Motion analysis is a technique used by clinicians (among many others) that quantifies human movement by using camera-based systems. Marker-based motion analysis systems have been used across a variety of application domains, from Interactive 3D TeleImmersion (i3DTI) environments to the diagnosis of neuromuscular and musculoskeletal diseases. Although such analysis is performed in several laboratories in many countries, numerous issues exist: (1) the high cost of precise motion capture systems; (2) scarcity of qualified personnel to operate them; (3) expertise required to interpret their results; (4) space requirements to install and store these systems; (5) complexity in terms of measurement protocol required for such systems; (6) limited availability; (7) and in some situations the use of markers means they are unsuitability for certain clinical use cases (e.g. for patients recovering from orthopaedic surgery). In this paper, we present, from a system perspective, an alternative, cheaper, and more accessible system for motion analysis. The ultimate aim is to use the output of this multimodal marker-less system as part of an immersive multimedia gait re-education tool. In real-time, it will advise the user on their gait performance (as well as potentially providing accurate clinical data to clinicians). With the initial focus on the capture system, we have developed and evaluated a novel multimodal system which integrates Multiple Microsoft Kinects (which employ RGB-D cameras) with multiple Shimmer Inertial Measurement Unit (IMU) sensors. We have compared this system with the VICON system (the gold standard in motion capture). Our marker-less motion capture system combines data from 4 skeletons generating 3D and complete 360 degrees in view skeleton. The system combines unit quaternions from each Kinect joint with quaternions from 4 inertial measurement units to promote integration. We used our system to measure 3D points of 12 joints from the Kinect fused skeleton and flexion-extension angles of the knee and hip in a walking trial in 8 participants with 8-10 trials per participant. The analysis found component similarity of 0.97 for knee angles and 0.98 for hip angles. These results show that our system, through combination of Multi Kinect system and Shimmer IMUs, offers a cheaper, sufficiently accurate and more accessible human motion analysis system