Closed-loop therapy adjustment via patient parameter sensing
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Solution Overview
Problem
Patients receiving chronic therapy, such as spinal cord stimulation, often need to manually adjust therapy parameters based on changing conditions like activity or posture, which is time-consuming and burdensome.
Innovation Solution
A medical device that senses patient parameters and automatically adjusts therapy by associating detected values with pre-defined therapy information, allowing it to 'learn' and deliver therapy without manual input over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of therapy parameters is allowed, then therapy can be customized to patient needs, but patient burden and time consumption increase
Solution Approach 1:
The medical device automatically adjusts therapy parameters by detecting patient parameters (such as activity level, posture, or physiological signals) and selecting appropriate therapy programs without requiring manual patient input. The device serves itself by autonomously making therapy adjustments based on sensed patient conditions, thereby eliminating the burden of manual operation while maintaining therapy customization.
Solution Approach 2:
The system continuously monitors patient parameters through sensors and uses this feedback to automatically adjust therapy delivery. The detected patient parameter values are compared against stored thresholds or patterns, and therapy parameters are dynamically modified in response to changing patient conditions, enabling adaptive customization without manual intervention.
2Ease of operation
If automatic therapy adjustment is implemented, then patient burden is reduced, but device complexity increases
Solution Approach 1:
The device architecture is divided into distinct functional modules: a sensor module for detecting patient parameters, a processing module for comparing detected values against stored data and determining therapy adjustments, and a delivery module for executing therapy parameter changes. This segmentation allows each component to perform a specific function, managing overall system complexity through modular design.
Solution Approach 2:
The device pre-stores multiple therapy programs and corresponding patient parameter thresholds or reference data in memory before actual therapy delivery. When a patient parameter is detected, the system quickly matches it against the pre-stored information to determine the appropriate therapy adjustment, eliminating the need for complex real-time calculations and reducing processing complexity.
3Reliability
If therapy parameters are continuously adjusted, then therapy effectiveness is improved, but loss of time for adjustments increases
Solution Approach 1:
The system continuously monitors patient parameters and maintains continuous therapy delivery without interruption. The automatic adjustment mechanism ensures that therapy parameters are continuously optimized based on real-time patient condition detection, eliminating gaps or delays associated with manual adjustment processes and ensuring uninterrupted effective therapy.
Solution Approach 2:
The device pre-prepares multiple therapy programs with optimized parameters for different patient conditions. When a change in patient parameter is detected, the system can immediately switch to the pre-configured appropriate program, avoiding time-consuming manual parameter adjustments and ensuring rapid response to maintain therapy effectiveness.
Data Source
AI summary
Techniques for detecting a value of a sensed patient parameter, and automatically delivering therapy to a patient according to therapy information previously associated with the detected value, are described. In exemplary embodiments, a medical device receives a therapy adjustment from the patient. In response to the adjustment, the medical device associates a sensed value of a patient parameter with therapy information determined based on the adjustment. Whenever the parameter value is subsequently detected, the medical device delivers therapy according to the associated therapy information. In this manner, the medical device may “learn” to automatically adjust therapy in the manner desired by the patient as the sensed parameter of the patient changes. Exemplary patient parameters that may be sensed for performance of the described techniques include posture, activity, heart rate, electromyography (EMG), an electroencephalogram (EEG), an electrocardiogram (ECG), temperature, respiration rate, and pH.