Unrestrained measurement of arm motion based on a wearable wireless sensor network

Measurement of human body motion has a myriad of applications ranging from gaming, rehabilitation, animation, virtual reality, sports science and surveillance. Existing methods of motion tracking include visual, mechanical, magnetic and inertial tracking. Visual methods require line of sight and suf...

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Bibliographic Details
Main Author: Lee, Guo Xiong
Other Authors: Low Kay Soon
Format: Theses and Dissertations
Language:English
Published: 2012
Subjects:
Online Access:https://hdl.handle.net/10356/50766
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Institution: Nanyang Technological University
Language: English
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Summary:Measurement of human body motion has a myriad of applications ranging from gaming, rehabilitation, animation, virtual reality, sports science and surveillance. Existing methods of motion tracking include visual, mechanical, magnetic and inertial tracking. Visual methods require line of sight and suffer from the notorious occlusion problem. For the existing mechanical or inertial tracking methods, they have cumbersome wiring which hinder the natural movements. In this thesis, a wearable wireless sensor network using inertial/ magnetic sensors is developed to overcome the limitations of these existing methods. Using tri-axial accelerometer as the sole sensor will lead to singularity when the heading axis is vertical, restricting measurement of orientation to half a vertical plane. A new factorized quaternion approach is proposed in this research to overcome this deficiency with consideration of anatomical and sensor constraints. Different from the conventional approach based on single angle-axis quaternion, the proposed approach factorizes the quaternion into two principal axis quaternions corresponding to two equivalent arm motions. This allows for the implementation of anatomical arm constraints that match the range of arm motion and reduces the ambiguity in solutions. In addition, the singularities arising from the use of tri-axial accelerometers can be detected and resolved for a transient state. A novel algorithm based on elevation and heading angles is also proposed to determine the orientation of a sensor node equipped with tri-axial accelerometer, gyroscope and magnetometer. Compared to Euler angles, the fixed elevation and heading angles are independent on the temporal order of rotations. In addition, the fixed elevation and heading angles are observable and thus more intuitively visualized. External acceleration due to the rotation of the human arm segment is estimated using the gyroscope and compensated in the accelerometer output. As the magnetometer is easily affected by magnetic disturbances caused by electrical appliances and ferrous materials, it is decoupled from the accelerometer and used solely for the determination of heading. A new singularity avoidance method is also proposed to resolve the singularity problem that may arise, thereby allowing for measurement through all possible orientations. Experiments have been performed to evaluate the proposed wearable wireless sensor network in terms of accuracy, latency and power consumption. Experimental results show that the proposed factorized quaternion approach is able to resolve transient singularities and ambiguity arising from the use of triaxial accelerometer. Performance of the novel elevation and heading algorithm is also comparable to an indirect Kalman Filter at a reduced computational cost. The implementation of a singularity avoidance strategy makes the algorithm suitable for implementation in a fixed-point processor. Magnetic disturbances affect only the accuracy of the heading angle and not the elevation angles.