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Platform development of body area network for gait symmetry analysis using IMU and UWB technology
Mälardalen University, School of Innovation, Design and Engineering.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Having a device with the capability of measure motions from gait produced by a human being, could be of most importance in medicine and sports. Physicians or researchers could measure and analyse key features of a person's gait for the purpose of rehabilitation or science, regarding neurological disabilities. Also in sports, professionals and hobbyists could use such a device for improving their technique or prevent injuries when performing. In this master thesis, I present the research of what technology is capable of today, regarding gait analysis devices. The research that was done has then help the development of a suggested standalone hardware sensor node for a Body Area Network, that can support research in gait analysis. Furthermore, several algorithms like for instance UWB Real-Time Location and Dead Reckoning IMU/AHRS algorithms, have been implemented and tested for the purpose of measuring motions and be able to run on the sensor node device. The work in this thesis shows that a IMU sensor have great potentials for generating high rate motion data while performing on a small mobile device. The UWB technology on the other hand, indicates a disappointment in performance regarding the intended application but can still be useful for wireless communication between sensor nodes. The report also points out the importance of using a high performance micro controller for achieving high accuracy in measurements.

Place, publisher, year, edition, pages
2018. , p. 49
Keywords [en]
BAN, Body Area Network, gait, gait symmetry, gait symmetry analysis, IMU, inertial measurement unit, UWB, Ultra Wide-Band, sensor node, sensors, sensor fusion, electronics, hardware
National Category
Engineering and Technology Electrical Engineering, Electronic Engineering, Information Engineering Embedded Systems Communication Systems Robotics Signal Processing Computer Systems Other Electrical Engineering, Electronic Engineering, Information Engineering Medical Laboratory and Measurements Technologies Medical Equipment Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-39498OAI: oai:DiVA.org:mdh-39498DiVA, id: diva2:1213054
Presentation
2018-06-01, 09:15 (English)
Supervisors
Examiners
Available from: 2018-06-11 Created: 2018-06-04 Last updated: 2018-06-11Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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