IEEE Trans Neural Syst Rehabil Eng. 2019 Jun;27(6):1209-1216. doi: 10.1109/TNSRE.2019.2912374. Epub 2019 Apr 22.
Overactive bladder (OAB) patients suffer from a frequent urge to urinate, which can lead to a poor quality of life. Current neurostimulation therapy uses open-loop electrical stimulation to alleviate symptoms. Continuous stimulation facilitates habituation of neural pathways and consumes battery power. Sensory feedback-based closed-loop stimulation may offer greater clinical benefit by driving bladder relaxation only when bladder contractions are detected, leading to increased bladder capacity. Effective delivery of such sensory feedback, particularly in real-time, is necessary to accomplish this goal. We implemented a Kalman filter-based model to estimate bladder pressure in real-time using unsorted neural recordings from sacral-level dorsal root ganglia, achieving a 0.88 ± 0.16 correlation coefficient fit across 35 normal and simulated OAB bladder fills in five experiments. We also demonstrated closed-loop neuromodulation using the estimated pressure to trigger pudendal nerve stimulation, which increased bladder capacity by 40% in two trials. An offline analysis indicated that unsorted neural signals had a similar stability over time as compared to sorted single units, which would require a higher computational load. We believe this paper demonstrates the utility of decoding bladder pressure from neural activity for closed-loop control; however, real-time validation during behavioral studies is necessary prior to clinical translation.
膀胱过度活动症（OAB）患者经常感到尿急，这会导致生活质量下降。目前的神经刺激疗法采用开环电刺激来缓解症状。持续刺激促进了神经通路的习惯化，并消耗电池电量。基于感觉反馈的闭环刺激可能会提供更大的临床益处，因为只有在检测到膀胱收缩时才会驱动膀胱放松，从而增加膀胱容量。为了实现这一目标，需要有效地提供这种感觉反馈，特别是实时反馈。我们实现了一种基于卡尔曼滤波器的模型，该模型使用骶神经根节的未排序神经记录实时估计膀胱压力，在五个实验中对 35 个正常和模拟的 OAB 膀胱充盈进行了拟合，相关系数为 0.88±0.16。我们还展示了使用估计压力触发阴部神经刺激的闭环神经调节，在两次试验中使膀胱容量增加了 40%。离线分析表明，与排序的单个单元相比，未排序的神经信号在时间上具有相似的稳定性，这将需要更高的计算负载。我们认为本文证明了从神经活动解码膀胱压力用于闭环控制的实用性；然而，在进行临床转化之前，有必要在行为研究中进行实时验证。
