A wearable sleep position tracking system based on dynamic state transition framework
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The experimental results demonstrate that the proposed system effectively and accurately classify twelve SP motions for tracking sleep positions, and hence, serves as a key building block for comprehensive sleep care applications related to sleep positions.Abstract:
Sleep monitoring is vital as sleep plays an important role in recovering physical and mental health. To have a sound sleep, one has to avoid bad sleep positions associated with personal health conditions. However, most of the existing sleep trackers merely show quantitative information about sleep patterns and duration at each sleep stage, overlooking the importance of sleep positions upon sleep quality. To accurately keep track of sleep positions, we propose a wearable sleep position tracking system consisting of two wristbands and one chest-band. We suggest a two-level classifier specialized for sleep motion based on Dynamic State Transition (DST)-framework. The DST-framework is designed to process the spatio-temporal sleep motion data collected via accelerometer/gyro sensing and classify twelve sleep position (SP) motions from four sleep positions. Our experimental results demonstrate that the proposed system effectively and accurately classify twelve SP motions for tracking sleep positions, and hence, serves as a key building block for comprehensive sleep care applications related to sleep positions.read more
Citations
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References
More filters
Book
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
TL;DR: This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory, and will guide practitioners to updated literature, new applications, and on-line software.
Journal ArticleDOI
National Sleep Foundation’s sleep time duration recommendations: methodology and results summary
Max Hirshkowitz,Max Hirshkowitz,Kaitlyn Whiton,Steven M. Albert,Cathy A. Alessi,Oliviero Bruni,Lydia L. DonCarlos,Nancy Hazen,John H. Herman,Eliot S. Katz,Leila Kheirandish-Gozal,David N. Neubauer,Anne E. O'Donnell,Maurice M. Ohayon,John H. Peever,Robert Rawding,Ramesh Sachdeva,Belinda Setters,Michael V. Vitiello,J. Catesby Ware,Paula J. Adams Hillard +20 more
TL;DR: A scientifically rigorous update to the National Sleep Foundation's sleep duration recommendations, determined expert recommendations for sufficient sleep durations across the lifespan using the RAND/UCLA Appropriateness Method.
Proceedings ArticleDOI
Estimation of IMU and MARG orientation using a gradient descent algorithm
TL;DR: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications, applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity sensor arrays that also include tri- axis magnetometers.
Book ChapterDOI
Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine
TL;DR: This paper presents a system for human physical Activity Recognition using smartphone inertial sensors and proposes a novel hardware-friendly approach for multiclass classification that adapts the standard Support Vector Machine and exploits fixed-point arithmetic for computational cost reduction.
Journal ArticleDOI
Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables
Jock A. Blackard,Denis J. Dean +1 more
TL;DR: The results of the comparison indicated that a feedforward artificial neural network model more accurately predicted forest cover type than did a traditional statistical model based on Gaussian discriminant analysis.