Search Results

Soft-tissue vibrations can be used to quantify selected properties of human tissue and their response to impact. Vibrations are typically quantified using high-speed motion capture or accelerometry. The aim of this study was to compare the amplitude and frequency of soft-tissue vibrations during running when quantified by highspeed motion capture and accelerometry simultaneously. This study showed: (a) The estimated measurement errors for amplitude and frequency were of the same order of magnitude for both techniques. (b) There were no significant differences in the mean peak frequencies and peak amplitudes measured by the two methods. (c) The video method showed an inability to capture high frequency information. This study has shown that a tradeoff has to be made between the accuracy in amplitude and frequency when these methods are employed to quantify soft tissue vibrations in running.

We increased the accuracy of an instrumented treadmill’s measurement of center of pressure and force data by calibrating in situ and optimizing the transformation between the motion capture and treadmill force plate coordinate systems. We calibrated the device in situ by applying known vertical and shear loads at known locations across the tread surface and calculating a 6 × 6 calibration matrix for the 6 output forces and moments. To optimize the transformation, we first estimated the transformation based on a locating jig and then measured center-of-pressure error across the treadmill force plate using the CalTester tool. We input these data into an optimization scheme to find the transformation between the motion capture and treadmill force plate coordinate systems that minimized the error in the center-of-pressure measurements derived from force plate and motion capture sources. When the calibration and transformation optimizations were made, the average measured error in the center of pressure was reduced to approximately 1 mm when the treadmill was stationary and to less than 3 mm when moving. Using bilateral gait data, we show the importance of calibrating these devices in situ and performing transformation optimizations.

The objective quantification of three-dimensional kinematics during different functional and occupational tasks is now more in demand than ever. The introduction of new generation of low-cost passive motion capture systems from a number of manufacturers has made this technology accessible for teaching, clinical practice and in small/medium industry. Despite the attractive nature of these systems, their accuracy remains unproved in independent tests. We assessed static linear accuracy, dynamic linear accuracy and compared gait kinematics from a Vicon MX-f20 system to a Natural Point OptiTrack system. In all experiments data were sampled simultaneously. We identified both systems perform excellently in linear accuracy tests with absolute errors not exceeding 1%. In gait data there was again strong agreement between the two systems in sagittal and coronal plane kinematics. Transverse plane kinematics differed by up to 3° at the knee and hip, which we attributed to the impact of soft tissue artifact accelerations on the data. We suggest that low-cost systems are comparably accurate to their high-end competitors and offer a platform with accuracy acceptable in research for laboratories with a limited budget.