 This is a version of my ISB presentation on inter-individual variation in coordination and control of counter-movement jumps. A link to the full conference abstract is available in the description below the video, as are links to each of the papers mentioned in the presentation and various other resources. So before I start, I'd like to say a big thank you to my co-author Rob Needham from Staffordshire University. It's been great to work with and particularly learn from Rob throughout this project, so thanks Rob. Coordination and control then. I've put some definitions up on screen, but for example, intra-individual coordination refers to the coupling relationship between body segments. Measures of control include amplitude, velocity, acceleration and force, and both coordination and control lead to the performance outcome. Some example coordination patterns that I'll refer to include in-phase coordination, where both segments rotate in the same direction. Anti-phase coordination, where both segments rotate in opposite directions. Proximal dominance means that the proximal segment is the dominant contributor to relative movement, whereas distal dominance means the distal segment is the dominant contributor. Previously during counter-movement jumps, coordination has been described at the group level. So for example, the thigh shank couple papers have reported an anti-phase and thigh dominated movement throughout the majority of the eccentric and concentric phases, but with an in-phase shank dominated transition. However, despite substantial inter-individual variation in results, particularly around movement initiation and the transition between phases, the individual strategies leading to this variation are yet to be explored, so our aim was to do exactly that. To do so, we analyzed the highest of three maximal effort counter-movement jumps by each of 16 recreationally active males recorded using an 18 camera vicon system. We qualitatively assessed coordination using an angle angle plot. So for this example, we have time normalized thigh shank data and a small increase in distal segment angle with a greater decrease in proximal segment angle would refer to an anti-phase proximal dominance. We can use vector coding to provide a more quantitative assessment of that coordination. So here we use the vector orientation between adjacent time normalized data points relative to the right horizontal and the outcome measure is referred to as the coupling angle. We can map that coupling angle onto a coordination pattern classification. So again, sticking with the same example, we have anti-phase proximal dominance of 65%. Each quadrant of a unit circle is 100 gradient, so it's relatively easy therefore to convert that to a percentage dominance, where a 45 degree angle would be 50-50 between the two segments. It's important to remember that the darker shade within each quadrant refers to distal dominance, whereas the lighter shade is always proximal dominance. And so if we apply this colour mapping technique at each normalized time point throughout the movement, we can visually assess what's happening in terms of coordination throughout that movement. If you want more information on the data visualization techniques, then I refer you to the need a metal paper currently highlighted on screen. In this visualization, bar height represents the segmental dominance from 50 to 100%, and bar colour again represents the coordination pattern classification as in previous slides. Vexicoding alone, however, cannot provide us a measure of control, such as range of motion or angular velocity, and these often differ even when coordination is similar between individuals, so it's important to include these. And in our example, the dotted line represents the inter-datapoint range of motion of the dominant segment. So if we take a look now at our group mean results at the thigh-shank couple, we see that we have an anti-phase and thigh-dominated coordination pattern during the majority of both the eccentric and concentric phases, where the level of dominance tends to decrease as the phase progresses due to increasing shank contribution, despite a corresponding increase in thigh range of motion. We also see an in-phase coordination pattern at the transition, so overall replicating the previous results at the group level. We can also use either bar height or colour mapping to show the inter-individual coordination variability, which again, as with previous results, is greatest at around movement initiation and the transition between phases. However, there are a number of limitations with this approach that need to be acknowledged. For example, we can't tell whether this variation, particularly at the transition, is spatial or temporal in nature. We also see a roughly inverse relationship between inter-datapoint range of motion and the coordination variability due to artefacts when range of motion is low. A number of alternatives have been proposed to deal with this, such as the use of ellipses or confidence intervals on the angle-angle plot by stock, MOLNU and others. However, at this point, our emphasis is not on quantifying the variability itself, but going on to look at the individual strategies that lead to this variability. And so to do that, we can plot the 16 individual participants ranked from the highest jump height through to the lowest. And to start with, we can see that there are a number of commonalities between individuals, which is useful from a coordination profiling perspective. We also see that the control often differs even when coordination is similar. But to focus on differences, one of the main things that stands out to me at least is at movement initiation, where some individuals have a blue anti-phase initiation, and other individuals have a green in-phase initiation. And both strategies were used successfully within the cohort, for example, by our two highest jumpers. So I'll dig into these representative examples in a bit more detail. We classified them as a deep or a shallow counter-movement strategy. The deep strategy has a greater inter-datapoint range of motion and a relatively longer counter-movement phase. Previously, it's initiated with an anti-phase and thigh-dominated movement initiation, whereas the shallow technique is initiated with an in-phase movement. And there's actually quite a large level of dominance by the thigh because we're seeing very little shank movement during this counter-movement as it remains relatively upright until a late, rapid shank counter-movement. So let's look at the same two individuals but at a different joint now, so the hip, focusing on the trunk thigh couple. We again see many of the same differences in range of motion or the duration of phases. But to pick on one other thing, we can see that at the transition, the deep is coloured green and the shallow is red. So these are two examples where both are in phase. For the deep strategy, the proximal trunk segment reverses its direction first, whereas for the shallow strategy, the distal thigh segment reverses its direction first. So again, these are just two representative examples. The point here is simply to demonstrate some application of the data visualization techniques, but also to give some examples of inter-individual differences that would be lost if we only analyse the group mean coordination patterns. To conclude, the group mean coordination patterns did replicate previous results, which included the greater inter-individual variation at movement initiation and transition between phases. And we've identified both a deep and a shallow strategy, both of which we use successfully within the cohort. These effects include the addition of alternative measures of control and also exploring the relationship between coordination, control and performance outcome. Finally, we conclude the group level analysis of counter movement jump coordination and control masks important to inter-individual variation in movement strategies. Thank you very much for watching. If you have any questions, then please leave a comment. If you want to keep up to date with any future videos, then please click subscribe and the bell next to it to receive notifications. Thank you very much.