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

Critical traffic situations, such as vehicle collisions and emergency manoeuvres, can cause an occupant to respond with reflex and voluntary actions. These affect the occupant’s position and dynamic loading during interactions with the vehicle’s restraints, possibly compromising their protective function. Electromyography (EMG) is a commonly used method for measuring active muscle response and can also provide input parameters for computer simulations with models of the human body. The recently introduced muscle-contraction (MC) sensor is a wearable device with a piezo-resistive element for measuring the force of an indenting tip pressing against the surface of the body. The study aimed to compare how data collected simultaneously with EMG, video motion capture, and the novel MC sensor are related to neck-muscle loading. Sled tests with low-severity frontal impacts were conducted, assuming two different awareness conditions for seated volunteers. The activity of the upper trapezius muscle was measured using surface EMG and MC sensors. The neck-muscle load F was estimated from an inverse dynamics analysis of the head’s motion captured in the sagittal plane. The volunteers’ response to impact was predominantly reflexive, with significantly shorter onset latencies and more bracing observed when the volunteers were aware of the impact. Cross-correlations between the EMG and MC, EMG and F, and F and MC data were not changed significantly by the awareness conditions. The MC signal was strongly correlated (r = 0.89) with the neck-muscle loading F in the aware and unaware conditions, while the mean ΔF-MC delays were 21.0 ± 15.1 ms and 14.6 ± 12.4 ms, respectively. With the MC sensor enabling a consistent measurement-based estimation of the muscle loading, the simultaneous acquisition of EMG and MC signals improves the assessment of the reflex and voluntary responses of a vehicle’s occupant subjected to low-severity loading.