Getting Started

Install the app

Setup your band

Troubleshooting

Connect the band

Data quality issues

The band turns off

Band dead after update

Using Pylot

Understanding Flow & Fatigue

Optimal time & length

Live recommendation

Daily summary

Trends

Tags

Firmware Update

Poor data quality

Poor data quality

How Pylot manages poor data quality

Many wearables struggle with collecting accurate data, and while some devices fail to alert you to this issue, Pylot prioritizes transparency by notifying you when there are data quality problems. This approach is not only user-friendly but also allows for quick resolutions, ensuring you can maximize the benefits offered by the product.

What is poor data?

Pylot's cognitive performance metrics depend heavily on the quality of the data collected by its EEG and PPG sensors, the latter being used to measure HRV. Poor data quality can occur in several ways:

• EEG Issues: Poor data quality from the EEG sensor often happens if the electrodes are not properly in contact with your skin, if they are in contact with hair instead of skin, or if there is a lot of movement causing the electrodes to shift. The Pylot app is designed to detect these issues and will notify you with a data quality warning.
• PPG Issues: Similar to the EEG, the PPG sensor needs to maintain contact with the skin to capture good data. If the sensor is not in close contact with the skin or has significant movement, the data quality may be compromised. The Pylot algorithm has the capability to detect when it is in proper contact with the skin and whether the collected values are within the expected range based on the last 10 seconds of data.

If adjustments are necessary, please note there is typically a 5-8 second delay before the changes are reflected in the data quality feedback. For more details on resolving these issues, you can refer to this informative article.

How Pylot manages poor data

It's common for there to be brief moments of suboptimal data during sessions with Pylot, but these short periods of poor data quality usually go unnoticed. The system is designed to handle and correct these minor blips effectively, meaning they have minimal impact on the overall quality and integrity of the session's data.

If there is a longer block of poor data (meaning you received an extended poor data warning), then this data is removed from your session summary to avoid misleading feedback.