Driven by recent advances in machine learning, decreasing hardware costs, improving sensor quality and fidelity, and the growing demand for teleoperation systems in robotic research, surgical robotics, and high-precision manufacturing, this project addresses the limitations of current commercial solutions, which are often expensive, produce low-quality data, and are kinematically mismatched to the human hand. It aims to design a low-cost, PLA 3D-printed, human-centered exoskeleton interface featuring a dry-fit assembly and accurate kinematic alignment with the human hand. The system will capture high-fidelity finger motion data to enable intuitive teleoperation and support machine learning applications.