Given the advantages listed above, video analysis will remain, for the foreseeable future, an important method of analysing technique in sport and exercise. Video analysis of a person’s technique may be qualitative or quantitative in nature. Qualitative analysis involves a detailed, systematic and structured observation of the performer’s movement pattern.
The video image is displayed on a TV monitor or computer screen and observed in real-time, slow motion and frame-by-frame. Often, multiple images, e.g. front and side views, are displayed simultaneously to allow a more complete analysis to be undertaken. The purpose of this type of analysis is often to establish the quality of the movement being observed in order to provide some feedback to the performer. It may also be used as a means of identifying the key performance parameters that need to be quantified and monitored in future analyses.
Quantitative analysis involves taking detailed measurements from the video recording to enable key performance parameters to be quantified. This approach requires more sophisticated hardware and software than for a qualitative analysis and it is vital to follow the correct data capture and data processing procedures. Quantitative analysis can be time-consuming as it often involves manually digitising a number of body landmarks (typically eighteen or more points for a full body model) over a large number of video images.
Typical landmarks selected for digitisation are those assumed to represent joint centres of rotation (e.g. knee joint centre), segmental endpoints (e.g. end of foot), or external objects (e.g. a sports implement). Two-dimensional coordinates resulting from the digitising process are then scaled and smoothed before being used to calculate linear and angular displacement-time histories.
Additional kinematic information (velocities and accelerations) is obtained by computing the first and second time derivatives of these displacement data. However, the accuracy of these derivatives will be severely compromised unless the appropriate data processing techniques are used (discussed in Chapter 7). The kinematic information obtained from video can be used to quantify key performance parameters (e.g. a take-off angle during a jump).
Such parameters can then be compared between performers (e.g. novice vs. elite), within performers (e.g. fatigued vs. non-fatigued), or monitored over a period of time (e.g. to evaluate the effects of training over a season). In order to understand the underlying causes of a gi