Automated Sleep Phenotyping System Using Stimulus-Triggered Sensor Analysis
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Solution Overview
Problem
Conventional methods for determining sleep phenotyping parameters are labor-intensive and inefficient, often requiring coordinated adjustments to apparatuses and complete data gathering before parameter determination can occur, lacking automation and accuracy.
Innovation Solution
A system comprising a sleep sensor, a parameter sensor, and a processor that generates and processes output signals to determine sleep stages and phenotyping parameters, using a stimulus generator to provide stimuli and gather information on parameters like critical pharyngeal closing pressure, upper airway vibration, and arousal threshold, enabling automated and enhanced phenotyping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to determine sleep phenotyping parameters, then information about sleep characteristics can be obtained, but the process is labor-intensive and requires coordinated adjustments to apparatuses
Solution Approach 1:
The system automatically determines sleep phenotyping parameters by processing sensor data through algorithms without requiring manual coordination or adjustment of apparatuses. The processor autonomously analyzes sleep stage data, respiratory effort signals, and other physiological parameters to compute phenotyping metrics, eliminating the need for caregiver intervention and reducing operational complexity while maintaining measurement precision.
2Measurement precision
If conventional methods are used to determine sleep phenotyping parameters, then parameter information can be obtained, but the process is inefficient and time-consuming
Solution Approach 1:
The system continuously processes sleep data in real-time during the sleep study, rather than requiring complete data gathering before analysis. The processor continuously computes sleep phenotyping parameters as sleep stage data and physiological signals are collected, enabling efficient determination of parameters without waiting for the entire sleep study to complete, thereby improving productivity while maintaining accuracy.
3Extent of automation
If automated determination is implemented, then labor requirements are reduced, but system complexity increases
Solution Approach 1:
The system uses a multi-functional processor that handles multiple tasks including sleep stage classification, respiratory event detection, and phenotyping parameter calculation within a single device. This consolidates what would otherwise require multiple separate apparatuses and coordination systems, achieving high automation while managing complexity through integrated multi-functionality rather than numerous separate components.
Data Source
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AI summary
A system (10) that determines one or more sleep phenotyping parameters of a subject. In one embodiment, the system comprises a sleep sensor (14), a stimulus generator (18), and a processor (20). The sleep sensor generates signals that convey information related to the physiological functions that indicate the sleep stage of the subject. The stimulus generator provides a stimulus to the subject that enables information related to the sleep phenotyping parameters to be determined. The processor receives the signals generated by the sleep sensor and is in operative communication with the stimulus generator. The processor (i) determines, based on the signals received from the sleep sensor, whether a trigger condition related to the current sleep stage of the subject is satisfied, (ii) controls the stimulus generator to provide the stimulus to the subject if the trigger condition is satisfied, and (iii) quantifies the response of the subject to the stimulus.