**Abstract**

Clinical evaluation of CNS injury patients before and after treatment is an essential step in gait rehabilitation. Medical care of gait disturbance for stroke patients is based on different treatments based on clinical and functional evaluations. Evaluation of gait aims at characterizing the motor performance to provide clinicians with information on the patient's organizational or performance status and to allow them to consider the most appropriate treatment options. A 3D instrumented gait analysis system allows quantification of several parameters at each instant of walking but does not represent gait in daily life conditions. The absence of devices usable in daily life situation constitutes a lack pointed out by clinical practitioners and is at the origin of this work. In the following are described the design and implementation of a wireless embedded system for the collection of spatiotemporal parameters of pathological gait in everyday life. Algorithms estimate joint angles, step length, and gait events and automatically partition data into gait cycles. Experiments have been carried out to accurately evaluate the joint angles, the precision of sensor synchronization, the precision of gait event detection, and the robustness in the case of pathological walk. Comparisons with references given by the 3D instrumented gait analysis system are detailed.

**Keywords:** CNS injury people, stroke patients, gait analysis, spatiotemporal gait parameters, gait event detection, embedded systems
