Bio-impedance Sensor Signal Separation for Respiration Monitoring
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Solution Overview
Problem
Conventional methods for monitoring heart failure and disordered breathing using bio-impedance face limitations, particularly in accurately separating cardiac stroke components from respiratory signals, leading to erroneous diagnostic measures due to unstable heart rates and overlapping heart and respiratory rates.
Innovation Solution
Implementing an implantable medical device with multiple electrodes and a processor that uses signal separation techniques such as adaptive noise cancellation and blind source separation to isolate cardiac and respiratory signals, enhancing the signal-to-noise ratio and improving the accuracy of respiration sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional bio-impedance monitoring methods are used to measure respiratory signals, then the measurement can be obtained, but the accuracy is degraded due to overlapping cardiac stroke components and unstable heart rates
Solution Approach 1:
The patent applies segmentation by dividing the composite bio-impedance signal into separate cardiac and respiratory components through signal separation techniques. Multiple impedance signals are segmented from different electrode pairs, and algorithm-based separation methods partition these signals to isolate the respiratory component from cardiac interference, thereby improving measurement precision while maintaining reliability
Solution Approach 2:
The patent uses an intermediary approach by introducing signal processing algorithms as mediators between the raw bio-impedance signals and the final respiratory measurement. These algorithms act as intermediaries that process the overlapping signals, separate the cardiac stroke components, and extract the pure respiratory signal, resolving the contradiction between measurement accuracy and signal reliability
2Measurement precision
If signal separation techniques are implemented to separate cardiac and respiratory signals, then the signal-to-noise ratio is improved, but the device complexity increases
Solution Approach 1:
The patent applies universality by designing the implantable device to perform multiple functions: it not only monitors cardiac activity but also measures respiratory signals, separates signals using multiple algorithms, and provides comprehensive patient monitoring. This multi-functionality justifies the increased device complexity by delivering enhanced measurement precision and multiple therapeutic benefits
Solution Approach 2:
The patent uses copying by creating multiple copies of impedance measurement channels using different electrode pairs. These redundant measurement copies are then processed through signal separation algorithms to extract the respiratory signal. The copying approach improves signal-to-noise ratio through statistical processing while the complexity is managed by using algorithmic rather than hardware-based separation
3Measurement precision
If multiple impedance signals are collected and processed using algorithm-based separation, then the diagnostic accuracy is improved, but the processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by pre-processing the multiple impedance signals through filtering and normalization before applying the separation algorithms. This preliminary preparation reduces the computational complexity of the subsequent separation process, thereby reducing processing time while maintaining diagnostic accuracy. The device also performs preliminary signal quality assessment to determine when separation processing is necessary
Data Source
AI summary
Implantable medical devices and techniques are implemented that use bio-impedance to measure aspects of patient physiology. A signal separation method is performed at least in part in an implantable device. The method involves detecting a plurality of impedance signals using a plurality of implantable electrodes coupled to the implantable device. The method further involves separating one or more signals from the plurality of impedance signals using a signal separation technique, such as an algorithm-based separation technique.