REM Sleep Enhancement via Closed-Loop Sensory Stimulation
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Solution Overview
Problem
Current sleep monitoring systems do not effectively enhance rapid eye movement (REM) sleep by delivering sensory stimulation, as they primarily focus on deep sleep stages and lack automated, accurate methods for stimulating REM sleep without manual intervention.
Innovation Solution
A closed-loop system using sensors, hardware processors, and neural networks to detect REM sleep and deliver tailored auditory stimulation automatically, adjusting parameters like intensity, timing, and tone frequency based on brain and cardiac activity to enhance REM sleep duration without causing arousals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If state-based sleep monitoring systems deliver stimulation responsive to EEG parameters breaching deep sleep thresholds, then deep sleep can be enhanced, but REM sleep cannot be enhanced because the systems do not detect or stimulate REM sleep stages
Solution Approach 1:
The system changes the detection parameters from traditional EEG-based deep sleep thresholds to multiple physiological parameters including cardiac activity ratios (LF/HF), respiratory patterns, and EEG delta wave activity to accurately detect REM sleep stages, enabling targeted stimulation of this specific sleep phase
Solution Approach 2:
The system segments sleep monitoring into distinct stage detection protocols, with specific algorithms for identifying REM sleep separate from deep sleep detection, allowing independent enhancement of different sleep stages through stage-specific stimulation protocols
2Reliability
If manual intervention is used to deliver sensory stimulation during REM sleep, then REM sleep enhancement is possible, but the system becomes complex and inconsistent because manual timing and delivery are difficult to standardize
Solution Approach 1:
The system implements closed-loop feedback by continuously monitoring physiological parameters, automatically detecting REM sleep onset and duration, and adjusting stimulation timing and intensity accordingly, ensuring consistent and reliable delivery without manual intervention
Solution Approach 2:
The system performs self-monitoring and self-adjustment of stimulation parameters based on real-time detection of sleep stage transitions, eliminating the need for manual timing and standardizing delivery through automated decision-making algorithms
3Duration of action of moving object
If auditory stimulation is delivered during REM sleep to enhance it, then REM duration increases, but the stimulation might cause arousals that interrupt sleep if not precisely controlled
Solution Approach 1:
The system delivers auditory stimulation in periodic bursts synchronized to the detected REM sleep cycle, using intermittent stimulation patterns that reinforce REM sleep without causing continuous disruption or arousal
Solution Approach 2:
The system dynamically adjusts stimulation parameters including intensity, frequency, and duration based on real-time detection of REM sleep depth and stability, reducing intensity near transition points to prevent arousals while maintaining enhancement during stable REM periods
Data Source
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AI summary
The present disclosure pertains to a system and method for automatically detecting rapid eye movement (REM) sleep and delivering sensory stimulation to prolong REM duration, without disturbing sleep. The sensory stimulation maybe auditory or other stimulation. The system and method ensure timely delivery of the stimulation and automatically adjust the amount, intensity, and/or timing of stimulation as necessary. REM sleep is detected based brain activity, cardiac activity and/or other information. REM sleep may be detected and/or predicted by a trained neural network. The amount, timing, and/or intensity of the sensory stimulation may be determined and/or modulated to enhance REM sleep in a subject based on one or more values of one or more intermediate layers of the neural network and one or more brain activity and/or cardiac activity parameters.