. Various additional kinematic signals such as velocity and jerk can be calculated from acceleration and angle information [5,22].…”

“…Studies have observed autonomic nervous-system variables that change during driving, such as skin conductance level (SCL) and photoplethysmographic (PPG) readouts of heart activity, via sensors attached to the hands or wrists [20,21]. Moreover, ultra-high speed cameras and inertial measurement units (IMUs; i.e., sensors) are now available to extract variables related to human body movement while driving, measure the manipulation angle and acceleration of steering wheels, and measure the variability of accelerator-and brake-pedal [22,23].…”