improve phrasing of algorithm design

vignettes/chapter1_WhatIsGGIR.Rmd

@@ -65,11 +65,11 @@ Further, we hope GGIR is of use to those without the financial resources for com
 
 ### Algorithm design
 
-The philosophy behind the algorithms as implemented in GGIR is that biomechanical explainable (heuristic or knowledge driven) approaches to measurement in science are preferable over purely data-driven approaches. Only when a knowledge driven approach is unrealistic we can consider a data-driven approach.
+The philosophy behind the algorithms as implemented in GGIR is that biomechanical explainable (heuristic or knowledge driven) approaches to measurement in science are preferable over purely data-driven approaches. Please note the specification to the scientific context rather than measurement in general, e.g. consumer wearables. Only when a knowledge driven approach is unrealistic we can consider a data-driven approach. 
 
-The idea of a knowledge driven approach is that in order to advance insight, it is essential to have an understanding of the causal relation between the phenomena being observed (e.g. acceleration of one body part), the way the (acceleration) sensor works, what we do with the data produced, and how we interpret the data. For example, we know that body acceleration relates to energy expenditure because of physics and human physiology. The abundance of scientific publications that have reported a positive correlation between accelerometer data and energy expenditure only served to confirm that existing knowledge was correct.
+The idea of a knowledge driven approach is that in order to advance insight, it is essential to have an understanding of the causal relation between the phenomena being observed (e.g. acceleration of one body part), the way the (acceleration) sensor works, what we do with the data produced, and how we interpret the data. For example, we know that body acceleration relates to energy expenditure because of physics and human physiology. The abundance of scientific publications that have reported a positive correlation between accelerometer data and energy expenditure only served to confirm prior knowledge.
 
-In contrast, data-driven methods focus on optimal correlation between sensor data and reference labels or values, and are much less concerned with causal associations that are the focus of knowledge driven approaches, as defined above. Identical to how correlation is not necessarily equal to causation in health research, the process of measurement can also be confounded. Some examples: We may see differences in body acceleration patterns that correlate with different activity types or different levels of energy expenditure, but that does not mean that we actually measure those activity types or energy expenditure levels. Ignoring such aspects can easily lead to overestimating the value of an accelerometer for measuring those constructs (activity type, etc) and to underestimate the value of an accelerometer of capturing acceleration as a useful measure of behaviour, if appropriately used and interpreted.
+In contrast, data-driven methods focus on optimal correlation between sensor data and reference labels or values, and are much less concerned with causal associations that are the focus of knowledge driven approaches, as defined above. Identical to how correlation is not necessarily equal to causation in health research, the process of measurement can also be confounded. Some examples: We may see differences in body acceleration patterns that correlate with different activity types or different levels of energy expenditure, but that does not mean that we actually measure those activity types or energy expenditure levels. Ignoring this distinction can easily lead to overestimating the value of an accelerometer for measuring those constructs (activity type, etc) and to underestimate the value of an accelerometer of capturing acceleration as a useful measure of behaviour, if appropriately used and interpreted.
 
 A second problem with data-driven methods is that they heavily depend on the availability of reliable criterion methods.