Journal ArticleDOI
Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications
Kamiar Aminian,Bijan Najafi +1 more
TLDR
The possibility to detect useful human motion based on new techniques using different types of body‐fixed sensors is shown and a combination of accelerometers and angular rate sensors (gyroscopes) showed a promising design for a hybrid kinematic sensor measuring the 2D kinematics of a body segment.Abstract:
Motion capture is mainly based on standard systems using optic, magnetic or sonic technologies. In this paper, the possibility to detect useful human motion based on new techniques using different types of body-fixed sensors is shown. In particular, a combination of accelerometers and angular rate sensors (gyroscopes) showed a promising design for a hybrid kinematic sensor measuring the 2D kinematics of a body segment. These sensors together with a portable datalogger, and using simple biomechanical models, allow capture of outdoor and long-term movements and overcome some limitations of the standard motion capture systems. Significant parameters of body motion, such as nature of motion (postural transitions, trunk rotation, sitting, standing, lying, walking, jumping) and its spatio-temporal features (velocity, displacement, angular rotation, cadence and duration) have been evaluated and compared to the camera-based system. Based on these parameters, the paper outlines the possibility to monitor physical activity and to perform gait analysis in the daily environment, and reviews several clinical investigations related to fall risk in the elderly, quality of life, orthopaedic outcome and sport performance. Taking advantage of all the potential of these body-fixed sensors should be promising for motion capture and particularly in environments not suitable for standard technology such as in any field activity. Copyright © 2004 John Wiley & Sons, Ltd.read more
Citations
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Journal ArticleDOI
Gait analysis using wearable sensors.
TL;DR: The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography, which are expected to play an increasingly important role in clinical applications.
Journal ArticleDOI
Activity classification using realistic data from wearable sensors
TL;DR: Methods used for classification of everyday activities like walking, running, and cycling are described to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required.
Journal ArticleDOI
Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions
TL;DR: The aim of this study was to examine how well the daily activities and sports performed by the subjects in unsupervised settings can be recognized compared to supervised settings and support a vision of recognizing a wider spectrum, and more complex activities in real life settings.
Journal ArticleDOI
Accelerometry: a technique for quantifying movement patterns during walking.
TL;DR: The use of accelerometers attached to the upper body has provided useful insights into the motor control of normal walking, age-related differences in dynamic postural control, and gait patterns in people with movement disorders.
Journal ArticleDOI
A Comparison of Feature Extraction Methods for the Classification of Dynamic Activities From Accelerometer Data
TL;DR: The findings show that, although the wavelet transform approach can be used to characterize nonstationary signals, it does not perform as accurately as frequency-based features when classifying dynamic activities performed by healthy subjects.