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

Published: 16 June 2014 Publication History

Abstract

The use of e-AR (ear-worn activity recognition) sensorfor 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 acorridor 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]. Thecorresponding 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 furtherprovide 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.

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  • (2024)GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMUCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680520(650-654)Online publication date: 5-Oct-2024
  • (2022)Sensing with EarablesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35503146:3(1-57)Online publication date: 7-Sep-2022
  1. Validation of the e-AR Sensor for Gait Event Detection Using the Parotec Foot Insole with Application to Post-Operative Recovery Monitoring

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      cover image Guide Proceedings
      BSN '14: Proceedings of the 2014 11th International Conference on Wearable and Implantable Body Sensor Networks
      June 2014
      156 pages
      ISBN:9781479949595

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      IEEE Computer Society

      United States

      Publication History

      Published: 16 June 2014

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      1. pressure measurement, heel contact, toe off, gait, e-AR (ear-worn activity recognition) sensor

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      • (2024)GCCRR: A Short Sequence Gait Cycle Segmentation Method Based on Ear-Worn IMUCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680520(650-654)Online publication date: 5-Oct-2024
      • (2022)Sensing with EarablesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35503146:3(1-57)Online publication date: 7-Sep-2022

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