Gait Analysis is a systematic study of human motion. It is utilized in the professional context to gain deeper insights into the understanding of common biomechanics linked with injuries. It is a vital tool to identify the causes of a player’s injury such as faulty running mechanics, musculoskeletal impairment, a training error or extrinsic factors.
The way that future monitoring perspective is going, we have this information to help MDT teams with reduction of injury risk strategies and improving performance. The systems that are used in the laboratory are the Time-motion capture systems and Force-plate platforms, however the MDT teams need to bring those systems to the field. This creates a new level of opportunity to test players in the field (providing context to movement) opposed to testing them in the lab.
Looking at the Running Cycle, a research study done by Katie Small, shows that there is an increase in the change of the knee extension and hip extension around the sprint mechanics when players were at risk of hamstring injury. The change in under fatigue caused greater increased risk towards hamstring muscle groups.
Research was conducted using Playermaker devices amongst Elite Teams. Using this technology new parameters can now be measured in the Elite context on the field instead of in the lab. For instance, how much time when there is heel strike to push off (how much time the foot is in contact with the ground. In the lab, during drop jumps practitioners use contact duration to measure a player’s reactive strength index.
Bringing that lab monitoring to the field from a physical point of view is where this new technology is taking research and ultimately trying to help practitioners to bring this information to life.
In this particular session, the player took part in a 6 set exercise where the player had to run for 2 minutes at the fastest speed and rest for 1 minute.
The bar graph is looking at “left vs right foot usage” , if it was a positive number it would reflect a left bias and if it was a negative number it would reflect a right bias. Two weeks before this session, this player had recovered from a calf injury.
Red Line: Total Distance Covered
Bar Graph: Contact Duration
Practitioners can see a change in his mechanics throughout the session, even though the player is covering the same distance, through the new gait analysis that the technology has introduced -Bringing the Lab to the Field-now practitioners can actually see there was a change in the player’s contact duration by over 15%.
Due to this, the following day the player suffered a calf injury- a recurrence injury to the left calf and the player had to pull out of training due to a right calf injury due to the player overloading both of his calves. The player overcompensated by not using his left calf as much and using his right calf too much.