• DocumentCode
    180883
  • Title

    Validation of the e-AR Sensor for Gait Event Detection Using the Parotec Foot Insole with Application to Post-Operative Recovery Monitoring

  • Author

    Jarchi, Delaram ; Lo, Benny ; Ieong, Edmund ; Nathwani, Dinesh ; Guang-Zhong Yang

  • Author_Institution
    Inst. of Global Health Innovation, Hamlyn Centre, Imperial Coll. London, London, UK
  • fYear
    2014
  • fDate
    16-19 June 2014
  • Firstpage
    127
  • Lastpage
    131
  • Abstract
    The use of e-AR (ear-worn activity recognition) sensor for gait pattern estimation has shown promise for a range of health and wellbeing applications. To establish its more detailed quantitative accuracy, an in-shoe pressure measurement system (Parotec) has been used to validate the estimated gait events from the e-AR sensor. Ten healthy adults equipped with Parotec and e-AR systems walked in a corridor of about 15m. The sampling frequency of both systems was set at 100Hz and a manual synchronisation has been performed for subsequent error measurements. The gait events from the e-AR sensor are estimated by using a recently developed method based on singular spectrum analysis and longest common subsequence algorithms [1]. The corresponding gait events from the Parotec system are estimated using the ground reaction forces. The upper and lower limits of absolute errors using 95% confidence intervals for heel contact and toe off events obtained as 35.38±3.22ms and 73.05±7.24ms respectively. We further provide a preliminary patient study to demonstrate how the estimated gait events and the gait analysis platform can be used for assessing patients recovering after orthopaedic surgery inside the clinic.
  • Keywords
    biomedical measurement; gait analysis; patient monitoring; patient rehabilitation; sensors; Parotec foot insole; e-AR sensor validation; ear worn activity recognition sensor; estimated gait events; gait event detection; ground reaction forces; in shoe pressure measurement system; longest common subsequence algorithm; manual synchronisation; orthopaedic surgery; patient recovery; post operative recovery monitoring; sampling frequency; singular spectrum analysis; Acceleration; Event detection; Foot; Large Hadron Collider; Measurement uncertainty; Monitoring; Silicon; e-AR (ear-worn activity recognition) sensor; gait; heel contact; pressure measurement; toe off;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wearable and Implantable Body Sensor Networks (BSN), 2014 11th International Conference on
  • Conference_Location
    Zurich
  • Print_ISBN
    978-1-4799-4932-8
  • Type

    conf

  • DOI
    10.1109/BSN.2014.16
  • Filename
    6855629