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Updated: Jul 30, 2026

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
Published on: June 5, 2019
[Relation between anthropometric indicators and electrocardiogram variability]
1Ustav normálnej a patologickej fyziológie Slovenskej akadémie vied, Bratislava, Slovenská republika.
Aim:
To investigate which combination of anthropometrical parameters influence significantly the variability of the magnitude spatial vectors of atrial (sPmax), activation and ventricular (sQRSmax) activation and ventricular depolarization (sTmax). Quantification of these relationships can improve the reliability of criteria for normal values of ECG and VCG characteristics.
Subjects And Methods:
The study group consisted of 195 healthy boys and men without signs of cardiac disease, with normal ECG and VCG, aged from 7 to 70 years, (median = 19 years). Electrocardiologic variables were obtained by Frank lead system in seated persons from a single heartbeat by the computer system Cardiac 128--PC (METE, Prague) in mid respiration. 30 anthropometrical measurements were taken including biceps, triceps, subscapulare and suprailiacare skinfold thicknesses. Proportionality of body and thoracic shape was evaluated according indexes computed from body height, weight (Body mass index, Rohrer and Ponderal index), circumferences (Relative abdominal circumference, Pignet index), anteroposterior and transversal dimensions (Thoracic index, relative sagittal diameter). Values of the 15th and 85th percentil of relevant indexes were taken as criteria for stratification of the sample into three subgroups demarcating the constitutional types. Differences in maximal spatial vector magnitudes between these subgroups were tested by variance analysis ANOVA. Relationships to anthropometrical and vectorcardiographic parameters were expressed also by regression equations.
Results:
The average magnitudes of maximal spatial vectors increased during maturation and early adulthood: sPmax, approximately up to 17 years, sQRSmax and sTmax up to 22 years. The magnitude of ventricular vectors decreased after this period. With increasing endomorphy, which is indicated by values of Rohrer index, relative abdominal circumference and fat percentage, magnitudes of sPmax, s QRSmax and sTmax decreased (p < 0.001) on the other hand they increased with higher linearity (Ponderal index) and index of fitness (Pignet index). The greatest differences (by 50%) were found in values of sPmax, whereas distributions of ventricular vectors sQRSmax differed by 20-30%.
Conclusions:
The variability of magnitudes of maximal spatial vectors was significantly influenced by the proportionality of body constitution independently of age. The tightest relationship of sTmax was found with fat percentage. Influence of anthropometrical parameters was most pronounced in younger adulthood and should be taken into account when evaluating of electrocardiograms and vectorcardiograms.
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