Validation of photoplethysmography-based sleep staging compared with polysomnography in healthy middle-aged adults

P. Fonseca, Tim Weysen, M.S. Goelema, Els Møst, M. Radha, C.F.W. Lunsingh Scheurleer, Leonie van den Heuvel, R.M. Aarts

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Abstract

Study Objectives: To compare the accuracy of automatic sleep staging based on heart rate variability measured from photoplethysmography (PPG) combined with body movements measured with an accelerometer, with polysomnography (PSG) and actigraphy. Methods: Using wrist-worn PPG to analyze heart rate variability and an accelerometer to measure body movements, sleep stages and sleep statistics were automatically computed from overnight recordings. Sleep-wake, 4-class (wake/N1 + N2/N3/REM) and 3-class (wake/NREM/REM) classifiers were trained on 135 simultaneously recorded PSG and PPG recordings of 101 healthy participants and validated on 80 recordings of 51 healthy middle-aged adults. Epoch-byepoch agreement and sleep statistics were compared with actigraphy for a subset of the validation set. Results: The sleep-wake classifier obtained an epoch-by-epoch Cohen's κ between PPG and PSG sleep stages of 0.55 ± 0.14, sensitivity to wake of 58.2 ± 17.3%, and accuracy of 91.5 ± 5.1%. ? and sensitivity were significantly higher than with actigraphy (0.40 ± 0.15 and 45.5 ± 19.3%, respectively). The 3-class classifier achieved a κ of 0.46 ± 0.15 and accuracy of 72.9 ± 8.3%, and the 4-class classifier, a κ of 0.42 ± 0.12 and accuracy of 59.3 ± 8.5%. Conclusions: The moderate epoch-by-epoch agreement and, in particular, the good agreement in terms of sleep statistics suggest that this technique is promising for long-term sleep monitoring, although more evidence is needed to understand whether it can complement PSG in clinical practice. It also offers an improvement in sleep/wake detection over actigraphy for healthy individuals, although this must be confirmed on a larger, clinical population.

Original languageEnglish
Article numberzsx097
JournalSleep
Volume40
Issue number7
DOIs
Publication statusPublished - 1 Jul 2017

Keywords

  • Actigraphy
  • Computerized analysis
  • Heart rate variability
  • Photoplethysmography
  • Scoring
  • Sleep tracker
  • Statistics
  • Heart Rate/physiology
  • Humans
  • Middle Aged
  • Photoplethysmography/methods
  • Wakefulness/physiology
  • Male
  • Healthy Volunteers
  • Polysomnography
  • Wrist
  • Adult
  • Female
  • Sleep Stages/physiology
  • Movement/physiology

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