Novel Sleep Stage Estimation Method for Children Using Body Movement

2013 ◽  
Vol 2 (2) ◽  
pp. 61-68 ◽  
Author(s):  
Shima Okada ◽  
Sachiko Shimizu ◽  
Yuko Ohno ◽  
Ikuko Mohri ◽  
Masako Taniike ◽  
...  
Keyword(s):  
Sleep Stage ◽  
Body Movement ◽  
Estimation Method ◽  
Stage Estimation

scholarly journals Sleep stage estimation method using a camera for home use

2019 ◽  
Vol 9 (2) ◽  
pp. 257-265 ◽  
Author(s):  
Teruaki Nochino ◽  
Yuko Ohno ◽  
Takafumi Kato ◽  
Masako Taniike ◽  
Shima Okada
Keyword(s):  
Sleep Stage ◽  
Estimation Method ◽  
Stage Estimation

Sleep Stage Estimation By Evolutionary Computation Using Heartbeat Data and Body-Movement

2012 ◽  
Vol 4 (22) ◽  
pp. 281-290 ◽  
Author(s):  
Hiroyasu MAtsushima ◽  
Kazuyuki Hirose ◽  
Kiyohiko Hattori ◽  
Hiroyuki Sato ◽  
Keiki Takadama
Keyword(s):  
Evolutionary Computation ◽  
Sleep Stage ◽  
Body Movement ◽  
Stage Estimation

Evolutionary Algorithm for Uncertain Evaluation Function

2015 ◽  
Vol 11 (02) ◽  
pp. 201-215
Author(s):  
Yusuke Tajima ◽  
Masaya Nakata ◽  
Hiroyasu Matsushima ◽  
Yoshihiro Ichikawa ◽  
Hiroyuki Sato ◽  
...  
Keyword(s):  
Evolutionary Algorithm ◽  
Robust Estimation ◽  
High Performance ◽  
Sleep Stage ◽  
Probability Model ◽  
Estimation Method ◽  
High Accuracy ◽  
Evaluation Function ◽  
The One ◽  
Stage Estimation

This paper proposes the evolutionary algorithm (EA) for the uncertain evaluation function in which fitness values change even with the same input. In detail, the proposed method employs the probability model to acquire the appropriate attributes that can drive the good solutions. To investigate the effectiveness of the proposed method, we apply it to sleep stage estimation problem where an accuracy of sleep stage estimation changes even in the same estimation filter (correspondingly the solutions). The experimental results have revealed the following implications: (i) The proposed method succeeded to acquire the robust estimation filters which stably derive a high accuracy of the sleep stage estimation; (ii) in detail, the proposed method with the roulette selection shows higher performance than the one with the random selection; and (iii) the proposed method shows high performance and robustness to the different days in comparison with the conventional sleep stage estimation method.

Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons

2010 ◽  
Vol E93-B (4) ◽  
pp. 811-818 ◽  
Author(s):  
Keiki TAKADAMA ◽  
Kazuyuki HIROSE ◽  
Hiroyasu MATSUSHIMA ◽  
Kiyohiko HATTORI ◽  
Nobuo NAKAJIMA
Keyword(s):  
Sleep Stage ◽  
Multiple Band ◽  
Band Pass ◽  
Stage Estimation ◽  
Care Support

scholarly journals A new estimation method for COVID-19 time-varying reproduction number using active cases

2020 ◽  
Author(s):  
A. Hasan ◽  
H. Susanto ◽  
V.R. Tjahjono ◽  
R. Kusdiantara ◽  
E.R.M. Putri ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Estimation Method ◽  
Virus Transmission ◽  
Estimation Procedure ◽  
Time Varying ◽  
State Variables ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Novel Coronavirus ◽  
Stage Estimation

AbstractWe propose a new method to estimate the time-varying effective (or instantaneous) reproduction number of the novel coronavirus disease (COVID-19). The method is based on a discrete-time stochastic augmented compartmental model that describes the virus transmission. A two-stage estimation method, which combines the Extended Kalman Filter (EKF) to estimate reported state variables (active and removed cases) and a low pass filter based on a rational transfer function to remove short term fluctuations of the reported cases, is used with case uncertainties that are assumed to follow a Gaussian distribution. Our method does not require information regarding serial intervals, which makes the estimation procedure simpler without reducing the quality of the estimate. We show that the proposed method is comparable to common approaches, e.g., age-structured and new cases based sequential Bayesian models. We also apply it to COVID-19 cases in the Scandinavian countries: Denmark, Sweden, and Norway, where we see a delay of about four days in predicting the epidemic peak.

scholarly journals Determinants of Child Height in Uganda: A Consideration of the Selection Bias Caused by Child Mortality

1995 ◽  
Vol 16 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Namkee Ahn ◽  
Abusaleh Shariff
Keyword(s):  
Child Mortality ◽  
Selection Bias ◽  
Estimation Method ◽  
Female Education ◽  
Health Transition ◽  
Maternal Characteristics ◽  
Child Height ◽  
Socio Economic Variables ◽  
Stage Estimation ◽  
Height For Age

This paper reports a methodology for analysis and presents the determinants of child height in Uganda. A two-stage estimation method that evaluated the effects of covariates on child height for age after controlling for the selection bias caused by child mortality was necessary. Important determinants of child health in Uganda are the child's and some maternal characteristics. Some environmental factors (at the levels of both community aggregate and household) have significance. The effects of mothers’ characteristics were relatively more sensitive to correction of the selection bias. In particular, mother's secondary education almost doubled its effect and became significant in determining the height of children. Overall results suggest that Uganda is facing a phase of health transition in which the effect of socio-economic variables (at both individual and community levels) are beginning to show up significantly. Although an all-round developmental effort is essential, selective interventions aiming to improve female education and, where that is difficult, extension of appropriate information through radio are likely to improve the survival and health of children.

scholarly journals Food demand in Brazil: an application of Shonkwiler & Yen Two-Step estimation method

2010 ◽  
Vol 40 (1) ◽  
pp. 186-211 ◽  
Author(s):  
Alexandre Bragança Coelho ◽  
Danilo Rolim Dias de Aguiar ◽  
James S. Eales
Keyword(s):  
Functional Form ◽  
Estimation Method ◽  
Demand System ◽  
Positive Relation ◽  
Monthly Income ◽  
Second Stage ◽  
Negative Income ◽  
Using Data ◽  
Stage Estimation ◽  
Two Step Estimation

The objective of the analysis is to estimate a demand system including eighteen food products using data from a Brazilian Household Budget Survey carried out in 2002 and 2003 (POF 2002/2003). The functional form used was Quadratic Almost Ideal Demand System (QUAIDS). Estimation employs the Shonkwiler and Yen method to account for zero consumption. Results showed that purchase probabilities of staples foods were negatively related to family monthly income, while meat, milk and other products showed a positive relation. Regional, educational and urbanization variables were also important in the first stage estimation. While some of the goods had negative income coefficients, none were inferior and six of eighteen were luxuries based on second stage estimates.

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