Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU

Accurate real-time gait event detection is the basis for the development of new gait rehabilitation techniques, especially when utilizing robotics or virtual reality (VR). The recent emergence of affordable wearable technologies, especially inertial measurement units (IMUs), has brought forth variou...

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Main Authors: Matej Tomc, Zlatko Matjačić
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/12/5500
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author Matej Tomc
Zlatko Matjačić
author_facet Matej Tomc
Zlatko Matjačić
author_sort Matej Tomc
collection DOAJ
description Accurate real-time gait event detection is the basis for the development of new gait rehabilitation techniques, especially when utilizing robotics or virtual reality (VR). The recent emergence of affordable wearable technologies, especially inertial measurement units (IMUs), has brought forth various new methods and algorithms for gait analysis. In this paper, we highlight some advantages of using adaptive frequency oscillators (AFOs) over traditional gait event detection algorithms, implemented a real-time AFO-based algorithm that estimates the gait phase from a single head-mounted IMU, and validated our method on a group of healthy subjects. Gait event detection was accurate at two different walking speeds. The method was reliable for symmetric, but not asymmetric gait patterns. Our method could prove especially useful in VR applications since a head-mounted IMU is already an integral part of commercial VR products.
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spelling doaj.art-75fa1645e75a4f4486059f4087bf4c182023-11-18T12:31:55ZengMDPI AGSensors1424-82202023-06-012312550010.3390/s23125500Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMUMatej Tomc0Zlatko Matjačić1University Rehabilitation Institute Republic of Slovenia Soča, Linhartova 51, 1000 Ljubljana, SloveniaUniversity Rehabilitation Institute Republic of Slovenia Soča, Linhartova 51, 1000 Ljubljana, SloveniaAccurate real-time gait event detection is the basis for the development of new gait rehabilitation techniques, especially when utilizing robotics or virtual reality (VR). The recent emergence of affordable wearable technologies, especially inertial measurement units (IMUs), has brought forth various new methods and algorithms for gait analysis. In this paper, we highlight some advantages of using adaptive frequency oscillators (AFOs) over traditional gait event detection algorithms, implemented a real-time AFO-based algorithm that estimates the gait phase from a single head-mounted IMU, and validated our method on a group of healthy subjects. Gait event detection was accurate at two different walking speeds. The method was reliable for symmetric, but not asymmetric gait patterns. Our method could prove especially useful in VR applications since a head-mounted IMU is already an integral part of commercial VR products.https://www.mdpi.com/1424-8220/23/12/5500gait event detectionadaptive oscillatorsvirtual realityinertial measurement units
spellingShingle Matej Tomc
Zlatko Matjačić
Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
Sensors
gait event detection
adaptive oscillators
virtual reality
inertial measurement units
title Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
title_full Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
title_fullStr Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
title_full_unstemmed Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
title_short Real-Time Gait Event Detection with Adaptive Frequency Oscillators from a Single Head-Mounted IMU
title_sort real time gait event detection with adaptive frequency oscillators from a single head mounted imu
topic gait event detection
adaptive oscillators
virtual reality
inertial measurement units
url https://www.mdpi.com/1424-8220/23/12/5500
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