18590444. SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY simplified abstract (Apple Inc.)
Contents
SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY
Organization Name
Inventor(s)
Saeed Mohammadi of Sunnyvale CA (US)
Albert E. Cerussi of San Jose CA (US)
Paul D. Mannheimer of Los Altos CA (US)
SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY - A simplified explanation of the abstract
This abstract first appeared for US patent application 18590444 titled 'SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY
Simplified Explanation: The patent application describes a method for robust estimation of a user's physiological signals by filtering or classifying samples at different wavelengths.
Key Features and Innovation:
- Robust estimation of physiological signals by filtering out samples that do not meet certain criteria.
- Weighting samples based on criteria to improve estimation accuracy.
- Criteria include analyzing physiological signals at different wavelengths.
- Estimating characteristics of physiological signals using selected and weighted samples.
Potential Applications: This technology could be applied in healthcare for monitoring patient vital signs, in sports performance analysis, and in stress management tools.
Problems Solved: This technology addresses the challenge of accurately estimating physiological characteristics from noisy signal data.
Benefits:
- Improved accuracy in estimating physiological signals.
- Enhanced reliability in monitoring user health metrics.
- Potential for real-time feedback on user well-being.
Commercial Applications: Potential commercial applications include wearable health devices, fitness trackers, and medical monitoring equipment for hospitals and clinics.
Prior Art: Prior research in signal processing and physiological monitoring technologies may provide insights into similar methods for robust estimation of physiological signals.
Frequently Updated Research: Researchers are continually exploring new algorithms and techniques to enhance the accuracy and efficiency of physiological signal estimation methods.
Questions about Robust Estimation of Physiological Signals: 1. How does this technology compare to traditional methods of physiological signal estimation? 2. What are the specific criteria used to filter and weight samples in this method?
Original Abstract Submitted
Robust estimation of a characteristic of a user's physiological signals can be achieved by filtering or classifying samples. Rather than estimating the characteristic of the user's physiological signals based on each sample at a first wavelength and a second wavelength, a robust system and method can, in some examples, estimate the characteristic using samples at the first wavelength and the second wavelength that meet one or more criteria and filter out samples that fail to meet the one or more criteria. In some examples, the system and method can weight samples based on the one or more criteria, and estimate the characteristic using the weighted samples. Samples failing to meet the one or more criteria can be given less weight or no weight in the estimation. The one or more criteria can include a criterion based on at least the physiological signal at a third wavelength.
