This study investigates the influence of immersive virtual reality environments and gamification on the classification of imaginary motor (MI) signals and the associated increase in energy in the motor cortex region for neurorehabilitation purposes. Two immersive virtual environments, indoor and outdoor, were selected, each with gamified and non-gamified scenarios. Event-Related Desynchronization (ERD) data underwent analyses to determine if there were significant differences in ERD levels between distinct age groups and whether Fully Immersive Virtual Reality (FIVR) environments induced notable energy increases. The initial analysis found no significant energy changes between age groups under constant environmental conditions. In the second analysis, FIVR environments did not lead to a statistically significant increase in cortical energy for the 21–24 age group (Group I). However, a notable difference in cortical energy increase was identified between gamified and non-gamified environments within the 32–43 age group (Group II). The study also explored the impact of environmental factors on MI signal classification using four deep learning algorithms. The Recurrent Neural Network (RNN) classifier exhibited the highest performance, with an average accuracy of 86.83%. Signals recorded indoors showed higher average classification performance, with a significant difference observed among age groups. Group I participants performed better in non-gamified environments (88.8%), while Group II achieved high performance indoors, especially in the gamified scenario (93.6%). Overall, the research underscores the potential of immersive virtual environments and gamification in enhancing MI signal classification and cortical energy increase, with age and environmental factors influencing the outcomes.