Exoskeleton robots have recently become popular in manufacturing sectors and rehabilitation facilities as intelligence wearable capacity aid equipment that may decrease lifting pressure and muscle exhaustion. Robotic skeleton has emerged as a resulting in piece of equipment for enhancing able-bodied functioning, assisting people in moving around and restoring misplaced limb characteristics. Using biomimetic approach, the prosthesis can be wear close to the structure and transmits force through driven revolute joints and structural arms. From basic hand biomechanics to actuation technology with motor, a full design and analysis of hand exoskeleton techniques for rehabilitation and supportive engineering uses were made in present work. Our project is meant to carry loads from 5 to 20 kg. Electromyography (EMG) has repeatedly been considered as the driving signal for powered exoskeletons. A lot of effort has gone into developing precise algorithms for estimating muscular torque, but relatively few research have attempted to determine how important an accurate torque estimate is in providing effective movement aid via powered exoskeletons. In this study, we focus on the latter element by employing a basic and low-accuracy torque estimate, an EMG-proportional control, and an elbow exoskeleton to give help. Preliminary results suggest that participants adapt relatively instantly to the support offered by the exoskeleton and can lower their effort while maintaining full control of the movement. © 2025 Elsevier B.V., All rights reserved.