Sleep Tracking Wearable Technology Solution

Project overview

A solution providing accurate measurement of user’s sleep metrics, including total sleep duration, boundaries and duration of sleep phases, such as REM, light sleep and deep sleep; sleep efficiency and sleep interruptions.

Customer profile

In-house proprietary project

Challenges Challenges

  • Need to design a sleep data analysis technology with high aссuraсy of sleep tracking based on limited sources of data
  • Need for compact design of the wearable device
  • Limited computing capabilities of the microcontroller user in the wearable device.

Technical highlights Technical highlights

  • Developed data acquisition techniques for a physical sensor
  • Developed data filtration and pre-processing algorithm
  • Data analysis and model definition enabled with the help of BaseGroupLab Deductor Studio software
  • Smart alarm – identification of an optimal wake-up moment
  • Developed the model for sleep phases detection
  • Developed an algorithm for sleep tracking, using correlation analysis and cluster analysis.

Business value Business value

  • According to lab test results, the average accuracy of detecting REM sleep phase boundaries is 73% (market median is 70%).
  • Implemented advanced data visualization techniques as a key differentiating function
  • Accuracy was verified based on the indicators of professional medical equipment, such as Nihon Kohden NEUROFAX EEG-1100K electroencelograph and TrackIt (TM) Sleep Walker(TM) polysomnograph.