Design And Implementation Of Humancomputer Interaction Control System For Lower-limb Exoskeleton Rehabilitation Robot

As the population ages and the incidence of stroke and disability increases each year,the number of people with lower limb mobility impairment has risen dramatically.Traditional rehabilitation training methods require patients to undergo intense and repetitive training with the help of one or even more caregivers.While there is a high demand for rehabilitation of patients with lower limb motor dysfunction due to brain injury,spinal cord injury and other factors,there is a relative shortage of specialist rehabilitation practitioners,resulting in many patients not receiving timely treatment.The emergence of lower limb exoskeletal rehabilitation robots has not only reduced the burden on rehabilitation practitioners,but also reduced the physical and psychological burden on patients,and improved the efficiency and effectiveness of rehabilitation training.Some breakthroughs have been made in this field,but the safety,intelligence and lightness of human-robot interaction still need to be given priority.The design of the rehabilitation robot needs to be softly controlled for safety issues during human-machine interaction.The rehabilitation robot is in direct contact with the patient’s lower limbs while the patient is undergoing rehabilitation.When the humanmachine interaction torque suddenly increases,it is easy to cause secondary injuries to the patient.Therefore,the impedance control algorithm is studied in this topic,and the angle and speed of each joint movement of the robot is adjusted in real time by designing adaptive stiffness and adaptive damping control laws,so that it can show equivalent flexibility externally and ensure the safety of the patient.To address the issue of intelligent human-robot interaction,patient rehabilitation is quantified.The rehabilitation assessment scales commonly used in medicine often pass the subjective judgement of rehabilitation practitioners and lack objective evaluation indicators.Therefore,this project designs a rehabilitation assessment method based on plantar pressure abnormality detection,which supports the vector data description algorithm to detect the patient’s plantar pressure,determine the patient’s rehabilitation degree according to the proportion of abnormal data,and quantify the patient’s rehabilitation situation,so that the rehabilitation physician and the patient can understand the rehabilitation progress more intuitively.To address the issue of lightweight human-computer interaction,a compact and lightweight human-computer interaction system is designed.The use of a PC as the host computer for the HCI system is inconvenient and costly to move around.Therefore,this project designs an Android client-based HCI system.Using modular programming ideas,the functional framework of the HCI system is constructed,and the interface and functions of each functional module are designed and implemented in turn,and targeted rehabilitation training strategies are designed for patients in different rehabilitation periods,making the HCI system more flexible and convenient to use and reducing the burden of This makes the HCI system more flexible and convenient to use,and reduces the burden on rehabilitation practitioners.The experimental platform was also built to verify the effectiveness and stability of the system.