Investigation on Energy Optimization of Neural Electrical Stimulation Based on Circuit Probability Theory

For the battery-powered implantable stimulators, the energy optimization of neural stimulation is critical for extending its lifetime. However, due to the nonlinearity and complexity of the relationship between the neural electrical stimulation and the neural response, optimizing the stimulation parameters to achieve desired neural response with minimal energy consumption is a challenge. The circuit-probability theory is a novel method to investigate the quantitative relationship between electrical stimulations and neural responses. Based on the circuit-probability theory, this paper proposed a method to investigate the energy optimization problem at different neural response strength. The results show that the pulse width of the optimal current waveform with minimal energy consumption is not a constant, but a value that increases with the neural stimulation strength. In the future, our study can be applied for the optimization of current pulses of implantable neural stimulators to prolong the lifetime and reduce the recharge intervals of batteries, thereby reducing the volume of implanted pulse generators and the costs and risks of battery-replacement surgeries.