Shuai Guo

Iterative Learning Impedance for Lower Limb Rehabilitation Robot

This paper discusses the problem of squatting training of stroke patients. The main idea is to correct the patients training trajectory through an iterative learning control (ILC) method. To obtain better rehabilitation effect, a patient will typically be required to practice a reference posture for many times, while most of active training methods can hardly keep the patients training with correct posture. Instead of the conventional ILC strategy, an impedance-based iterative learning method is proposed to regulate the impedance value dynamically and smartly which will help patients correct their posture gradually and perform better. To facilitate impedance-based ILC, we propose two objectives. The first objective is to find the suitable values of impedance based on the ILC scheme. The second objective is to search the moderate learning convergence speed and robustness in the iterative domain. The simulation and experimental results demonstrate that the performance of trajectory tracking will be improved greatly via the proposed algorithm.

Design and analysis of a novel fall prevention device for lower limbs rehabilitation robot

BACKGROUND Most stroke survivors are suffering from physical motor impairments and confronting with the risk of falls, and well trunk stability is essential for balance during daily functional activities. OBJECTIVES Current fall prevention devices have various limits to the efficient recovery of balance function of the trunk. To provide hemiplegic patients after stroke with the retraining of trunk position sense and a safety environment, a novel fall prevention device is proposed. METHODS Firstly, the structure of the device is introduced and this work is a first effort towards restoring trunk balance function through retraining of trunk position sense. Secondly, the kinematic and static model of the device are developed. Lastly, kinematic and static analysis are carried out to study the motion characteristics, and a contrast experiment was derived to show the effectiveness of robot. RESULTS No obvious difference in balance ability between two groups prior treatment (P> 0.05). Fugl-Meyer assessment in all the cases were improved in different extent (P< 0.05). The robot group had significantly higher Fugl-Meyer scores after treatment than the control group (P< 0.05). CONCLUSIONS The results show that the fall prevention device has good kinematic dexterity within the prescribed workspace and markedly improves balance function.