Motion Capture Sensing Technologies and Techniques: A Sensor Agnostic Approach to Address Wearability Challenges

Abstract

AbstractBody area sensing systems specifically designed for motion capture need to consider the wearer’s comfort and wearability criteria. In this paper, after studying body models and their approximation by link-segment models, the kinematics and inverse kinematics problems for determining motion are explored. Different sensor technologies and related motion capture systems are then discussed within the context of wearability and portability challenges of the systems. For such systems, the weight and size of the system need to be kept small and the system should not interfere with the user’s movements. The requirements will be considered in terms of portability: portable motion capture systems should be less sensitive in accurate positioning of sensors and have more battery lifetime or less power consumption for their wider adoption as an assisted rehabilitation platform. Therefore, a proposed signal processing technique is validated in a controlled setting to address the challenges. By reducing sampling frequency, the power consumption will be reduced but there would be more variability in data whereas by utilising an adaptive filtering approach the variation can be compensated for. It is shown how by using the technique it is possible to reduce the energy consumption; therefore, the potential to decrease the battery size leading to a less bulky on-body sensing system with more comfort to the wearer.