Abstract
<jats:p>Background: Spinal cord injury (SCI) is frequently associated with orthostatic hypotension, defined by a sustained decrease in blood pressure upon assuming an upright posture due to impaired autonomic regulation. Cardiovascular spinal cord epidural stimulation (CV-scES) can regulate systolic blood pressure (SBP) in people with SCI, but stimulation paradigms are highly individualized. To make this treatment available to more patients, we developed an algorithm to tailor individualized CV-scES paradigms that closely mimic researcher-developed paradigms. Methods: We performed an offline analysis using datasets collected from eight individuals with SCI with epidural stimulators implanted over the lumbosacral spinal segments. During data collection, researchers modulated stimulation parameters with the goal of maintaining SBP between 110-120 mmHg. Each two-hour dataset included synchronized SBP and stimulation recordings. We ran optimization analyses offline to determine temporal requirements before modifying stimulation amplitude to mitigate out-of-range SBP. Results: The algorithm parameters that best matched researcher-selected stimulation changed relatively quickly during the first 12 min (one every ~40 sec), and more slowly thereafter (one every ~79 sec). Overall, algorithmic stimulation closely tracked researcher-controlled stimulation, with a mean correlation coefficient of 0.94. To evaluate online performance, we tested the algorithm in real time with a single participant. We found that a faster approach was needed to respond to changes in SBP caused by rapid, unpredictable events, such as postural changes. We implemented a sigmoid-based paradigm that determined the time to wait before changing stimulation as a function of the current SBP, with worse SBP values requiring faster responses. The new paradigm outperformed the original algorithm and researcher-controlled stimulation across measures of SBP stability, though recovery from a postural tilt maneuver remained slower than with researcher control. Conclusions: Our results indicate that algorithmic stimulation may minimize assistance required from researchers and participants, making CV-scES more feasible for clinical translation.</jats:p>