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Research Article

Mobile gait analysis via eSHOEs instrumented shoe insoles: a pilot study for validation against the gold standard GAITRite®

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Pages 375-386 | Received 25 Aug 2016, Accepted 09 Apr 2017, Published online: 02 Jun 2017

References

  • Andriacchi TP, Alexander EJ. Studies of human locomotion: past, present and future. J Biomech. 2000;33:1217–1224.
  • Sudarsky L. Geriatrics: gait disorders in the elderly. N Engl J Med. 1990;322:1441–1446.
  • Perry J. Gait analysis: normal and pathological function. 1st ed. Thorofare (NJ): Slack Incorporated; 1992.
  • Vaughan CL, Davis BL, O’Connor JC. Dynamics of human gait. 2nd ed. Cape Town: Kiboho Publishers; 1992.
  • Götz-Neumann K. Gehen verstehen: ganganalyse in der physiotherapie. [Understanding gait: gait analysis in physiotherapy]. 2nd ed. Stuttgart (GER): Georg Thieme Verlag; 2003.
  • Öberg K. Basic gait parameters: reference data for normal subjects, 10-79 years of age. J Rehabil Res Dev. 1993;30:210–223.
  • Auvinet B, Chaleil D, Barrey E. Accelerometric gait analysis for use in hospital outpatients. Rev Rhum Engl Ed. 1999;66:389–397.
  • Moe-Nilssen R, Helbostad JL. Estimation of gait cycle characteristics by trunk accelerometry. J Biomech. 2004;37:121–126.
  • Muro de la Herran A, Garcia-Zapirain B, Mendez-Zorrilla A. Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications. Sensors (Basel) 2014;14:3362–3394.
  • Kidder SM, Abuzzahab FS, Harris GF, et al. A system for the analysis of foot and ankle kinematics during gait. IEEE Trans Rehab Eng. 1996;4:25–32.
  • Hansen AH, Childress DS, Meier MR. A simple method for determination of gait events. J Biomech. 2002;35:135–138.
  • Menz HB, Latt MD, Tiedemann A, et al. Reliability of the GAITRite walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait Posture. 2004;20:20–25.
  • Hausdorff JM, Ladin Z, Wei JY. Footswitch system for measurement of the temporal parameters of gait. J Biomech. 1995;28:347–351.
  • Aminian K, Rezakhanlou K, De Andres E, et al. Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty. Med Biol Eng Comput. 1999;37:686–691.
  • Mariani B, Hoskovec C, Rochat S, et al. 3D gait assessment in young and elderly subjects using foot-worn inertial sensors. J Biomech. 2010;43:2999–3006.
  • Schwesig R, Leuchte S, Fischer D, et al. Inertial sensor based reference gait data for healthy subjects. Gait Posture. 2011;33:673–678.
  • Barth J, Klucken J, Kugler P, et al. Biometric and mobile gait analysis for early diagnosis and therapy monitoring in Parkinson’s disease. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:868–871.
  • Greene BR, McGrath D, O’Neill R, et al. An adaptive gyroscope-based algorithm for temporal gait analysis. Med Biol Eng Comput. 2010;48:1251–1260.
  • Mayagoitia RE, Nene AV, Veltink PH. Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. J Biomech. 2002;35:537–542.
  • Pappas IP, Popovic MR, Keller T, et al. A reliable gait phase detection system. IEEE Trans Neural Syst Rehabil Eng. 2001;9:113–125.
  • Pappas IP, Keller T, Mangold S, et al. A reliable gyroscope-based gait-phase detection sensor embedded in a shoe insole. IEEE Sensors J. 2004;4:268–274.
  • Morris SJ, Paradiso JA. Shoe-integrated sensor system for wireless gait analysis and real-time feedback. Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint; 2002. p. 2468–2469.
  • Morris-Bamberg SJ, Benbasat AY, Scarborough DM, et al. Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans Inf Technol Biomed 2008;12:413–423.
  • Stirling R, Fyfe K, Lachapelle G. Evaluation of a new method of heading estimation for pedestrian dead reckoning using shoe mounted sensors. J Navigation. 2005;58:31–45.
  • Yun X, Bachmann ER, Moore H, et al. Self-contained position tracking of human movement using small inertial/magnetic sensor modules. Proceedings 2007 IEEE International Conference on Robotics and Automation, Roma; 2007. p. 2526–2533.
  • Braun BJ, Bushuven E, Hell R, et al. A novel tool for continuous fracture aftercare - Clinical feasibility and first results of a new telemetric gait analysis insole. Injury. 2016;47:490–494.
  • Windolf M, Gtzen N, Morlock M. Systematic accuracy and precision analysis of video motion capturing systems–exemplified on the Vicon-460 system. J Biomech. 2008;41:2776–2780.
  • Zijlstra W, Bisseling R. Estimation of hip abduction moment based on body fixed sensors. Clin Biomech (Bristol, Avon). 2004;19:819–827.
  • Jagos H, Oberzaucher J, Reichel M, et al. A multimodal approach for insole motion measurement and analysis. Proceedings of the 8th Conference of the International Sports Engineering Association (ISEA); 2010 Jul 12–16; Vienna, Austria.
  • Jagos H, Reich S, Rattay F, et al. Determination of gait parameters from the wearable motion analysis system eSHOE. Biomed Tech (Berl) 2013 [Sep 7]. DOI: 10.1515/bmt-2013-4241.
  • Tura A, Raggi M, Rocchi L, et al. Gait symmetry and regularity in transfemoral amputees assessed by trunk accelerations. J Neuroeng Rehabil. 2010;7:4.
  • Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait Posture. 2003;17:68–74.
  • Webster KE, Wittwer JE, Feller JA. Validity of the GAITRite walkway system for the measurement of averaged and individual step parameters of gait. Gait Posture. 2005;22:317–321.
  • Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika. 1965;52:591611.
  • Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Int J Nurs Stud. 2010;47:931–936.
  • Braun BJ, Veith NT, Hell R, et al. Validation and reliability testing of a new, fully integrated gait analysis insole. J Foot Ankle Res. 2015;8:54.
  • Latham NK, Mehta V, Nguyen AM, et al. Performance-based or self-report measures of physical function: which should be used in clinical trials of hip fracture patients? Arch Phys Med Rehabil. 2008;89:2146–2155.
  • Kirtley C. Clinical gait analysis: theory and practice. 1st ed. Edinburgh (UK): Elsevier; 2006.
  • Hausdorff JM, Edelberg HK, Cudkowicz ME, et al. The relationship between gait changes and falls. J Am Geriatr Soc. 1997;45:1406.
  • Menz HB, Lord SR, Fitzpatrick RC. Acceleration patterns of the head and pelvis when walking on level and irregular surfaces. Gait Posture. 2003;18:35–46.
  • Sprager S, Zazula D. Impact of different walking surfaces on gait identification based on higher-order statistics of accelerometer data. Signal and Image Processing Applications (ICSIPA), 2011 IEEE International Conference, 2011 16-18 Nov; p. 360–365.
  • Zurales K, DeMott TK, Kim H, et al. Gait efficiency on an uneven surface is associated with falls and injury in older subjects with a spectrum of lower limb neuromuscular function: a prospective study. Am J Phys Med Rehabil. 2016;95:83–90.
  • Cetin E, Muzembo J, Pardessus V, et al. Impact of different types of walking aids on the physiological energy cost during gait for elderly individuals with several pathologies and dependent on a technical aid for walking. Ann Phys Rehabil Med. 2010;53:399–405.
  • Härdi I, Bridenbaugh SA, Gschwind YJ, et al. The effect of three different types of walking aids on spatio-temporal gait parameters in community-dwelling older adults. Aging Clin Exp Res. 2014;26:221–228.
  • Polasek D. Foot-mounted IMU sensor – data processing for gait analysis parameter extraction [master’s thesis]. Zurich University of Applied Sciences, School of Engineering, Institute for Mechatronic Systems, Winterthur, Switzerland; 2014.
  • Tkachenko BA, Scherer M, David V, et al. Development of a wearable live-feedback system to support partial weight-bearing while recovering from lower extremity injuries. Proceedings of the 11th Conference of the International Sports Engineering Association (ISEA); Delft, Netherlands; 2016.
  • Jagos H, David V, Haller M, et al. A framework for (tele-) monitoring of the rehabilitation progress in stroke patients: eHealth 2015 special issue. Appl Clin Inform. 2015;6:757–768.

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