Closed-Loop Peripheral Nerve Stimulation for the Restoration of Normal Pain Processing

Neuropathic chronic pain, caused by nerve injury, is common and debilitating. Pharmaceuticals, the primary treatment, often lead to severe side effects. Electrical stimulation is a promising alternative with fewer side effects, but its efficacy is limited. Most clinical neuromodulation methods are open-loop, with settings adjusted during office visits, leading to reduced effectiveness over time. Proposed closed-loop strategies typically activate when a pain signal crosses a threshold, acting like an anesthetic by removing all pain. However, since acute pain has a protective role, the ideal therapy should target chronic pain while preserving acute pain responses. We present a proof-of-concept for a model-based closed-loop neuromodulation therapy aimed at normalizing pain responses in neuropathic rats. By measuring evoked pain responses from thalamic local field potentials in nerve-injured and naïve rats, we estimate transfer functions for both groups. We then use a model matching approach to quantify the difference between the nerve-injured and ideal (naïve) system responses as the error signal. Finally, we design an optimal controller using H-infinity methods to minimize this error and control input within relevant frequency bands. The resulting in-silico experiment provides a foundation for a more biologically realistic controller design which can be implemented in-vivo.