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Development of a smart insole tracking system for physical therapy and athletics

Published: 27 May 2014 Publication History

Abstract

Development of a smart insole tracking system is described. Originally designed for healthcare applications, the system has found applications in both physical therapy and athletic training. The entire system is distributed between insole hardware, mobile device applications that interface with the insoles and a central Internet server for data warehousing and analysis. We describe the development of these components so far including a discussion of custom algorithm development required for the system. The athletic version has been commercialized while the more complex healthcare version is still under development.

References

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Bamberg, S., et al. Gait Analysis Using a Shoe-Integrated Wireless Sensor System. In IEE Transactions on Information Technology in Biomedicine, 12, 4 (July 2008), 413--423.
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Brooks, Kelly. Remote Performance Measurement and Monitoring: RPM2 Device Validation. In Journal of Sports and Human Performance, 1, 2 (2013), 4 pages. DOI=http://journals.tdl.org/jhp/index.php/JHP/article/view/8.
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Mitchell, T. Machine Learning. McGraw-Hill, 1997.
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Park, S., et al. Comparison of Sensor Systems for Gait Phase Detection in Hemiplegic Gait, World Congress on Medical Physics and Biomedical Engineering (Munich, Germany, September 7--12), IFMBE Proceedings, 25, 9 (September 2009), 358--361.
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Wang, H., and Song, M. "Ckmeans.1d.dp: Optimal k-means clustering in one dimension by dynamic programming." The R Journal, 3, 2 (December 2011), 16--21.
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Watanabe, T., and Minegishi, Y. A Test of Stride Length Measurement with an Accelerometer and a Gyroscope Attached on the Foot. World Congress on Medical Physics and Biomedical Engineering (Munich, Germany, September 7--12), IFMBE Proceedings, 25, 9 (September 2009), 502--505.

Cited By

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  • (2024)Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation SensorCureus10.7759/cureus.59801Online publication date: 7-May-2024
  • (2023)Activity Recognition Using Different Sensor Modalities and Deep LearningApplied Sciences10.3390/app13191093113:19(10931)Online publication date: 2-Oct-2023
  • (2023)Design, Optimization and Fabrication of a Sensorized-Insole using Taguchi Method2023 30th National and 8th International Iranian Conference on Biomedical Engineering (ICBME)10.1109/ICBME61513.2023.10488662(398-404)Online publication date: 30-Nov-2023
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  1. Development of a smart insole tracking system for physical therapy and athletics

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    Published In

    cover image ACM Other conferences
    PETRA '14: Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments
    May 2014
    408 pages
    ISBN:9781450327466
    DOI:10.1145/2674396
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • iPerform Center: iPerform Center for Assistive Technologies to Enhance Human Performance
    • CSE@UTA: Department of Computer Science and Engineering, The University of Texas at Arlington
    • HERACLEIA: HERACLEIA Human-Centered Computing Laboratory at UTA
    • U of Tex at Arlington: U of Tex at Arlington
    • NCRS: Demokritos National Center for Scientific Research
    • Fulbrigh, Greece: Fulbright Foundation, Greece

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 27 May 2014

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    Author Tags

    1. mobile applications
    2. physical therapy
    3. sensors
    4. tracking

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    PETRA '14
    Sponsor:
    • iPerform Center
    • CSE@UTA
    • HERACLEIA
    • U of Tex at Arlington
    • NCRS
    • Fulbrigh, Greece

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    Cited By

    View all
    • (2024)Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation SensorCureus10.7759/cureus.59801Online publication date: 7-May-2024
    • (2023)Activity Recognition Using Different Sensor Modalities and Deep LearningApplied Sciences10.3390/app13191093113:19(10931)Online publication date: 2-Oct-2023
    • (2023)Design, Optimization and Fabrication of a Sensorized-Insole using Taguchi Method2023 30th National and 8th International Iranian Conference on Biomedical Engineering (ICBME)10.1109/ICBME61513.2023.10488662(398-404)Online publication date: 30-Nov-2023
    • (2022)Smart insoles review (2008-2021): Applications, potentials, and futureSmart Health10.1016/j.smhl.2022.10030125(100301)Online publication date: Sep-2022
    • (2021)Towards Supporting Data-Driven Practices in Stroke Telerehabilitation TechnologyProceedings of the ACM on Human-Computer Interaction10.1145/34490995:CSCW1(1-33)Online publication date: 22-Apr-2021
    • (2019)GymSolesProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300404(1-12)Online publication date: 2-May-2019
    • (2017)A.1D-CApplied Soft Computing10.1016/j.asoc.2016.09.00152:C(1200-1209)Online publication date: 1-Mar-2017

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