Large impact force is generated as the large capacity shovel loads 100 tons of material into the dump truck, which in-turn generates high-frequency shockwaves that travels through the truck body, chassis and exposes the operator to whole body vibrations (WBV). Real-time tracking is required for this dynamic impulse force on the truck body which is the sole cause for these vibrations. Therefore, in current work, state-of-the-art machine learning algorithms Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been implemented to track the generation and progression of this dynamic force during a shovel dumping operation. With efficient and realtime tracking, appropriate steps will be taken for minimizing the resulting vibrations and thus improving the operator's health and safety.