Sleep Support Apparatus Using Pulse Wave Transit Time
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Solution Overview
Problem
Existing sleep support technologies cannot determine whether a person's body is in a suitable state for sleep, despite detecting sleepiness, leading to ineffective sleep induction.
Innovation Solution
A sleep support apparatus that uses electrocardiographic and pulse wave sensors to measure pulse wave transit time and heartbeat interval, determining a suitable sleep state and adjusting environmental conditions like temperature to facilitate sleep.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse wave transit time is used to determine sleep suitability, then measurement precision is improved, but device complexity increases due to multiple sensors and signal processing requirements
Solution Approach 1:
The system divides the measurement task into separate functional modules: electrocardiographic electrodes for cardiac signal detection, pulse wave sensor for peripheral pulse detection, peak detector for identifying signal maxima, and pulse wave transit time computer for calculating the time difference. This segmentation allows each component to be optimized independently while maintaining overall system precision.
Solution Approach 2:
The patent introduces an intermediary computational process that transforms raw sensor data into meaningful physiological indicators. The peak detector and transit time computer act as intermediaries between the physical sensors and the sleep state determination, converting complex waveforms into a simple time-difference metric that accurately reflects autonomic nervous system state.
2Reliability
If multiple sensors and processing steps are added to accurately determine sleep suitability, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent combines multiple sensing functions into an integrated system where electrocardiographic electrodes and pulse wave sensor work together to measure pulse wave transit time. The signal processing functions (peak detection, time difference calculation) are merged into a unified computational framework that automatically determines sleep suitability without requiring separate manual assessments.
Solution Approach 2:
The system performs self-calibration and automatic determination of sleep suitability through the inherent physiological signals. The peak detector automatically identifies waveform maxima, and the transit time computer automatically calculates the time difference, eliminating the need for manual intervention or complex user setup procedures.
Data Source
AI summary
A sleep support apparatus includes a pair of electrocardiographic electrodes that detect an electrocardiographic signal, a photoelectric pulse wave sensor that includes a light emitter and a light receiver and that detects a photoelectric pulse wave signal, peak detectors that respectively detect the peaks of the electrocardiographic signal and the photoelectric pulse wave signal, a pulse wave transit time clock that obtains a pulse wave transit time from a time difference between the peak of the photoelectric pulse wave signal and the peak of the electrocardiographic signal, a sleep state detector that determines that a user's body has not reached a state suitable for sleep when the pulse wave transit time is less than or equal to a certain threshold, and a forearm heater that increases a temperature of a forearm when it is determined the user's body has not reached a state suitable for sleep.