Click-on-and-Play human motion capture using wearable sensors

Abstract

Human motion capture is often used in rehabilitation clinics for diagnostics and monitoring the effects of treatment. Traditionally, camera based systems are used. However, with these systems the measurements are restricted to a lab with expensive cameras. Motion capture outside a lab, using inertial sensors, is becoming increasingly popular to obtain insight in daily-life activity patterns. There are two main disadvantages of inertial sensor systems. Preparing the measurement system is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. Another disadvantage is that inertial sensors cannot measure relative segment positions directly. Especially relative foot positions are very important to be estimated. Together with the center of mass, these positions can be used to assess the balance of a subject. From these two main disadvantages, the goal of this thesis was derived: Contribute to the development of a click-on-and-play human motion capture system. This should be a system in which the user attaches (clicks) the sensors to the body segments and can start measuring (play) immediately. Therefore, the following sub-goals were defined. The first goal is to develop an algorithm for the automatic identification of the body segments to which inertial sensors are attached. The second goal is to develop a new sensor system, with a minimal number of sensors, for the estimation of relative foot positions and orientations and the assessment of balance during gait. In this thesis it is shown that a click-on-and-play human motion capture system is feasible. A method is presented for the identification of body segments to which inertial sensors are attached. This will reduce errors and set-up time of wearable sensor systems. Furthermore, a gait analysis system is presented with sensors only on the feet. Not only is this system ambulant and easy to use, it is also shown to be accurate for gait analysis and balance assessment.