Introduction: Characterization of Whole-Body Vibration (WBV) exposure is important for the development and evaluation of mitigation strategies for occupational WBV. Traditional gold standard accelerometer (GSA) systems can be bulky, expensive, and difficult to implement in real world testing. Recently, relatively inexpensive, compact Inertial Measurement Unit (IMU) devices, which have built-in batteries and memory and are capable of collecting WBV exposure data, have emerged. While the ease of use of these devices may allow for more efficient collection of WBV exposure data, it must be determined if the data collected are comparable to data collected from traditional GSA systems. Methods: Using an accelerometer calibrator, a GSA system and IMU device were used to measure known sinusoidal acceleration inputs of different frequencies (2, 8, 16, 32, 100 Hz) and amplitudes (0.125, 0.25, 0.50, 1.0, 5.0 m/s2). The errors of these measurements to the known values were compared, as well as the inter-tool agreement of the measurements of the systems. The measures under consideration were the unweighted root mean square acceleration (URMS) and weighted acceleration (Aeq). Next, using a shaker table and single axis real-world, random vibration profile inputs collected from an SUV traversing a cobblestone road and a rough bumpy road, parallel measurements were performed with a GSA and IMU. The measures under consideration were the Aeq and vibration dose value (VDV). For both tests, a relative difference in measurements between the two systems of 10% or less was deemed to be an acceptable margin of error. Results: In sinusoidal testing with the accelerometer calibrator, the grand mean unweighted error of the IMU device was -0.081 m/s2 (-7.6%) and fell within the a priori range of acceptable error, with the largest errors occurring at 100 Hz. The grand mean weighted error of the IMU was less than the unweighted error, with a value of 0.006 m/s2 (1.2%). Using Bland-Altman analysis, there was no statistically significant difference in measurements between the IMU device and GSA system with the unweighted measurements (mean difference 0.084 m/s2, p=0.19) or the weighted measurements (mean difference -0.001 m/s2, p=0.95). In the random vibration profile testing, the differences in weighted (Aeq) measurements fell within acceptable ranges with an average difference of 0.06 m/s2 (4.6%). Differences in VDV measurements were also within acceptable ranges with an average difference of 1.2 m/s1.75 (4.1%). Discussion: The IMU device was found to have comparable measurement accuracy to the GSA system in measuring sinusoidal inputs, with relative errors of less than 10% in both URMS and Aeq measurements, and no statistically significant difference in inter-tool agreement between the systems. In the random profile vibration testing, the weighted Aeq and VDV measurement differences between systems were both below the a priori 10% limits. As the weighted vibration values are used when assessing occupational exposures, these results suggest that the IMU device may be an acceptable replacement for GSA systems in measuring occupational vibration exposures.