Ambulatory motion capture is of great interest for applications ranging for the monitoring of elderly people, sporty performances monitoring, functional rehabilitation, etc. These applications require that the movement is not constrained by an external system, that it can be performed in different situations, including outdoor environment. It requires lightweight and low cost equipment; it must be truly ambulatory without complex process of calibration.Currently, only systems using an exoskeleton or inertial modules (often combined with magnetic modules) can be used in such situations. Unfortunately, the exoskeleton weight is not affordable and it imposes constraints on the movements of the person, which makes it unusable for certain applications such as monitoring of the elderly.Inertial technology is lighter. Itcan be used for the capture of movement without constraints on the capture space or on the movements. However, it suffers from gyros drift, and the system must be recalibrated.The objective of this thesis is to develop a system of motion capture for an articulated chain, low-cost, real-time truly ambulatory that does not require specific capture infrastructure, that can be used in many application fields (rehabilitation, sport, leisure, etc.).We focus on intra-corporal measurements. Thus, all sensors are placed on the body and no external device is used. In addition to a final demonstrator to validate the proposed approach, we also develop tools to evaluate the system in terms of technology, number and position of sensors, but also to evaluate different algorithms for data fusion. To do this, we use the Cramer-Rao lower bound. \The subject is multidisciplinary. It addresses aspects of modelling and design of fully ambulatory hybrid systems. It studies estimation algorithms adapted to the field of motion capture of a whole body by considering the problem of observability of the state and taking into account the biomechanical constraints that can be taken into account. Thus, with an appropriate treatment, the pose of a subject can be reconstructed in real time from intra-body measurements.
