Japan’s Leomo unveils motion analysis wearable technology for cycling athletes

Leomo was unveiled at a track for cycling race in the US.

See the original story in Japanese.

“Raise your foot up a bit more, good, keep it up” – some of you who ever had played sports, was a runner or been into fitness may have been given this type of admonition.

However, words are always subjective and ambiguous. If there is any detailed reference or scoring which is completely precise for everyone, conversations upon training may change dramatically. Japan’s Leomo has unveiled a device just for this.

Leomo, developing IoT devices for sports use, launched this month a wearable device called Type-R. It provides useful data using sensors and display device, supporting athletes to maximize their training performances. With this device, athletes can optimize their playing forms or power efficiencies, as well as preventing injuries and for rehabilitation.

Type-R can be attached to a bicycle in a way like doing with a cycling computer.

According to Kunihiko Kaji, co-founder / CEO of Leomo, the firm plans to sell the device to invited users only for a while and aims to commence general sales by around this May.

Leomo was founded in 2012 and subsequently launched a logging app for fitness use called Lemonade (it was also the initial company name) in 2013. Fundraising $5.8 million from the Foxconn Group and others in August of 2015, the firm has been developing this device since then. It has 28 staffers, with offices in Tokyo and San Diego in the US.

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Motion capturing for usual training


Motion capturing may be one of the well-known methods for digitalization of the human motion. Putting markers on a person’s body, it digitalizes his motion by a fixed-point observation with cameras set in a specialized studio. The greatest feature of Type-R is that these motion sensors can be taken outdoors.

Kaji spoke about the limitations of conventional motion capturing:

Conventional motion capturing requires an operator and costs tens of thousands of dollars. Moreover, the observation location was limited due to the need for cameras upon calibration.

Type-R enables athletes or coaches to collect motion data under the same condition as the general training environment. For example, a coach can confirm whether his advice was conveyed to an athlete accurately when he is trying out a new form.

Kaji explains the need for motion capturing upon training:

Actually, people cannot easily move their body precisely as they intend. Although you may think yourself that you are just straightening out, that may not be the reality. This gap between the brain and the body cannot be verbalized yet. Therefore, it is difficult to make someone realize things that cannot be conveyed in words.

Five motion sensors attached to the body

Type-R digitalizes the body motion by measuring pedal speed, vertical motion or tilting angle of the pelvis with five sensors attached to his / her body. Since these collected data will be uploaded to the cloud via Wi-Fi and can be analyzed anywhere, users can also receive remote instructions.

Digitalization of the “beautiful form”

After the demo, a feedback could be heard: Type-R tells us what to do and why we should do so. Once we know the “precise” reference, coaches can suggest the best plan for improving the athletes’ performances.

For example, even the form of a bike racer holding an excellent record is not always beautiful. How is the “beautiful form” defined?

To clarify the evaluation criteria between coaches and athletes, Leomo announced the establishment of a think-tank named IMA (Institute of Motion Analysis) consisting of global sports experts including sports scientists, exercise physiologists, coaches, physical therapists and professional bicycle fitters.

The mission of IMA is to evaluate the sports science being used at the top of the sports world based on objective data, in order to cultivate the field where motion capturing can be utilized more effectively.

Many experts such as sports scientist or athletes participate in Leomo’s project

It may be easier to understand the vision by imaging a scoring method like Tabe-log (Japan’s restaurant/diner scoring portal) in the sports world; the total score of a top athlete’s form is 4.5 and mine is 3.0 – what is the difference between him and me? Leomo visualizes such kind of motion differences utilizing data and offers a common understanding.

If it is realized, one can explain what is the motion with least possibility of injuries or which balance is the most ideal for running fast. Kaji explains Leomo’s future:

The perfect circle is beautiful, isn’t it? But no one can draw it free hand. I think professional athletes are people who can draw a circle close to the perfect one. We aim to create evaluation criteria as to the best motion for drawing a beautiful circle for each user.

Translated by Taijiro Takeda
Edited by “Tex” Pomeroy