Respiration Pacing System with Adaptive Sensor Sampling
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Solution Overview
Problem
Existing respiration implant systems for treating impaired breathing, such as those caused by recurrent laryngeal nerve injuries, often fail to synchronize pacing with the patient's natural breathing cycle effectively, leading to reduced benefits and requiring manual frequency adjustments, which can result in phase mismatches and inefficient energy use.
Innovation Solution
A respiration pacing system that uses a pacing processor to generate a synchronized pacing signal based on detected respiration and movement signals, employing multiple power management modes to optimize energy consumption, including active, reduced, and prolonged inactive modes, using sensors like three-axis accelerometers and electromyographic sensors to deliver stimulation pulses to neural tissues like the posterior cricoarytenoid muscle or hypoglossal nerve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous respiration signal measurement is used to ensure accurate breathing cycle detection, then synchronization accuracy is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts the respiration sensor measurement mode based on movement sensor data. When movement is detected, continuous measurement is performed for accurate breathing cycle detection. When no movement is detected, measurement is reduced to periodic sampling, thereby saving energy while maintaining detection accuracy when needed.
Solution Approach 2:
The movement sensor automatically triggers changes in respiration sensor measurement behavior. The system uses the movement signal to determine when continuous monitoring is necessary versus when reduced measurement is acceptable, enabling autonomous energy management without external intervention.
2Adaptability or versatility
If manual frequency switching is implemented to adapt to different physical activities, then adaptability is improved, but system complexity and user burden increase
Solution Approach 1:
The system continuously monitors movement sensor signals and automatically adjusts pacing frequency based on detected physical activity levels. The movement signal serves as feedback that triggers automatic frequency changes, eliminating the need for manual user intervention while maintaining adaptability to different physical conditions.
Solution Approach 2:
The respiration pacing system automatically adapts to changing physical demands by processing movement sensor data and adjusting pacing parameters autonomously. The system serves itself by using its own sensor data to make real-time adjustments without requiring external user input or complex manual controls.
3Reliability
If phase-synchronization between pacemaker and natural breathing is implemented, then treatment effectiveness is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary detection of the breathing cycle phase using movement sensor data before delivering pacing stimulation. By identifying the inspiratory phase onset in advance through movement patterns, the system can time stimulation to achieve phase-synchronization, improving treatment effectiveness while using relatively simple control logic.
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
The system provides improved synchronization with the patient's breathing cycle, optimizing energy use and extending battery life by reducing unnecessary sensor measurements during periods of reduced activity, thereby enhancing the effectiveness of breathing assistance and reducing the risk of asphyxia.
Implementation Method 1
A movement sensor, such as a three-axis accelerometer, is located within the housing of the pacing processor
Implementation Method 2
Electromyogram (EMG) measurements also are under investigation for use in developing a stimulation trigger signal
Data Source
AI summary
A method of developing a respiration pacing signal includes detecting respiration and movement activity in an implanted patient and developing corresponding respiration and movement signals. A respiration pacing signal is synchronized with the detected respiration activity and delivered to respiration neural tissue of the implanted patient to promote breathing of the implanted patient. A plurality of respiration sensing modes are used that reflect activity of the movement signal over time to optimize system power consumption over time, including: i. an active respiration mode when the movement signal is either actively changing or remains unchanged for a brief period less than some reduced activity period, wherein the respiration signal is measured continuously, and ii. a plurality of reduced activity respiration modes when the movement signal has remained unchanged for the reduced activity period, wherein the respiration signal is measured only during a limited respiration sampling period.