Development of an economic wireless human motion analysis device for quantitative assessment of human body joint - Ong, Zhi Chao; Seet, Y.C.; Khoo, Shin Yee; Noroozi, Siamak (Elsevier, 2018)
In recent years, the study of human body dynamics has been attracting a significant amount of attention. Currently there are many camera or active sensor based motion analysis systems available on the market. They have been extensively adopted and used by the film and animation or entertainment industries such as film and video game producers. More recently their potential in studying human dynamics/motion for medical purposes has been realised to the extent that they are now used to study full body human biomechanics in the form of gait analysis systems. Most orthopaedic surgeries are usually about joint repair or implants. According health line, revision surgery is usually due to infection, continued pain, joint stiffness, wear, instability, loosening. Apart from infection, the rest can be linked to the operation itself. Currently, surgical planning and placing implants is performed in a subjective manner, relying on the surgeon's experience and instinct, current systems to help the surgeon to place implant are also bulky, expensive, slow and not user friendly. The aim of this project is to develop an economic and portable motion assessment system which involves a wireless inertial measurement unit (IMU) dedicated to study and assess body joints. Through the data collected from the IMU, the system is capable real time measurement of relative position and orientation of the human joint. Several tests were conducted to validate the data extracted from gyroscope and accelerometer of the IMU. The joint motion results analysed using the device was compared with the results analysed using commercial video motion analysis software and it shows good correlation. It is found that the gyroscope of the IMU under DMP sensor fusion algorithm and calibration capability is able to give the angular velocity with less than 5% error. This has led to a more accurate orientation data which gives 7% error in average bending angle.