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Wearable Sensor Integration and Bio-motion Capture: A Practical Perspective

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Body Sensor Networks

Abstract

In the previous chapters, we have discussed the fundamentals of BSN hardware and processing techniques including multi-sensor fusion, context aware and autonomic sensing. In this chapter, we will use bio-motion analysis as an exemplar to demonstrate how some of these methods are used for practical applications involving multiple wearable sensors.

Motion Capture (Mocap) and reconstruction is the process of recording the general body movement of a human subject or living being and translating the movement onto a 3D model such that the model performs the same actions as the subject (De Aguiar E, Theobalt C, Stoll C, Seidel HP. Marker-less deformable mesh tracking for human shape and motion capture. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp 1–9, 2007). The Mocap technology has been used for a variety of applications, from delivering realistic animation in filming and entertainment to assessing the performance of professional athletes. Clinically, motion reconstruction systems are increasingly used to analyse the biomechanics of patients. The analysis provides an objective measure of physical function to aid interventional planning, evaluate the outcomes of surgical procedures and assess the efficacy of treatment and rehabilitation (King and Paulson Computer 40(9):13–16, 2007; Wong C, Zhang Z, Kwasnicki R, Liu J, and Yang GZ. Motion Reconstruction from Sparse Accelerometer Data Using PLSR, In: Proceedings of ninth International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp 178–183, 2012). Thus far, a number of motion-tracking technologies have been developed and they can be mainly classified as optical tracking, mechanical tracking and inertial-sensor based tracking systems (Yun and Bachmann IEEE Transactions on Robotics 22(6): 1216–1227, 2006).

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Authors and Affiliations

  1. The Hamlyn Centre, Imperial College London, London, SW7 2BY, UK

    Zhiqiang Zhang, Athanasia Panousopoulou & Guang-Zhong Yang PhD

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  1. Zhiqiang Zhang
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  2. Athanasia Panousopoulou
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  3. Guang-Zhong Yang PhD
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Correspondence to Guang-Zhong Yang PhD .

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Editors and Affiliations

  1. Director and Co-Founder,The Hamlyn Centre, Imperial College London, London, United Kingdom

    Guang-Zhong Yang

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Zhang, Z., Panousopoulou, A., Yang, GZ. (2014). Wearable Sensor Integration and Bio-motion Capture: A Practical Perspective. In: Yang, GZ. (eds) Body Sensor Networks. Springer, London. https://doi.org/10.1007/978-1-4471-6374-9_12

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  • DOI: https://doi.org/10.1007/978-1-4471-6374-9_12

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