Data processing

The raw data collected during a testing section usually contains many stroke cycles, which have various duration and magnitudes of biomechanical variables:


If every stroke analysed, it would create huge amount of information, which could be ambiguous and difficult to comprehend. To solve this problem and represent accurately rowing technique, a method was developed, which converts raw data into a form representing one typical stroke cycle for the sample, so it is called “averaging” process. 

The cycle start time was defined as the moment when the oar (right oar in sculling) of the stroke rower crosses the zero angle (perpendicular to the boat) during the recovery phase. This moment was used as a trigger of the stroke cycle for the whole crew. The average cycle time was calculated over all the strokes in the sample and then each cycle of the sample should be normalised the same average cycle time. The data was then processed (averaged) into 50-point data arrays for each measured variable (oar angle, force, etc.). 

Discrete data values (extremes, sub-phases) were then derived using second-order polynomial interpolation based on the four nearest points of the arrays. The normalization algorithm was checked for validity by means of a comparison between the derived values (such as catch and release angles, maximum force, work and power, etc.) calculated using normalized data and an average of those values from each cycle in the sample using raw data. The differences ranged from 0.02% to 0.85%, which was considered satisfactory.

Analysis of the typical (averaged) patterns of different samples allows reliable comparison of various samples (various rowers, stroke rates, long-term trends, etc.) and makes the changes in rowing technique very clear. The following figures illustrates this analysis:

  
The specific feature of the technique a is a significant change in the timing of the maximal force application: at lower rates the rower applies more force at the second half of the drive (1), but at higher stroke rates the peak force is shifted to the first half of the drive (2). The comparison of the start and finish sections (3) gives us information about fatigue resistance, which was satisfactory in this case.
Figure b shows another example of changes of the force curve at various stroke rates: the force gradient (rate the force increasing) at the beginning of the drive (1) remains the same at all stroke rates, as well as the position of the peak force (2). However, at stroke rates higher than 30 this sculler suffers from the ‘hump’ in the force curve (3), which is caused by early activation of the trunk at the catch, then a decrease in its velocity when the leg drive is the fastest. The hump occurs at the moment of the second activation of the trunk (see Blade Entry) and is also related to a weak posture of the sculler and very deep burying of the blade (see Vertical Oar Angle). Such “disconnection” and double emphasis of force application significantly decreases rowing effectiveness at racing stroke rates and negatively affects performance.
It was assumed that the conditions of the second last piece are very close to the racing conditions in terms of stroke rate and fatigue. Therefore, this data sample was usually taken  for analysis and compared with “targets” to evaluate the technique of each rower. The comparison is made in two ways. Qualitative values are compared with the main criteria and percentage of differences are defined for variables of the Horizontal oar angle, Force Curve, blade work (see Vertical Oar Angle) and body segments. Qualitative evaluation is made by means of comparison of the real measured curves with target curves, which were built based on quantitative values:


This evaluation method allows clear and effective feedback for rowers, coaches and helps improving technique.
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