A Novel Approach to Measuring Muscle Mechanics in Vehicle Collision Conditions

Abstract

The aim of the study was to evaluate a novel approach to measuring neck muscle load and activity in vehicle collision conditions. A series of sled tests were performed on 10 healthy volunteers at three severity levels to simulate low-severity frontal impacts. Electrical activity—electromyography (EMG)—and muscle mechanical tension was measured bilaterally on the upper trapezius. A novel mechanical contraction (MC) sensor was used to measure the tension on the muscle surface. The neck extensor loads were estimated based on the inverse dynamics approach. The results showed strong linear correlation (Pearson’s coefficient r¯P = 0.821) between the estimated neck muscle load and the muscle tension measured with the MC sensor. The peak of the estimated neck muscle force delayed 0.2 ± 30.6 ms on average vs. the peak MC sensor signal compared to the average delay of 61.8 ± 37.4 ms vs. the peak EMG signal. The observed differences in EMG and MC sensor collected signals indicate that the MC sensor offers an additional insight into the analysis of the neck muscle load and activity in impact conditions. This approach enables a more detailed assessment of the muscle-tendon complex load of a vehicle occupant in pre-impact and impact conditions.

Estimating the Effects of Awareness on Neck-Muscle Loading in Frontal Impacts with EMG and MC Sensors

“…The dynamic response of the volunteers was comparable to the previous studies of low-severity frontal impacts. The mean head excursion was significantly influenced by the awareness and was decreased for the aware trials to 140.8 ± 38 mm ( Table 1 ), compared to 168 ± 35 mm at the peak deceleration of the sled (2.6 g) in the previous study [ 36 ]. Beeman et al [ 11 , 12 , 13 ] observed a 124 ± 9 mm head excursion at 2.5 g for relaxed volunteers in the driver’s position with the arms acting against the steering wheel.…”

“…This study is based on the experimental data from the sled tests performed and partially described by Krašna et al [ 36 ]. In addition, signal- and data-processing methods are revised for this study.…”

“…Impacts were delivered in the same order for all the volunteers, gradually increasing the dropping height of the sled and the impact severity to prevent the volunteers from possible discomfort. Two sets of low-velocity frontal impacts were completed, Δv = 7.6 ± 0.4 km/h, peak deceleration 1.7 ± 0.1 g. The first set aimed to measure the dynamic response of a volunteer aware of the impact, as partially presented in the previous study [ 36 ], and was processed again for the purpose of this study. In addition, a second measurement set, obtained during the same sled tests, is included for which the volunteers were asked to close their eyes during the pre-impact phase to simulate the dynamic response of an unaware occupant.…”

“…Kinematic data from the motion capture were used for the planar-inverse-dynamics analysis to estimate the neck-muscle loads during the impact [ 13 , 36 , 41 , 42 ]. The head was considered as a rigid body connected to the neck at the occipital condyles (OC).…”

“…The MC signal (indentation force of the tip of the sensor) showed a nearly linear correlation (Pearson’s r = 0.976) with muscle force for isometric contractions [ 35 ]. For eccentric contractions in conditions of low-severity frontal impacts, a Pearson’s r = 0.821 was obtained between the MC signal and the estimated load of the upper trapezius muscle in our previous study [ 36 ].…”