Blueberry uses brain sensing (fNIRS) to understand your internal state and context sensing (motion, camera, sound) to understand your environment. Together, these enable you to gain deeper insight into how, why, and when your mind activates during the day. With head up information, you can understand how your mind responds throughout the day.
Blueberry uses functional near infrared spectroscopy (fNIRS) to measure oxygenation of blood in the brain. Our algorithms process brain and image data to extract information about users’ mental states, including energy, stress, mental load, and more.
Beyond the basic physiological measurements estimations (heart rate, HRV, and respiratory rate) we estimate perceived mental states based on validated models from datasets we collect. One we call "perceived stress", and one we call "perceived energy", we also have an estimation towards mental activity.
- For an overview of the history of fNIRS, see a brief history on fNIRS brain sensing.
- fNIRS was invented in 1977, but wasn’t applied in a research setting until early 90's.
- An overview of fNIRS related brain sensing, how it works, and applied machine learning techniques on the data.
- How fNIRS can be used to measure mental workload; meaning how much effort the mind is undergoing during a specific task.