Assessing the Accuracy of an Algorithm for the Estimation of Spatial Gait Parameters Using Inertial Measurement Units: Application to Healthy Subject and Hemiparetic Stroke Survivor

Visi, Federico; Georgiou, Theodoros; Holland, Simon; Pinzone, Ornella; Donaldson, Glenis and Tetley, Josie (2017). Assessing the Accuracy of an Algorithm for the Estimation of Spatial Gait Parameters Using Inertial Measurement Units: Application to Healthy Subject and Hemiparetic Stroke Survivor. In: 4th International Conference on Movement Computing (MOCO '17), 28-30 Jun 2017, London, UK, ACM.

DOI: https://doi.org/10.1145/3077981.3078034

Abstract

We have reviewed and assessed the reliability of a dead reckon- ing and drift correction algorithm for the estimation of spatial gait parameters using Inertial Measurement Units (IMUs). In particular, we are interested in obtaining accurate stride lengths measurements in order to assess the effects of a wearable haptic cueing device designed to assist people with neurological health conditions during gait rehabilitation. To assess the accuracy of the stride lengths estimates, we compared the output of the algorithm with measurements obtained using a high-end marker-based motion capture system, here adopted as a gold standard. In addition, we introduce an alternative method for detecting initial impact events (i.e. the instants at which one foot contacts the ground, here used for de- limiting strides) using accelerometer data. Our method, based on a kinematic feature we named ‘jerkage’, has proved more robust than detecting peaks on raw accelerometer data. We argue that the resulting measurements of stride lengths are accurate enough to provide trend data needed to support worthwhile gait rehabilitation applications. This approach has potential to assist physiotherapists and patients without access to fully-equipped movement labs. More specifically, it has applications for collecting data to guide and assess gait rehabilitation both outdoors and at home.

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• Item ORO ID
• 49866
• Item Type
• Conference or Workshop Item
• ISBN
• 1-4503-5209-X, 978-1-4503-5209-3
• Keywords
• Gait Analysis; Haptic Bracelets; Inertial Measurement Unit; IMU; Motion Capture; Dead Reckoning; Stroke; Hemiparetic Gait; Gait Rehabilitation
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
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  Music Computing Lab
• Copyright Holders
• © 2017 The Authors
• Depositing User
• Users 12745 not found.