This paper reports the development and the experimental verification of a new helmet based on the use of a redundant array of accelerometers (ACs) which enables the measurement of angular velocity, angular acceleration and translational $(a−g)$ component of the head during normal activity through an unconstrained workspace. Taking into account the outcome of a numerical simulation previously conducted, a lightweight foam bicycle helmet is equipped with ten biaxial, low-cost MEMS ACs. Validation tests were carried out by means of an instrumented pendulum, which allows the evaluation of the accuracy in the measurement of angular velocity, angular acceleration and $(a−g)$ component over a range of $300deg∕s$, $1300deg∕s2$, and $7m∕s2$. The effects induced by the sensor redundancy in the metrological performances of the helmet were also analyzed; in fact, by adopting an optimal selection criterion, some of the cemented ACs were ignored in the data processing, so that, in addition to the 20 axis configuration, also the clusters equipped by a total number of 18, 16, 14, or 12 sensing axes were analyzed and comparatively examined. The results clearly indicate that the redundancy reduces the effect of the noise level of the single transducers to the acceleration measurements; consequently the bandwidth of the device may be increased, because higher cutoff frequency can be chosen for the low pass filtering. The redundancy is also useful to reduce the angular velocity drift that is further decreased by adopting a drift compensation method. The results of the present experiments revealed that the presented helmet can be considered a viable tool in the measurement of head angular and translational acceleration for the assessment of equilibrium control capability. In case the evaluation of the angular velocity is required, time-limited routine clinical application (few seconds) must be performed due to the presence of relevant drift.

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