In the field of 3D body scanning the topic of measurement, and in particular error in measurement, is highly important. We know that in all measurements some degree of uncertainty is present, which can be expressed as error in measurement. When we speak about measurement error, questions are often asked about the accuracy or the precision of the results. It is a legitimate concern, but it’s not always clear what we are talking about (depending on the terms used). In this article, we are going to clarify and define several terms; we will visit later the different tools used to calculate the different ways to quantify measurements.
True or Accepted Reference Value (Reference)
A value that serves as an agreed-upon reference for comparison, and which is derived as:
a) the known value;
b) a theoretical or established value, based on scientific principles;
c) as assigned or certified value, based on the experimental work of a national or international organization
d) a consensus or certified value; based on the collaborative work of a scientific or engineering group
e) when a), b), c) or d) are not available, the expectation of the (measurable) quantity, i.e. the mean of a specified population of measurements.
The difference between a population mean of the measurement or test result and the reference value. Therefore, trueness leads to an under- or overestimate of the reference value. The measure of trueness is usually expressed in terms of bias.
Measurement bias is mainly due to faulty measuring devices or procedures.
Precision/reliability represents how close measurements are to each other, i.e. the amount of variation or dispersion around the mean.
Unlike trueness, its magnitude is only dependent on the estimated (or observed) values and is completely independent of the reference value. In measurement situations, precision arises from the variance produced by the measurement device or procedure.
The total variance then arises from the variability generated by measurement error, sample variation and estimation variance.
Precision can be divided in repeatability and reproducibility
• Repeatability: Variation observed when successive measurements are obtained under near identical conditions.
• Reproducibility: Variation observed when successive measurements are obtained under changed conditions, e.g. changes in techniques, operators and/or devices.
Accuracy represents how close measurements are to the reference value by combining trueness and precision. The more biased and the less precise an estimator is, the worse its overall ability to make an accurate point estimation. Accuracy is thus defined as the overall distance between estimated (or observed) values and the reference value.
Unlike accuracy, agreement refers to the closeness of two measured values, not to whether those values are correct or not.
Resolution is the smallest change of the measurement value that a device can show, i.e. if the resolution is 1mm, changes under 1mm will not be detected by the device. Generally, resolution is higher than accuracy on the devices, thus the resolution does not limit the minimal changes of the measurement value that the device can detect.
Bartlett J., Frost, C. (2008) Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound Obstet Gynecol. 31(4):466-475
Walther B., Moore J. (2005) The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography. 28: 815-829, 2005
Trajković G. (2008) Measurement: Accuracy and Precision, Reliability and Validity. In: Kirch W. (eds) Encyclopedia of Public Health. Springer, Dordrecht
ISO 5725-1:1994, 3.5 (Source: ISO 3534-1)
Picture from https://amloceanographic.com/blog/sensor-accuracy/
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