Seats and cushions can attenuate whole-body vibration (WBV) exposures and minimize health risks for heavy machine operators. We successfully developed neural network (NN) algorithms to identify the vibration attenuation properties for four different seating conditions (seat/cushion combinations), and implemented each of the NN models to predict the equivalent daily exposure A(8) values for various vehicles in the forestry and mining environments. We also evaluated the performance of the new prototype No-Jolt™ air-inflated cushion and the original cushion of each seat with jolt exposures. We observed that the air cushion significantly improved the vibration attenuation properties of the seat that initially had good performance, but not for the seat that had relatively poor vibration attenuation properties. In addition, operator's anthropometrics and sex influenced the performance of the air-inflated cushion when the vibration environment included jolt exposures.
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