Peripheral Nerve Field Stimulation Control via Physiological Feedback
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Solution Overview
Problem
Current medical devices for pain management, such as those using neurostimulation and therapeutic agents, often rely on fixed stimulation protocols that do not adapt to individual patient responses, leading to inefficiencies and potential discomfort due to lack of real-time feedback on physiological effects.
Innovation Solution
The development of a system that uses implanted electrodes to deliver peripheral nerve field stimulation (PNFS) based on detected physiological responses, allowing for closed-loop control of therapy delivery by monitoring parameters like heart rate, muscle activity, and skin conductance to adjust stimulation in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed stimulation protocols are used for pain management, then device complexity is reduced and ease of operation is improved, but adaptability to individual patient responses deteriorates and therapy effectiveness is reduced
Solution Approach 1:
The patent implements closed-loop control by detecting physiological responses (such as muscle activity via EMG, skin conductance, or heart rate) and using this feedback to automatically adjust stimulation parameters. The IMD continuously monitors patient responses and modifies stimulation intensity, frequency, or pulse width in real-time to optimize pain relief while adapting to individual variations in patient response.
2Adaptability or versatility
If real-time physiological monitoring is implemented for closed-loop control, then adaptability and therapy effectiveness are improved, but device complexity and measurement difficulty increase
Solution Approach 1:
The patent employs electrodes that serve dual functions: delivering electrical stimulation therapy and detecting physiological responses. The same electrodes used for PNS can detect local field potentials, muscle activity, or other physiological signals, eliminating the need for separate sensing components and reducing overall device complexity while enabling closed-loop control.
Solution Approach 2:
The system uses the patient's own physiological signals to automatically control the stimulation parameters without requiring external intervention or complex external monitoring equipment. The IMD self-regulates by detecting its own effects on the patient's physiology and adjusting accordingly.
3Reliability
If stimulation intensity is increased to improve pain relief, then therapy effectiveness is improved, but harmful effects such as muscle contractions and discomfort increase
Solution Approach 1:
The patent uses real-time detection of physiological responses (such as muscle contractions via EMG or skin conductance changes) as feedback signals to automatically adjust stimulation intensity. When harmful effects are detected, the system reduces stimulation parameters to prevent discomfort while maintaining effective pain relief through optimized parameter selection.
Solution Approach 2:
The patent dynamically adjusts stimulation parameters based on real-time patient response rather than using fixed intensity levels. The system can vary pulse width, frequency, and amplitude in real-time to maximize therapeutic effect while minimizing harmful side effects, adapting the stimulation profile to the patient's instantaneous physiological state.
Data Source
AI summary
Peripheral nerve field stimulation (PNFS) may be controlled based on detected physiological effects of the PNFS, which may be an efferent response to the PNFS. In some examples, a closed-loop therapy system may include a sensing module that senses a physiological parameter of the patient, which may be indicative of the patient's response to the PNFS. Based on a signal generated by the sensing module, the PNFS may be activated, deactivated or modified. Example physiological parameters of the patient include heart rate, respiratory rate, electrodermal activity, muscle activity, blood flow rate, sweat gland activity, pilomotor reflex, or thermal activity of the patient's body. In some examples, a patient pain state may be detected based on a signal generated by the sensing module, and therapy may be controlled based on the detection of the pain state.