Wearable Respiration Phase Detection via Sensor Correlation
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Solution Overview
Problem
Wearable electronic devices face challenges in accurately distinguishing between inhalation and exhalation phases of respiration due to low bit rates for sampling, especially when physiological changes are not directly measured from the body, leading to incorrect measurement possibilities and difficulty in distinguishing between the two phases.
Innovation Solution
A wearable electronic device equipped with a sensor module comprising a first sensor for pulse wave signals and a second sensor for acceleration signals, which correlates respiratory characteristics to accurately detect and differentiate between inhalation and exhalation phases in real-time, using a processor to match and estimate respiration phases based on these signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If physiological changes are not measured directly from the body part, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent uses an accelerometer as an intermediary sensor to indirectly measure respiration by detecting body movements caused by respiratory cycles. Instead of directly measuring physiological changes like PPG signals, the accelerometer captures acceleration patterns that correlate with inhalation and exhalation phases, thus reducing device complexity while maintaining measurement capability through a different physical quantity
Solution Approach 2:
The patent replaces optical/physiological measurement systems with a mechanical acceleration-based sensing system. By substituting direct physiological measurement (PPG) with mechanical movement detection (accelerometer), the device achieves simpler hardware architecture while capturing respiration information through body motion patterns associated with breathing
2Use of energy by moving object
If sampling bit rate is reduced, then energy consumption is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent extracts only the essential respiratory characteristics from the acceleration signal, such as peak detection and zero-crossing points, rather than processing the entire high-resolution signal. This selective extraction of key features maintains measurement precision for respiration phase detection while significantly reducing the computational energy required for signal processing
Solution Approach 2:
The patent applies partial processing to the acceleration signal by focusing only on critical portions that indicate respiration phases (inhalation/exhalation transitions). Instead of continuously processing all signal data at high bit rate, the system performs measurements on selected signal segments, reducing overall energy consumption while preserving essential respiratory information
3Reliability
If respiration phase detection accuracy is improved, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary matching between acceleration signal patterns and PPG signal characteristics during an initial calibration phase. By pre-establishing the relationship between mechanical movements and physiological respiration phases, the system creates a reference model that improves subsequent detection accuracy without requiring complex real-time processing, thus enhancing reliability while limiting complexity growth
Solution Approach 2:
The patent transforms the acceleration signal into respiratory phase information by changing the parameter representation - detecting peaks, valleys, and zero-crossings in the acceleration data that correspond to inhalation and exhalation phases. This parameter transformation simplifies the detection algorithm while improving phase identification accuracy, achieving better reliability through mathematical transformation rather than hardware complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables high-accuracy, real-time detection of respiration phases, facilitating effective breathing exercises and providing medical information for diagnosis, while also aiding in stress reduction and mental health management.
Implementation Method 1
a first sensor configured to sense a first signal including a pulse wave based on a respiration
Implementation Method 2
a second sensor configured to sense a second signal including a first pattern corresponding to the inhalation and a second pattern corresponding to the exhalation
Data Source
AI summary
A wearable electronic device according to an embodiment includes: a sensor module including a first sensor configured to sense a first signal including a pulse wave based on a respiration of a user corresponding to a first time, the respiration including an inhalation and an exhalation, and a second sensor configured to sense a second signal including a first pattern corresponding to the inhalation and a second pattern corresponding to the exhalation. The wearable electronic device includes a processor configured to: match a first respiratory characteristic of the first signal and a second respiratory characteristic of the second signal based on a correlation between the first signal and the second signal, and estimate a respiration phase of the user corresponding to the second signal measured at a second time after the first time, based on the matched first and second respiratory characteristics.