Apple inc. (20240245329). SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY simplified abstract
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 20240245329 titled 'SYSTEM AND METHOD FOR ROBUST PULSE OXIMETRY
Simplified Explanation: The patent application discusses a method for robust estimation of a user's physiological signals by filtering or classifying samples at different wavelengths.
- The system estimates the characteristic using samples that meet specific criteria and filters out those that do not.
- Weighted samples are used for estimation based on the criteria, giving less or no weight to samples that fail to meet the criteria.
- Criteria may include factors related to the physiological signal at a third wavelength.
Key Features and Innovation:
- Robust estimation of physiological signals using filtering and classification of samples.
- Weighted estimation based on specific criteria to improve accuracy.
- Incorporation of multiple wavelengths for analysis.
Potential Applications:
- Healthcare monitoring and diagnostics.
- Fitness tracking devices.
- Stress management tools.
Problems Solved:
- Inaccurate estimation of physiological signals.
- Noise interference in signal processing.
- Lack of robustness in signal analysis.
Benefits:
- Improved accuracy in estimating physiological characteristics.
- Enhanced reliability of user data.
- Better performance in real-world conditions.
Commercial Applications: Potential commercial applications include:
- Medical device manufacturing.
- Wearable technology development.
- Biometric security systems.
Prior Art: Prior research in physiological signal processing and estimation methods can be found in academic journals and patents related to healthcare technology.
Frequently Updated Research: Ongoing research in signal processing algorithms, machine learning techniques, and wearable sensor technology may impact the development of this innovation.
Questions about Physiological Signal Estimation: 1. How does the weighted estimation method improve the accuracy of physiological signal estimation? 2. What are the criteria used to filter out samples in the estimation process?
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.
