The latest INSPEC update introduces hypnograms and computed sleep quality metrics. The implementation estimates AWAKE, REM, Light Sleep (NREM1 and NREM2), and Deep Sleep (NREM3 and NREM4) phases using a combination of stillness scoring and detected rapid eye movement patterns from the video stream. Stillness is inferred from frame-to-frame pixel variance, while REM is detected through bursts of eye movement activity from the REM-detection engine.
The hypnogram output aligns well with typical sleep architecture and already offers valuable insight into session dynamics. This lays the groundwork for real-time sleep staging and deeper analysis to optimize cue timing relative to vivid dreams during REM sleep.
There is still lots planed, like adding indicators for when the REM-detection algorithm triggered the audio cues and caching for faster load times, but it is already yielding valuable insights and fun to play with.
 |
 |
 |
 |
The top frame is animated and replays highlights from the session where rapid eye movement patterns were detected. The rest of the frames are stills that can be removed – for when you want to export to an LSD file and share the session, but were caught sleep-talking or at an awkward angle.😅
lucidcode 