2015
DOI: 10.3390/s16010012
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Robust Foot Clearance Estimation Based on the Integration of Foot-Mounted IMU Acceleration Data

Abstract: This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject’s foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking co… Show more

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Cited by 58 publications
(59 citation statements)
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“…In future work, we will use information from the sensor to modulate the stimulation in real time, in case of FOG detection, u‐turn or, for example, to adapt the stimulus to gait pattern. Such a sensor may also be used to monitor some gait parameters in order to assess functional improvement .…”
Section: Methodsmentioning
confidence: 99%
“…In future work, we will use information from the sensor to modulate the stimulation in real time, in case of FOG detection, u‐turn or, for example, to adapt the stimulus to gait pattern. Such a sensor may also be used to monitor some gait parameters in order to assess functional improvement .…”
Section: Methodsmentioning
confidence: 99%
“…This work has now to be extended and validated experimentally in real-time conditions. In other studies we have also shown that other gait parameters can be obtained from one inertial sensor such a stride length [7], foot clearance [8]. This type of information as well as foot inclination can be integrated in optimal controllers to online compute the FES pattern for the upcoming stride.…”
Section: Fes-drop-foot Correction: From Pre-programmed Patterns To Onmentioning
confidence: 99%
“…In addition, the PNS based on self-contained sensors can only use the output of accelerometers and gyroscopes to detect the ZVI without the assistance of external sensors. Commonly-used ZVI detection methods for PNS with self-contained sensors include the acceleration magnitude method [8], the angular velocity magnitude method [9,10,11,12], the moving variance method [13], a combination of the above methods [14,15,16], and so on; all of these methods have a common characteristic that the ZVI is detected by setting a threshold.…”
Section: Introductionmentioning
confidence: 99%