Sleep Stage Determination via Heartbeat Cycle Difference Analysis
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Solution Overview
Problem
Existing sleep stage determination methods require special equipment like an air mat and body movement information, making it challenging to precisely determine sleep stages without these resources.
Innovation Solution
A sleep determination device that uses a heartbeat obtaining unit to calculate heartbeat cycles and difference values, generating distribution data to determine sleep stages based on predefined criteria, allowing for precise sleep stage discrimination using only heartbeat information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If special equipment such as air mat is used to estimate sleep stage, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The invention extracts and utilizes only the heartbeat signal component from the complex physiological data, eliminating the need for air mat equipment and body movement sensors. By focusing solely on heartbeat cycle analysis, the system achieves sleep stage determination without requiring special equipment, thus reducing device complexity while maintaining measurement precision through sophisticated signal processing.
Solution Approach 2:
The invention replaces the mechanical/physical measurement system (air mat, flow velocity sensors) with a biological signal-based system (heartbeat analysis). Instead of measuring physical parameters like airflow or body movement, the system processes heartbeat temporal patterns to determine sleep stages, substituting mechanical measurement with physiological signal analysis.
2Measurement precision
If body movement information is obtained to estimate sleep stage, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The invention extracts and utilizes only the heartbeat signal component from the complex physiological data, eliminating the need for air mat equipment and body movement sensors. By focusing solely on heartbeat cycle analysis, the system achieves sleep stage determination without requiring special equipment, thus reducing device complexity while maintaining measurement precision through sophisticated signal processing.
3Device complexity
If only heartbeat information is used to determine sleep stage, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The invention segments the heartbeat signal into discrete heartbeat cycles and further segments these cycles into multiple feature parameters (cycle length, variability, frequency components). By dividing the complex heartbeat signal into manageable segments and extracting specific temporal characteristics, the system achieves precise sleep stage determination using only heartbeat information, compensating for the limited data source through comprehensive feature extraction.
Solution Approach 2:
The invention transforms the one-dimensional heartbeat signal into multi-dimensional feature space by calculating temporal characteristics, variability metrics, and frequency components. This dimensional expansion allows the system to capture rich physiological patterns from the limited heartbeat data, enabling precise sleep stage determination without additional equipment by exploiting the temporal dimension of the heartbeat signal.
Data Source
AI summary
An object of the present invention is to provide a sleep determination device and a sleep determination method capable of precisely determining a sleep stage based on heartbeat information of a subject. The sleep determination device and the sleep determination method according to the present invention obtain the heartbeat of the subject, calculate a heartbeat cycle for each heartbeat based on the obtained heartbeat, calculate difference values until obtaining Nth-degree difference values set in advance with difference values between the successive heartbeat cycles as first-degree difference values and difference values between the successive first-degree difference values as second-degree difference values, generate a return map and a histogram indicative of a distribution of the respective values in a predetermined period of time for each of the heartbeat cycles and the difference values from the first-degree difference values to the Nth-degree difference values, and determine a sleep stage of the subject based on the generated return map and the histogram by referring to a return map and a histogram for determination set in advance for each sleep stage.