Radar-Based Sleep Quality Evaluation via Waveform Feature Extraction
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Solution Overview
Problem
Current methods for detecting sleep quality are invasive, costly, and often require specialized equipment, making it difficult to detect sleep apnea and related respiratory events in a timely and non-invasive manner.
Innovation Solution
A computing apparatus and evaluation method that uses radar-based sensing data to transform radar echoes into feature data, which includes statistics of waveform features, allowing for the determination of sleep quality through non-touch sensing, leveraging machine learning models like Deep Neural Decision Trees to predict respiratory events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized equipment is used for sleep quality detection, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical sensing systems with electromagnetic wave-based radar sensing. The radar system uses electromagnetic waves to detect respiratory movements and heartbeats, eliminating the need for complex mechanical sensors, electrodes, and wires while maintaining measurement precision for sleep quality assessment
Solution Approach 2:
The patent creates a simplified copy of the polysomnography measurement capability using radar technology. Instead of replicating the full complexity of PSG equipment, the radar system captures essential physiological signals (respiratory rate, heartbeat) through electromagnetic wave reflection, providing comparable sleep quality information with much simpler hardware
2Measurement precision
If specialized equipment is used for sleep quality detection, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent employs commercially available, inexpensive radar modules that can be manufactured at low cost. These radar sensors are mass-producible consumer electronics components rather than specialized medical equipment, significantly reducing manufacturing costs while maintaining sufficient measurement precision for sleep quality detection
Solution Approach 2:
By substituting expensive mechanical sensing systems with electromagnetic wave-based radar, the patent eliminates costly components such as specialized sensors, amplifiers, and signal processing hardware, resulting in a much more cost-effective solution that maintains measurement accuracy
3Ease of operation
If non-contact sensing is used, then ease of operation is improved, but measurement precision may deteriorate
Solution Approach 1:
The radar system uses periodic transmission of electromagnetic waves at frequencies specifically tuned to detect human physiological movements. By transmitting continuous waves or pulsed signals at regular intervals, the system accumulates sufficient signal data to accurately measure respiratory rate and heartbeat even through non-contact sensing
Solution Approach 2:
The patent uses electromagnetic waves as an intermediary medium to bridge the gap between the sensor and the subject. The radar waves interact with the body's natural movements (respiration, heartbeat) and carry this information back to the sensor, enabling precise measurement without direct contact
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
Enables the non-invasive and efficient evaluation of sleep quality by predicting respiratory events, correlating with polysomnography results, providing a reliable indicator of sleep quality without the need for direct contact or expensive equipment.
Implementation Method 1
The sensing data is generated based on a radar echo
Implementation Method 2
The sensing data is generated based on a radar echo
Data Source
AI summary
An evaluation method of sleep quality and a computing apparatus related to sleep quality are provided. In the evaluation method, sensing data is obtained. The sensing data is generated based on a radar echo. The sensing data is transformed into feature data. The feature data includes a statistic of a plurality of feature points on a waveform of the radar echo. Sleep quality information is determined according to the feature data. Accordingly, sleep quality may be evaluated through non-touch sensing.