Morphic Sensors for Respiratory Parameters Estimation: Validation against Overnight Polysomnography

Area of Science:

• Biomedical Engineering
• Sleep Medicine
• Wearable Technology

Background:

• Effective monitoring of sleep respiratory disturbances is crucial.
• Current methods like polysomnography are invasive and time-consuming.
• There is a need for non-invasive, accurate sleep monitoring solutions.

Purpose of the Study:

• To evaluate the performance of a novel wearable morphic sensor for respiratory monitoring during sleep.
• To compare the accuracy of morphic sensors against traditional polysomnography.
• To assess the sensor's ability to capture respiratory rate and chest/abdominal motion.

Main Methods:

• A non-invasive wearable stretchable morphic sensor embedded in a t-shirt was used.
• 32 participants with sleep-disordered breathing underwent an overnight in-laboratory sleep study.
• Respiratory parameters from morphic sensors were directly compared to polysomnography data.

Main Results:

• The morphic sensor achieved approximately 95% (95 ± 0.7) accuracy in computed respiratory parameters compared to polysomnography.
• The sensor does not require direct skin contact.
• Simultaneous capture of respiratory rate and chest/abdominal motion was demonstrated.

Conclusions:

• Novel wearable morphic sensors offer a viable, non-invasive alternative for respiratory monitoring during sleep.
• These sensors can accurately capture key respiratory metrics.
• This technology has the potential to improve sleep study diagnostics.