Imu-based online load spectrum estimation for human knee-joint

Directing to knee joint injury in the elderly, this paper proposes a multi sensor based dynamic online load spectrum estimation for human knee-joint. Most of existing researches focused on the metabolic marker during joint damage process while people’s walking and sports habits influence the injury of knee joint seriously. Through developing a wireless and wearable prototype inertial measurement unit (IMU) with accelerometer and gyroscope, this paper continuously captures the human daily motion data and obtains the load spectrum of knee joints. Using dynamic output of inertial measurement unit and human physical data, the mathematic model of human knee joint under load spectrum is established. Considering the influence of various motions, the proposed model is modified by the experimental data under running, jumping, and jogging. The analysis and experimental results show that human knee injury is closely related to the exercise style and habits. With online load spectrum measuring, the proposed model can estimate the knee joint damage process and give its remaining useful life prediction to the elderly when the knee joint has been damaged. Furthermore, the proposed estimation also can guide the design of artificial joint.