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
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