Title page for ETD etd-05062010-100653


Type of Document Dissertation
Author Shaban, Heba Ahmed
Author's Email Address hshaban@vt.edu
URN etd-05062010-100653
Title A Novel Highly Accurate Wireless Wearable Human Locomotion Tracking and Gait Analysis System via UWB Radios
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Buehrer, Richard Michael Committee Co-Chair
El-Nasr, Mohamad Abou Committee Co-Chair
Reynolds, Marion R. Jr. Committee Member
Riad, Sedki Mohamed Committee Member
Shukla, Sandeep K. Committee Member
Keywords
  • and Wireless healthcare
  • Ultra wideband (UWB) transceivers
  • Sensor-fusion
  • Power consumption
  • Performance analysis
  • Gait analysis
  • Body area networks (BAN)
Date of Defense 2010-04-29
Availability unrestricted
Abstract
Gait analysis is the systematic study of human walking. Clinical gait analysis is the process by which quantitative information is collected for the assessment and decision-making of any gait disorder. Although observational gait analysis is the therapist’s primary clinical tool for describing the quality of a patient’s walking pattern, it can be very unreliable. Modern gait analysis is facilitated through the use of specialized equipment. Currently, accurate gait analysis requires dedicated laboratories with complex settings and highly skilled operators. Wearable locomotion tracking systems are available, but they are not sufficiently accurate for clinical gait analysis. At the same time, wireless healthcare is evolving. Particularly, ultra wideband (UWB) is a promising technology that has the potential for accurate ranging and positioning in dense multi-path environments. Moreover, impulse-radio UWB (IR-UWB) is suitable for low-power and low-cost implementation, which makes it an attractive candidate for wearable, low-cost, and battery-powered health monitoring systems. The goal of this research is to propose and investigate a full-body wireless wearable human locomotion tracking system using UWB radios. Ultimately, the proposed system should be capable of distinguishing between normal and abnormal gait, making it suitable for accurate clinical gait analysis.
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