Heart Rate Monitor Noise Reduction via Step Rate Filtering
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Solution Overview
Problem
Existing personal health monitors, particularly those using photoplethysmograph (PPG) sensors, face accuracy issues due to noise interference from motion, such as step rate, which can corrupt heart rate measurements, leading to latency problems in processing and decision-making.
Innovation Solution
The solution involves using filtering techniques to remove the step rate component from heart rate measurements by computing a difference between the step rate and heart rate, and then filtering the heart rate based on this difference, thereby reducing noise and processing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral transform operation uses a 6 s window to process heart rate data, then measurement precision is improved, but loss of time increases due to 3 s average latency
Solution Approach 1:
The system performs preliminary spectral transform on the PPG signal to identify step rate components before they interfere with heart rate measurement. By pre-processing the signal and detecting motion artifacts in advance, the system can compensate for the latency inherent in spectral analysis while maintaining measurement accuracy.
Solution Approach 2:
The system uses feedback from the accelerometer to continuously monitor and adjust the heart rate measurement. When step rate is detected through spectral analysis of acceleration data, the system feedback-corrects the PPG-derived heart rate by subtracting the step rate component, thereby maintaining precision despite the time delay introduced by spectral transform.
2Measurement precision
If post-transform operations are implemented to achieve desired accuracy, then measurement precision is improved, but loss of time increases due to additional processing latency
Solution Approach 1:
The system extracts and removes the step rate component from the PPG signal by using spectral analysis of accelerometer data to identify and subtract the motion artifact. This extraction approach isolates the true heart rate signal from the corrupted measurement, achieving high accuracy without requiring extensive post-processing operations.
Solution Approach 2:
The accelerometer serves as an intermediary device that provides motion information to correct the PPG heart rate measurement. Instead of directly processing the corrupted PPG signal through multiple transformation stages, the system uses the accelerometer as an intermediate source to identify step rate and then corrects the PPG data, reducing overall processing time while maintaining precision.
3Ease of operation
If PPG sensors are used in ear bud for portable monitoring, then ease of operation is improved, but measurement precision deteriorates due to sensitivity to motion noise
Solution Approach 1:
The system merges the PPG sensor and accelerometer into a single ear bud device, combining the advantages of both technologies. The PPG provides continuous physiological monitoring while the accelerometer provides motion reference data, and their combined output is processed together to eliminate motion artifacts from the heart rate measurement.
Solution Approach 2:
The accelerometer acts as an intermediary that provides motion information to correct the PPG signal. By using the accelerometer data as a reference for step rate detection, the system can compensate for the motion noise that inherently affects PPG measurements in portable ear bud devices.
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
This approach provides accurate heart rate measurements with reduced latency by processing only current spectrally transformed data, eliminating the post-transform latency issues of prior art methods.
Implementation Method 1
PPG sensors measure the relative blood flow using an infrared or other light source that projects light that is ultimately transmitted through or reflected off tissue, and is subsequently detected by a photodetector and quantified
Implementation Method 2
an inertial sensor, an inertial processor, a physiological sensor, a physiological processor, and a noise processor. The inertial processor computes an inertial cadence of a user based on an inertial waveform provided by the inertial sensor
Data Source
AI summary
The heart rate monitor disclosed herein removes a step rate component from a measured heart rate by using one or more filtering techniques when the step rate is close to the heart rate. In general, a difference between the step rate and the heart rate is determined, and the step rate is filtered from the heart rate based on a function of the difference.