This paper proposes a novel perspective for the rehabilitation of the finger using a smart exoskeleton gear that combines artificial intelligence (AI) and the internet of things (IoT). The proposed system is designed to aid in the rehabilitation of individuals who have suffered finger paralysis because of neurological disorders or injuries. The exoskeleton is equipped with sensors that collect data on the user's hand movements and transmit it to an AI algorithm. The algorithm then processes the data and generates personalised recovery plans based on the user's specific needs. The IoT aspect of the system allows for remote monitoring and adjustments to the rehab plan as needed. This system has the potential to significantly improve the effectiveness and efficiency of finger rehabilitation while also providing patients with increased autonomy and flexibility. The Internet of Things (IoT) features allow for seamless communication between the user, healthcare experts, and the exoskeleton, which improves the whole rehabilitation process. This research proposes the use of wireless sensor networks (WSNs) in smart exoskeleton systems for tracking and directing mobility during rehabilitation. In the proposed system, WSNs are used to collect data on joint angles, muscle activity, and other biological features. Because of its small size and wireless communication, the WSN allows for real-time monitoring of the user's progress and, if necessary, revision of the rehabilitation plan. technology is perfect for use in a wearable exoskeleton. This strategy has the potential to significantly improve the effectiveness of rehabilitation programs while also allowing for remote monitoring and user changes. Overall, the use of WSNS in smart exoskeleton systems offers a lot of promise for enhancing recovery for those who have mobility disorders or accidents. This study discusses the creation of an exoskeleton finger glove that the user wears to strengthen grip strength. It accomplishes this by locking the user's joint locations so that the user cannot let go unless the exoskeleton gets a release signal from the user. This has applications for people who are physically weaker, such as the elderly or those suffering from neuromuscular illnesses. The node MCU is used to control the signal acquisition using force and flex sensors. The physical exoskeleton was prototyped using Meccano components. The key power requirements of the glove are that its exoskeleton has a holding force of 5 pounds without imposing excessive force on the user's fingertips.

Smart Exoskeleton, AI (Artificialintelligence),IOT (Internet of Things), Paralysis, Rehabilitation, Wireless sensor Network (WSN’s), Real-timemonitoring, Remote monitoring, Node MCU, Meccano components.