This study is involved in the development and applicability of a smart rollator. First, this study figured out the user’s gait intention to be applied as a rollator design variable. Next, it proposed a fuzzy control algorithm applying the gait intention, developed a smart rollator to which the proposed algorithm was applied and would understand the function and effectiveness of the proposed algorithm.
In other words, this study conducted kinematic and kinetic evaluations of the human body in the initial gait, an evaluation of the muscles in the lower limb activity, an evaluation of foot pressure, a kinematic evaluation of the human body using an Inertial Measurement Unit (IMU) sensor and an evaluation of the forward displacement of the knee joints in order to check variables related to gait for detecting the gait intention.
Throughout this experiment, this study suggested a method of figuring out the gait intention with just a change in the forward displacement of the knee joints with the variables that could be measured and utilized most simply, of the kinematic, kinetic and physiological variables of the human body related to the gait in walking.
For checking the effectiveness of the proposed variables for detecting the gait intention, input variables of the fuzzy control algorithm proposed as a controller of the smart rollator developed in this include the value of the pressure of holding the smart rollator handles and the value of the forward displacement of the knee joints, and an output variable is the determination of the speed and direction of the electric actuator of the smart rollator. The fuzzy control algorithm proposed in this study was made to measure the gait intention by the input variables and to control the speed and direction of the electric actuator of the smart rollator effectively by the gait intention. It was found that the difference in the distance between the knee joints of 5cm was the optimum for the measurement of the gait intention, and the recognition rate was the highest when the time to measure the gait intention was 560ms.
This study could measure the gait intention related to the intention of the gait of the human body just with two IR distance sensors. This study proposed a fuzzy control algorithm that controls the gait intention data actively and developed a smart rollator which could be used practically. The developed smart rollator consists of functions of a simple rollator, electric wheelchair and fitness trainer, in addition to the function of the smart rollator mode that functionally measures the gait intention. Further, it can measure the gait intention with just the distance sensor, so it is expected that the development of a rollator differentiated from the existing products and the result of a test in various gait environments for normal pedestrians can be effectively used for the gait of the elderly and that this study will be utilized as basic data on the development of products for users with gait abnormality.