Energy-Efficient Waveforms for Selective Neuromodulation
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Solution Overview
Problem
Existing electrical neuromodulation devices for treating neurologic conditions, such as brain injury and stroke, face challenges in prolonging battery life, as they require frequent surgical replacement due to battery depletion, despite efforts to improve battery technology and optimize electrode materials and circuit configurations.
Innovation Solution
The use of energy-efficient waveforms, such as exponential decreasing or increasing waveforms, for selective neural activation, which reduce energy consumption and allow for more precise control over neural tissue activation, enabling longer-term neuromodulation without the need for frequent battery replacements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional rectangular waveforms are used for neural stimulation, then neural tissue activation is achieved, but energy consumption is high leading to frequent battery replacement
Solution Approach 1:
The patent applies parameter changes by transitioning from conventional rectangular waveforms to exponentially decaying waveforms for neural stimulation. This waveform modification changes the temporal distribution of current delivery, concentrating the stimulating effect at the onset while reducing overall charge injection. The exponential decay parameter (time constant) is optimized to maintain neural activation efficacy while minimizing total energy consumption, thereby extending battery life without compromising therapeutic effect
2Reliability
If higher amplitude pulses are used to ensure reliable neural activation, then neural tissue activation is more reliable, but energy consumption increases
Solution Approach 1:
The exponential waveform delivers the majority of its stimulating effect at the beginning of the pulse (preliminary action), with the current amplitude highest at onset and then decaying. This preliminary concentration of stimulatory effect achieves reliable neural activation at the start of the pulse, while the subsequent decay phase contributes minimally to energy consumption. The time constant is selected to ensure sufficient initial amplitude for reliable activation while allowing rapid decay to conserve energy
3Volume of moving object
If longer pulse widths are used to activate deeper neural tissue, then activation depth is increased, but charge injection and energy consumption increase
Solution Approach 1:
The patent utilizes parameter changes in the waveform time constant to achieve deeper neural activation without proportionally increasing charge injection. By optimizing the exponential decay time constant, the waveform maintains sufficient duration to activate deeper tissue while the decaying nature of the waveform ensures that extended duration does not linearly increase total charge. The shape parameter allows decoupling of activation depth from charge consumption that would occur with rectangular waveforms
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
These energy-efficient waveforms provide effective neuromodulation that is at least as effective as conventional rectangular waveforms, while conserving battery power, potentially extending device operation to over 7 years and offering finer control over neural activation, reducing charge injection, and allowing for smaller electrode designs.
Implementation Method 1
An electrical signal is applied to a site in the nervous system of the subject, wherein the electrical signal comprises pulses having the energy-efficient waveform
Data Source
AI summary
Methods of selective neuromodulation in a live mammalian subject, such as a human patient. The method comprises applying an electrical signal to a target site in the nervous system, such as the brain, where the electrical signal comprises a series of pulses. The pulses includes a waveform shape that is more energy-efficient as compared to a corresponding rectangular waveform. Non-limiting examples of such energy-efficient waveforms include linear increasing, linear decreasing, exponential increasing, exponential decreasing, and Gaussian waveforms. The parameters for the energy-efficient waveform are chosen to selectively activate neural tissue on the basis of axonal diameter.