Improving Passive Ankle Foot Orthosis System Using Estimated Ankle Velocity Reference

Abstract

This study aims to investigate an appropriate ankle velocity reference (ωref), which is the average ankle velocity of a certain healthy subject when walking with a certain walking speed. The goal is to improve a Passive Controllable Ankle Foot Orthosis (PICAFO) by implementing the ankle velocity reference. Firstly, the function to estimate ωref, based on walking speed and body mass index (BMI), is obtained from 16 able-bodied subjects walking gait data. The effect of controlled stiffness (based on ωref) to the user's ankle kinematics and muscle activity was evaluated by comparing it to other settings, such as walking barefooted and various constant damping stiffness (0%, 30%, 60%, and 100% of the maximum damping stiffness). Two able-bodied subjects (normal and overweight) participated in the evaluation, where they had to walk at two different walking speeds (1 and 2 km/h). The result showed that ankle kinematics and muscle activity were improved when ω was controlled during walking speed of 1 km/h for both subjects. In terms of ankle kinematics, the toe clearance occurred, and walking stability increased. In terms of muscle activity, the average muscle activity had reduced by ~29% for the normal subject and by ~57% for an overweight subject, which shows that PICAFO provides necessary damping stiffness to replace the muscle works partially. In the future, by using the ωref based on walking speed and BMI, the therapists can skip the trial and error process of finding an appropriate PICAFO prescription for a post-stroke patient.

Field oriented control driver development based on BTS7960 for physiotherapy robot implementation

“…Because of that, the open-loop FOC driver shown in this study can be further utilized in developing a physiotherapy robot, such as the previous ankle robot by the authors [14]. However, it is important to note that the required torque for ankle application is at least 1 Nm [18]. The assumption is the robot should be able to lift the foot, which is 1.45% of the body weight [34].…”

“…Sensors are used to monitor the patient's ankle movements, joint angles, and forces exerted during therapy. This information is crucial for the control system to adjust the robot's movements and provide appropriate assistance or resistance during the exercises [18], [19]. Common sensors used in ankle rehabilitation robots include encoders, force sensors, and accelerometers [12], [20].…”

Immediate Effect Evaluation of a Robotic Ankle–Foot Orthosis with Customized Algorithm for a Foot Drop Patient: A Quantitative and Qualitative Case Report

“…The flexion speed or the ankle velocity of each person might be different. A previous study has shown that ankle velocity is related to the body mass index and walking speed [ 22 , 42 ]. Improvement on the control algorithm should consider this ankle velocity reference in each gait phase because it cannot always be constant.…”

“…The supporting scheme or strategy is varied. The flexible AFO [ 16 , 17 , 18 ] and passive controlled AFO [ 19 , 20 , 21 , 22 ] keep the ankle position at a certain angle to avoid the foot drop [ 23 ] or to avoid muscle pain [ 5 , 24 ]. The powered AFO generates ankle movements to force the user to walk normally in several scenarios, such as flat walking [ 25 ], sit-to-standing motions [ 26 ], and ascending and descending stairs [ 27 ].…”