Decision support algorithm for personalized sleep staging application

SATT LUTECH



09 Juillet 2019

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Fields

NICT

Sectors

Health

Market challenges:

Sleep staging is a fundamental step in diagnosis and treatment of sleep disorders. However, it is a time-consuming and tedious task, which has to be performed by medical experts.

Hypnograms (graphs that represent the stages of sleep as a function of time) are usually obtained by visually scoring the recordings from electroencephalogram, electrooculography and electromyography. The data is heterogeneous as there is a multiplicity of physiological parameters recorded at night (using a wired connection which may be a source of disturbance for the patient’s sleep) and rules of interpretation (on the basis of the American Academy of Sleep Medicine – AASM - textbook).

There is a need for integrating and analyzing information from heterogeneous data sources with high accuracy in order to be able to automatically read hypnograms.

Innovative solution:

The solution is a novel system that mimics visual decision making process of clinical sleep staging using symbolic fusion and an evolutionary algorithm (for adaptive thresholds), with an approach based on AASM guidelines.

Suggested applications:

  • Home sleep testing
  • Clinical application : decision support software for the diagnosis of sleep disorders
  • E-learning and validation of polysomnography data interpretation
  • Software tool for monitoring sleep disorders and loss of vigilance (risk factors for accidents at work - drivers, pilots, etc.)

Competitive advantages:

  • Knowledge integration (practice guidelines) into an automated medical decision support system
  • Software validated with sleep physicians (APHP - France) by a gold standard database set (130 PSG)
  • Work time optimization for sleep physicians
  • Annotation of all sleep events allows deeper causality relationship analysis of sleep diseases
  • Simplification of sleep staging reports
  • A proof of concept (algorithm and software) has been validated
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