Model-based analysis of implanted hypoglossal nerve stimulation for the treatment of obstructive sleep apnea

Study Objectives: Individuals with obstructive sleep apnea (OSA), characterized by frequent sleep disruptions from tongue muscle relaxation and airway blockage, are known to benefit from on-demand electrical stimulation of the hypoglossal nerve. Hypoglossal nerve stimulation (HNS) therapy, which activates the protrusor muscles of the tongue during inspiration, has been established in multiple clinical studies as safe and effective, but the mechanistic understanding for why some stimulation parameters work better than others has not been thoroughly investigated. Methods: In this study, we developed a detailed biophysical model that can predict the spatial recruitment of hypoglossal nerve fascicles and axons within these fascicles during stimulation through nerve cuff electrodes. Using this model, three HNS programming scenarios were investigated including grouped cathode (---), single cathode (o-o), and guarded cathode bipolar (+-+) electrode configurations. Results: Regardless of electrode configuration, nearly all hypoglossal nerve axons circumscribed by the nerve cuff were recruited for stimulation amplitudes <3 V. Within this range, monopolar configurations required lower stimulation amplitudes than the guarded bipolar configuration to elicit action potentials within hypoglossal nerve axons. Further, the spatial distribution of the activated axons was more uniform for monopolar versus guarded bipolar configurations. Conclusions: The computational models predicted that monopolar HNS provided the lowest threshold and the least sensitivity to rotational angle of the nerve cuff around the hypoglossal nerve; however, this setting also increased the likelihood for current leakage outside the nerve cuff, which could potentially activate axons in unintended branches of the hypoglossal nerve.