The human hand’s complex structure enables a large number of degrees of freedom with an inherent supple nature and ability to subtly control separate digits simultaneously. Evolution and skill development have played a key role in the individualization of the hand control over separate digits, pushing the boundaries created by the neuromuscular constraints, which physically imposes the dependency of motion between digits of the hand. The hand is miraculously capable of the singulation of the fingers’ actuation and control of grasping behavior over the wide range between precision to power grip, even between delicate and coarse manipulation, allowing the hand to perform highly sophisticated tasks involving a high degree of sensitivity, adaptability and productivity. For the design of an anthropomorphic prosthetic hand, it is essential to consider the replication of the hand structure and high ability of adaptation needs resulting from the large number of degrees of freedom within the human hand. However, such a hand may require up to 24 degrees of freedom for a typical hand replica. In order to reduce the number of actuators for an anthropomorphic prosthetic hand, Principal Components Analysis (PCA) has been implemented, which resulted in a selection of seven actuators contributing to 74.45% of the dataset. The dataset is formed by the capturing of hand poses from both Intel RealSense Camera system and Leapmotion controller stereo cameras, through Kalman filter data fusion for the captured frames.