Prototype Pelvic Motion Algorithms and Real-Time App for Coaches Using the TYPE-

By Naoto Saita

Hi, I’m Naoto from the R&D department at LEOMO, and I’d like to share my findings from one of our coach/athlete testing experiences. In this scenario, they used the TYPE-R with our prototype pelvic algorithms and prototype app for coaches. We were able to test these algorithms and software recently during the 2017 Japan National Championships ITT, which took place in the beautiful northern prefecture of Aomori, Japan.

Let’s look at the winner for the women’s ITT, Eri Yonamine and her coach, Kyosuke Takei.

Real-time feedback using the TYPE-R, prototype web-app, and prototype pelvic MPIs

Athlete: Eri Yonamine

Coach: Kyosuke Takei

Takei and members from LEOMO tested Yonamine’s MPIs (Motion Performance Indicators) beforehand, checking where her MPIs fluctuated when she became fatigued. This gave us a clear idea of what sort of MPI values Takei should be watching out for during the TT.

Takei watched her numbers during the TT using our prototype real-time coaching web app, and provided live feedback to Yonamine:

  1. When Takei noticed Yonamine’s Pelvic Lateral Rotation* became larger than her Pelvic Anterior-Posterior Rotation*, he told her to relax and try to move more calmly.
  2. When Takei noticed that Yonamine’s Pelvic Tilt was too large at times (about 50°), he told her to loosen her grip, relax, and go for a more aggressive position.

*algorithms are currently in beta testing, and not yet available to the public.

Since Takei knows how his cyclist is moving in real-time, he can better pinpoint their movement problems and provide easy to understand feedback, also in real-time. Importantly, he was able to see how the numbers changed based on his feedback, allowing him to see what sort of feedback works or doesn’t work with his cyclist.

Pictured Above: The TYPE-R on a TT bike

Race Data Analysis

Looking at Yonamine’s data after the race, we can see that there are large differences between the MPIs for the first and last laps.

Pictured Above: ANT+ and MPI Data from the LEOMO Web App.

Pictured Above: Range comparisons from the LEOMO Web App.

Takei thinks that watching for the increase in DSS and Pelvic Anterior-Posterior Rotation is key for signaling to Yonamine that her bad habits are back — whole body tension, and especially the tension caused by gripping the handlebars, leading to higher DSS and Pelvic AP Rotation.

Seeing my athlete’s motion quantified in real-time was incredibly beneficial for supporting my athlete during the heat of the TT. During the end of the race, where my athlete was suffering the most, it was highly effective to know in real-time the exact issues that were going on, so that I can give the right feedback at the right times. Yonamine adjusting her posture and movement at key moments was key in bringing her across the finish line to win the ITT. I’m really looking forward to continuing my training with the TYPE-R and finding new ways to utilize it even more.— Takei

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