2-Point Error Estimation Algorithm for 3-D Thigh and Shank Angles Estimation Using IMU

Abstract

Inertial measurement units (IMUs) have been widely used for many applications such as aircrafts, gaming, animation, and sports. However, the use of IMU in medical diagnosis is still largely unexplored. A great deal of researcher has focused on estimating the pitch angle using accelerometer and gyroscope, while some researchers managed to estimate the roll angle, not many researchers have extended their research to estimate the yaw angle. For those who estimate the yaw angle, the utilization of magnetometer is common, but it requires a more complex algorithm to tackle the magnetic interference. This paper presents an innovative method, called the 2-point error estimation algorithm, to estimate the pitch, roll, and yaw angles using the accelerometer and gyroscope-only. The proposed algorithm is also very computationally efficient to estimate 3-D angles as only two 'atan2()' functions are computed throughout the whole walking motion, and seven additions and four multiplications for each angle estimated. The accuracy of the 3-D angles estimated using the IMU is validated against the gold standard Vicon optical motion capture system. The proposed algorithm gives a low average root mean square error of 2.9°, 3.6°, and 4.2° for flexion/extension (pitch), adduction/abduction (roll), and internal/external rotation (yaw) angles of the thigh and shank, respectively. The proposed algorithm can be used to design a low-cost 3-D gait evaluation system.