Last week, Team BRIT came first in their category at Birkett Relay, a 6-hour-long race at the Silverstone Circuit.
As part of Team BRIT’s mission to allow disabled drivers to race on equal terms, NTT DATA, team BRIT’s sponsor, embarked on a project that combined multi-national teamwork and technology. The project has been supported by an international team from NTT DATA utilizing advanced wearable and analytics technologies from Japan, reports NTT DATA.
The first trial of the project took place in the Birkett Relay, where four members of Team BRIT wore the innovative Hitoe smart shirts. The shirts were custom made for the Team BRIT drivers and in compliance with racing regulations. The Hitoe shirts’ devices captured data about how the drivers’ bodies responded in the race by recording their bio electrical signals (e.g. ECG and EMG).
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Hitoe (Pronounced: He Toe A) smart t-shirt is a real wearable sensor with electricity conductor polymers. This futuristic tool monitors the driver’s heartbeat and breath, his muscle contractions and even his skin PH, transmitting this information into a digital message. NTT DATA, the creator of this shirt produced it in their Italian factory in Cosenza.
Hitoe allows the team to control drivers’ activity, performance and health, providing new data to analyze. By pinpointing which muscles are working while driving, sport coaches are able to prepare more specific and effective physical trainings. It also makes it easier to find any driving mistakes and correct them.
Access to real-time data makes wearable technology particularly useful. It’s helpful when you know what happened, but in many professions – like healthcare – knowing what is happening right now matters a lot more.
The theory also applies to various other jobs. Knowing when someone is tired before they admit it could make major enhancements in employee safety.
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NTT DATA conducted a study on nurses to find out when they felt tired. The researchers placed sensors in scrubs. The nurses working 12-hour shift started at 8 pm. They said they became particularly tired around 2 a.m. Reviewing the bio-signals showed that a majority of them were tired around midnight. The nurses were actually fatigued well before they “felt” tired. Since a tired employee is a less effective employee, building in an earlier break time helped ease the problem.
