Real-Time Human Foot Motion Localization Algorithm With Dynamic Speed

Nguyen, Luan Van; La, Hung Manh

doi:10.1109/thms.2016.2586741

Cited by 27 publications

(14 citation statements)

References 26 publications

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“…Since the IMU normally outputs data of the acceleration a t+1 b , the angular rate w t+1 b , the Earth magnetic field o t+1 b , and the quaternion q t+1 , we need to derive the Euler rotation angles, Roll (α t+1 ), Pitch (β t+1 ) and Yaw (γ t+1 ), from these raw data. The detail of obtaining these rotation angles can be found in [24].…”

Section: Real-time Human Foot Motion Localization Algorithm For the Smentioning

confidence: 99%

A Smart Shoe for building a real-time 3D map

Nguyen

Sánchez

et al. 2016

Automation in Construction

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Three dimensional (3D) mapping of environments has gained tremendous attention, from academic to industry to military, owing to the ever increasing needs of environmental modeling as well as monitoring. While many highly effective techniques have been reported thus far, a few even turned into commercial products, none has explored the use of wearable sensors to capture human foot motion, gait, and phase for 3D map construction, especially in the Architecture, Engineering, and Construction (AEC) domain. In this work, we propose a smart (and wearable) shoe, called "Smart Shoe", which integrates multiple laser scanners and an inertial measurement unit (IMU) to build a 3D map of environments in real time. Such a Smart Shoe can be a potential tool for floor plan surveying, in-construction monitoring, planning renovations, space usage planning, managing building maintenance and other tasks in the AEC domain. Besides, this Smart Shoe could assist disabled people (blind people) to navigate and avoid obstacles in the unknown environment. In another case, the shoes may help firefighters quickly model and recognize objects in the firing, dark, and smoky buildings where traditional camera-based approaches might not be applicable. We integrate this shoe with a novel foot localization algorithm that produces a smooth and accurate pose and trajectory of human walking, which is the key enabling technique to minimize data registration errors from laser point cloud.

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Section: Real-time Human Foot Motion Localization Algorithm For the Smentioning

confidence: 99%

A Smart Shoe for building a real-time 3D map

Nguyen

Sánchez

et al. 2016

Automation in Construction

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“…In this paper, we aim to design a high gain observer, a conventional sliding mode observer, and a new adaptive sliding mode observer for our dual muscle system. The benefits of accurate state estimation for the agonistic-antagonistic muscle model offer useful frameworks to investigate several problems in human-machine interactions such as monitoring of human health state and gait analysis [28]- [30], 3-D human skeleton localization [31], human foot localization [32], [33], artificial muscles [16], etc.…”

Section: Introductionmentioning

confidence: 99%

On the State Estimation of an Agonistic-Antagonistic Muscle System

Nguyen

Warner

Mohammadi

et al. 2017

Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Cont

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Abstract-Research on assistive technology, rehabilitation, and prosthesis requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic-antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the convergence of the three observers. To facilitate numerical simulations, a backstepping controller is employed to drive the muscle system to track a desired trajectory. Numerical simulations reveal that the three observers are comparable and provide reliable estimates in noise free and noisy cases. The proposed schemes may serve as frameworks for estimation of complex multi-muscle systems, which could lead to intelligent exercise machines for adaptive training and rehabilitation, and adaptive prosthetics and exoskeletons.

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“…Inertial measurement units (IMU) can be used to make portable rehabilitation devices. They have been extensively used in position and attitude estimation, allowing for pedestrian navigation tracking [6][7][8][9][10][11][12][13], gait analysis [14][15][16][17][18][19][20], foot pose estimation [21], foot clearance estimation [22], wearable devices for Game Play application [23], and detecting foot strike in recreational runners [24]. A problem of inertial measurement units is that they present biases and other systematic errors that are responsible for position and attitude estimation errors.…”

mentioning

confidence: 99%

“…To provide robust distortion-free and refined absolute position and orientation vectors, data fusion is used to combine the measurements from the three-axis gyroscope, three-axis geomagnetic sensor, and three-axis accelerometer enclosed in the IMU [17]. Approaches used with data fusion include Kalman filters [6,9,15], clustering algorithms [7], and hidden Markov models [8]. Some of these approaches rely on additional information, such as map information [8,10], multiple IMU [11], biomechanical models [25], or light detection and ranging (LIDAR) systems [12].…”

mentioning

confidence: 99%

“…Without an error-resetting algorithm, this error rapidly increases. For pedestrian navigation tracking and gait analysis, a zero velocity update (ZVU) algorithm could be employed as an effective way to correctly detect the stance phase of each gait cycle and compensate for speed bias errors [6,9]. Another source for errors in IMU sensors comes from magnetic disturbances that might take place in indoor environments such as medical facilities, which becomes a problem for IMU clinical applications.…”

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confidence: 99%

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Foot-Mounted Inertial Measurement Units-Based Device for Ankle Rehabilitation

2018

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Ankle sprains are frequent injuries that occur among people of all ages. Ankle sprains constitute approximately 15% of all sports injuries, and are the most common traumatic emergencies. Without proper treatment and rehabilitation, a more severe sprain can weaken the ankle, making it more likely for new injures, and leading to long-term problems. In this work, we present an inertial measurement units (IMU)-based physical interface for measuring the foot attitude, and a graphical user interface that acts as a visual guide for patient rehabilitation. A foot-mounted physical interface for ankle rehabilitation was developed. The physical interface is connected to the computer by a Bluetooth link, and provides feedback to the patient while performing dorsiflexion, plantarflexion, eversion, and inversion exercises. The system allows for in-home rehabilitation at an affordable price while engaging the patient through active therapy. According to the results, more consistent rehabilitation could be achieved by providing feedback on foot angular position during therapy procedures.

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Real-Time Human Foot Motion Localization Algorithm With Dynamic Speed

Cited by 27 publications

References 26 publications

A Smart Shoe for building a real-time 3D map

A Smart Shoe for building a real-time 3D map

On the State Estimation of an Agonistic-Antagonistic Muscle System

Foot-Mounted Inertial Measurement Units-Based Device for Ankle Rehabilitation

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