Related Experiment Video
Updated: Jul 29, 2026

Tilt Testing with Combined Lower Body Negative Pressure: a "Gold Standard" for Measuring Orthostatic Tolerance
Published on: March 21, 2013
Static stabilometry and repeated testing in a normal population
S H Nordahl1, T Aasen, B M Dyrkorn
1Department of Otolaryngology/Head and Neck Surgery, Haukeland University Hospital, Bergen, Norway. stein.nordahl@ore.uib.no
Background:
The purpose of the present study was to see if there is a learning effect of repeated static stabilometric testing, using a protocol suitable for testing postural control in narrow spaces, like hypo- and hyperbaric chambers.
Hypothesis:
Static stabilometry testing under normobaric conditions is objective and reproducible. With repeated testing, a learning effect may be observed.
Methods:
Four groups of healthy individuals were tested ten times under the same four acoustically and visually standardized and normobaric normoxic test conditions on a static balance platform. First, the subjects were asked to stand on a bare platform with the eyes open, thereafter with the eyes closed. This was repeated with a foam rubber mat placed on top of the balance platform. The time interval between the first and the last test sequence was 11 (10-13) days for the test subjects in group I (n = 22), 17 d for group II (n = 13), 31(28-36) days for group III (n = 15) and 115 (49-193) days for group IV (n = 10).
Results:
Static stabilometry tests in a normal population are objective and reproducible. With repeated tests, a learning effect was observed. The learning effect was largest when standing on a foam rubber mat with eyes closed and when the time intervals between the tests were shortest. There was no difference in sway pattern or learning ability between tall and short test subjects, between subjects with heavy and light body weight or between the sexes.
Related Concept Videos
Regression Toward the Mean
Variation: Normal Distribution, Range, and Standard Deviation
Assessment of blood pressure in brachial artery(two-step method)
Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...

