Closed-loop Therapy Adjustment via Sensor-Driven Parameter Association
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Solution Overview
Problem
Patients receiving chronic medical therapies, 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 inefficient.
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 optimal treatment without continuous patient input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If patients manually adjust therapy parameters based on changing conditions, then therapy can be customized to patient needs, but it is time-consuming and inefficient
Solution Approach 1:
The medical device automatically monitors patient parameters (activity, posture, physiological signals) and autonomously selects and applies appropriate therapy programs from stored options, eliminating the need for manual patient adjustment. The device serves itself by making therapy decisions based on real-time sensor data and pre-programmed treatment protocols.
Solution Approach 2:
Multiple therapy programs with different parameters are pre-programmed into the device before patient use. These programs are prepared in advance based on various possible patient conditions, allowing the device to quickly retrieve and apply the appropriate pre-configured therapy without requiring real-time manual setup or adjustment by the patient.
2Reliability
If therapy parameters are manually adjusted frequently, then therapy effectiveness is maintained, but patient burden and complexity increase
Solution Approach 1:
The device continuously monitors patient parameters through integrated sensors (activity sensors, posture detectors, physiological signal sensors) and uses this feedback to automatically determine when and how to adjust therapy. The system compares real-time sensor data against predetermined thresholds and conditions, triggering automatic therapy program selection to maintain effectiveness without patient intervention.
Solution Approach 2:
The medical device integrates multiple functions into a single system: it performs therapy delivery, patient parameter monitoring, automatic program selection, and adaptive adjustment all through one device. This multi-functionality eliminates the need for separate manual adjustment mechanisms and reduces overall system complexity while maintaining therapy reliability.
3Productivity
If automatic therapy adjustment is implemented, then efficiency is improved, but the device must learn and adapt to patient preferences over time
Solution Approach 1:
The device automatically monitors patient responses to therapy and learns optimal parameter settings through continuous operation. It autonomously tracks which therapy programs provide best results under different conditions and adapts its selection criteria accordingly, eliminating the need for manual programming or external intervention to optimize performance.
Solution Approach 2:
Multiple therapy programs with varying parameters are pre-programmed into the device with different characteristics for different patient conditions. This preliminary preparation of diverse therapy options enables the device to efficiently select and apply appropriate treatments as patient needs change, improving productivity while maintaining adaptability.
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.