Temporal Dynamics of Symptom and Treatment Variables in a Lifestyle-Oriented Approach to Anxiety Disorder: A Single-Subject Time-Series Analysis

2012 ◽  
Vol 81 (4) ◽  
pp. 253-255 ◽  
Author(s):  
H.J. Rogier Hoenders ◽  
Elisabeth H. Bos ◽  
Joop T.V.M. de Jong ◽  
Peter de Jonge
Keyword(s):  
Time Series ◽  
Anxiety Disorder ◽  
Time Series Analysis ◽  
Temporal Dynamics ◽  
Single Subject ◽  
Series Analysis ◽  
Oriented Approach

scholarly journals Wind direction and mental health: a time-series analysis of weather influences in a patient with anxiety disorder

2012 ◽  
Vol 2012 (jun07 1) ◽  
pp. bcr2012006300-bcr2012006300 ◽  
Author(s):  
E. H. Bos ◽  
R. Hoenders ◽  
P. de Jonge
Keyword(s):  
Mental Health ◽  
Time Series ◽  
Anxiety Disorder ◽  
Time Series Analysis ◽  
Wind Direction ◽  
Series Analysis

Time series analysis for single-subject designs.

1982 ◽  
Vol 91 (1) ◽  
pp. 178-189 ◽  
Author(s):  
G. Porter Horne ◽  
Mark C. Yang ◽  
William B. Ware
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Single Subject ◽  
Series Analysis ◽  
Single Subject Designs

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

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