Hello everyone, Joe from LEOMO here. Today I want to go over how I identify movement and strength imbalances in a marathon runner with the Live Video Sync application, and use the data to create a targeted training plan to improve performance.
I want to start off with a question: Why analyze running motion?
Running is a technical movement. Running fast over long distances requires immense energy input and coordination/synchronization of many parts of the body through thousands of cycles of motion. Thus, athletes and coaches looking to improve running performance must consider both the physiological costs as well as the biomechanical costs. Tracking changes in biomechanics, especially at key times of the training and racing seasons, can help to inform training decisions.
What happens when fatigue is high? What about when we are fully rested and in peak fitness? On a shorter scale, what happens to our biomechanics after long workouts, or after strength training?
Aside from tracking changes, I want to see how we can optimize motion such that we are putting as much of our energy as possible into achieving our goal. Energy outlets cost us oxygen and speed. Could we be going faster at the same metabolic cost over a given race distance?
Let's introduce our athlete...
Athlete Type: Marathon Runner
Personal Best: Tokyo Marathon 2019
Strengths: Distance Events
Needs: Durability, Strength (history of cramping, loss of power in right leg late in races)
- Set a new marathon PR
- Improve efficiency and durability late in races and during training
Furu has reportedly been experiencing cramping and "loss of power" in his right leg during races and long bouts of training. He claims this has prevented him from reaching his potential in races. Because of this, today we will prioritize observing differences between his left and right side during his running, specifically in the trunk and hips.
For the running assessment we will place our motion sensors on Furu’s feet, torso (bottom of sternum), and pelvis (sacrum). This setup will allow us to capture the motion of his pelvis and torso in relation to the motion of his feet.
Initial Visual Observations:
Based on our visual analysis of Furu’s running, there appears to be asymmetrical collapse of the torso on right vs left side during mid-stance phase. Using some specific motion sensor outputs, we can begin to apply some quantifiable metrics to these observations. To capture this movement and begin to analyze further we will look at data from Foot Acceleration Y and Torso Gyro Z.
Why should we look at these two sensor behaviors?
- Foot Acceleration Y will give us a timestamp that represents footstrike (highest foot acceleration).
- Torso Gyro Z will give us a measure of the velocity at which the torso is laterally rotating.
- Using this combination we can look at not only what is happening at the torso during the stride, but also when each action occurs relative to footstrike.
Let’s Start with Foot Acceleration Y:
In this view, the darker blue line is the left foot, and the lighter green line is the right foot. Each one of those sharp acceleration peaks is associated with Furu’s respective foot hitting the ground. This gives us a useful time stamp when looking at the motion data to know when each foot is striking the ground.
Next Let’s Look at Torso Gyro Z:
In this view we can see the yellow/orange line displaying the output of the sensor on his sternum. This output will measure the lateral rotation of Furu’s torso. Based on the orientation of our sensor, any negative data will indicate the sensor is rotating towards Furu's left side (rib cage tilting down towards his left hip), and any positive data will indicate the sensor is rotating towards Furu’s right side (rib cage tilting down towards his right hip).
If we look at his torso position during mid-stance phase, we see on the right side his torso sensor hits a peak value after footstrike of 133.8dps, and on the left only 50.2dps. Although we are only looking at one stride, this trend extends through his entire run.
Putting them both together:
Now that we’ve looked at the individual components of Furu’s analysis today, let’s put it all together and view his motion with all 3 sensor outputs.
We can see his left and right foot strikes and the subsequent Torso Gyro Z spikes immediately after them. On both sides, Gyro Z peak occurs several milliseconds after peak Acceleration Y of the foot. However, we can see that the magnitude of lateral rotation on the right is quite high compared to the left. This indicates that the trunk and hips are not maintaining position well during right foot mid-stance phase.
At this point, we have analyzed the running motion and identified some key areas of interest. What I would like to do now, is further examine Furu's ability to maintain their center of mass (COM) in single leg positions. For this we will perform a series of movement assessments.
For this, we will place our motion sensors on Furu’s pelvis (sacrum) and torso (sternum). This setup will allow us to capture how his trunk and hips move in single leg positions. As stated above, we want to capture any compensatory shifting of his COM in single leg positions.
The specific sensor behaviors I will use to capture the motion of interest in this exercise will be the Torso Acceleration Z output and the Pelvis Gyro Y output.
Why these specific behaviors?
I will use the Torso Acceleration Z output as a timestamp for when he begins and ends his sagittal plane movement, and the Pelvis Gyro Y output to observe any lateral rotation of his pelvis.
Start of Movement:
For me, this was the most telling feature of the movement. In this position, we are using the Torso Acceleration Z to indicate when the forward motion of his trunk begins. If we look at the Waist Gyro Y data at the moment motion begins, we can see a spike in the Gyro Y output. This indicates a rotation of the hips towards the standing leg (a compensatory shift of the athlete's COM) the moment he enters a single leg position. On the left side, we see normal variation of the pelvis throughout the movement.
End of Movement:
In this image, I am displaying the end position of the eccentric phase of this movement. Visually, we can see additional compensatory shifts in the COM. When standing on the right leg, the left leg shifts behind his standing leg, and his torso swings towards his right side. These features are not present on his left leg.
These observations support our findings from the running analysis. A primary target will now be increasing Furu's ability to maintain his hip and trunk position during his running stride. Being able to resist some of these compensatory movements will allow for more energy to be directed towards his forward motion.
Why do a Running & Movement Assessment?
The first thing I want to see is how the runner’s motion presents naturally. For the running analysis, we selected marathon pace because that is the event he wants to improve at. A movement assessment based on our run observations can help us to further identify and clearly define targets for improvement. Together with both of these analyses, we can develop and implement changes to Furu's training regimen, with specific criteria for tracking changes.
Solutions and Future Directions:
Listed here are some of the key components we will be introducing to Furu’s training program. An important note is that Furu has never done strength training or plyometrics prior to this, and has not utilized high speed interval training of any sort. This leaves great potential for improvement in these areas. We will utilize a strength & conditioning program to develop core and hip strength and also develop leg stiffness. Next, we will progressively introduce some different types of high speed, high power workouts into his run training to help us translate the strength and conditioning work into his running motion and ultimately his marathon goal.
Joseph Cavarretta, MS, ACSM-EP
LEOMO Sport Scientist & Coach