Train.Red APP

Unlock peak sports performance with Train.Red! Activate your most trainable assets—your muscles—to improve pacing, strength, and stamina.

About this app
The official app for the Train.Red muscle oxygen sensors, the new metric for performance.

To move, your muscles need energy. The most efficient way to get this energy requires oxygen. We measure the oxygen saturation in your muscles to help you improve.
Not every athlete has a team of scientists helping them with their physiological data, we measure data from your muscle and translate this into useable insights, in real-time.

- Monitor your physiological power and perform easy exercise tests as an endurance athlete.
- Know when your muscle is fully recovered and ready for the next set when doing strength.


What’s more?
- Cloud functionality to allow workout analysis at home, even when you perform in the gym.
- A Team/organisation structure that allows multiple athletes to use the sensors.
- Actionable insights after your training or scientific analysis with access to raw data.
- Live view with data overlay to match measured fatigue with movement patterns.
- Muscle States, Protocols, Dashboard, Training Menu, Muscle Stress Score, and much more.


How to start with Train.Red:

Create a user profile and connect your sensor.
No sensors yet? The Train.Red app requires the Train.Red sensors for full functionality (https://train.red/).

Connected your FYER or PLUS? Nice, you are ready to BE AHEAD.

What does Train.Red do for me:
Whether you’re an athlete, coach, scientist, physio, or anyone involved in sport, Train.Red has something to offer you. Simply because your muscles play a key role in human movement.

We track your muscle oxygenation, more specifically, the hemoglobin concentration changes.
The Train.Red sensors measure:
- SmO2, Muscle Oxygen Saturation (%)
- O2Hb, Oxyhemoglobin (mM)
- Hhb, Deoxyhemoglobin (mM)
- Thb, Total hemoglobin (mM)
- HbDiff, the Hemoglobin Difference (mM)

If this sounds like Abracadabra, no worries. We display the oxygen saturation in your muscle live and use the other metrics to provide you with actionable insights in real-time. Our AI and advanced analysis options translate this data into 5 different muscle states showing you if your muscle is recovering, or approaching its limits.
If this physiological data sounds familiar, perfect. We allow exporting your data to .csv or .fit files for an in-depth analysis of all your data.
Every single training session is stored in our cloud and can be analyzed or exported afterward.

How do I use Train.Red?
The Train.Red sensor is a light-based wearable that you wear directly on your skin. You’re free to place the sensor anywhere on your body but know that this is a hyperlocal metric that will only tell you something about the exact location you place the sensor.
We recommend wearing the sensor on a primary involved locomotor muscle, a place on your body that is active during the activity you’re performing.
e.g. on your thigh during cycling or squats, the middle part of your upper leg during running, or on your lower arm during climbing.
Of course, you are free to use more than one sensor! You can connect up to 4 sensors simultaneously and measure multiple areas at once.

You’re not bound to this smartphone application.

The Train.Red hardware is integrated into 3rd party apps allowing you to easily synchronise your data from multiple sources.
Train.Red sensors can be connected to most Wahoo’s, Garmin’s, Suunto’s and several other devices.

More information can be found on our website
https://train.red/

Recent changes:
!Hotfix for data migration!
New Features
Significant upgrade to the Test feature, now including almost 30 sport-specific tests, max and submax protocols.
Advanced analytics for determining thresholds and additional performance metrics
Improvements & Fixes
Firmware updates across all devices for improved stability and performance
Battery performance improvements addressing previously reported issues
Resolved bugs that could cause the system to remain in processing mode or fail to detect sensors