Advanced Platform Technology Center, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA.
Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, USA.
Proc Inst Mech Eng H. 2024 Jun;238(6):619-627. doi: 10.1177/09544119231172272. Epub 2023 May 2.
Individuals with spinal cord injury (SCI) usually develop neurogenic detrusor overactivity (NDO), resulting in bladder urgency and incontinence, and reduced quality of life. Electrical stimulation of the genital nerves (GNS) can inhibit uncontrolled bladder contractions in individuals with SCI. An automated closed-loop bladder neuromodulation system currently does not exist but could improve this approach. We have developed a custom algorithm to identify bladder contractions and trigger stimulation from bladder pressure data without need for abdominal pressure measurement. The goal of this pilot study was to test the feasibility of automated closed-loop GNS using our custom algorithm to identify and inhibit reflex bladder contractions in real time. Experiments were conducted in a single session in a urodynamics laboratory in four individuals with SCI and NDO. Each participant completed standard cystometrograms without and with GNS. Our custom algorithm monitored bladder vesical pressure and controlled when GNS was turned on and off. The custom algorithm detected bladder contractions in real time, successfully inhibiting a total of 56 contractions across all four subjects. There were eight false positives, six of those occurring in one subject. It took approximately 4.0 ± 2.6 s for the algorithm to detect the onset of a bladder contraction and trigger stimulation. The algorithm maintained stimulation for approximately 3.5 ± 1.7 s, which was enough to inhibit activity and relieve feelings of urgency. Automated closed-loop stimulation was well-tolerated and subjects reported that algorithm decisions generally matched with their perceptions of bladder activity. The custom algorithm automatically, successfully identified bladder contractions to trigger stimulation to inhibit bladder contractions acutely. Closed-loop neuromodulation using our custom algorithm is feasible, but further testing is needed refine this approach for use in a home environment.
脊髓损伤(SCI)患者通常会出现神经源性逼尿肌过度活动(NDO),导致膀胱紧迫感和失禁,并降低生活质量。生殖器神经(GNS)电刺激可以抑制 SCI 患者不受控制的膀胱收缩。目前不存在自动化闭环膀胱神经调节系统,但可以改善这种方法。我们开发了一种定制算法,可以根据膀胱压力数据识别膀胱收缩并触发刺激,而无需进行腹部压力测量。该初步研究的目的是测试使用我们的定制算法实时识别和抑制反射性膀胱收缩的自动化闭环 GNS 的可行性。该实验在 4 名 SCI 和 NDO 患者的一个泌尿科实验室中进行了单次会议。每位参与者都完成了没有和有 GNS 的标准膀胱测压图。我们的定制算法监测膀胱膀胱压力,并控制 GNS 的开启和关闭。定制算法实时检测到膀胱收缩,成功地总共抑制了所有四个研究对象的 56 次收缩。有 8 次假阳性,其中 6 次发生在一个研究对象中。算法检测到膀胱收缩的起始并触发刺激大约需要 4.0±2.6 秒。算法维持刺激约 3.5±1.7 秒,足以抑制活动并减轻紧迫感。自动化闭环刺激被很好地耐受,研究对象报告说算法决策通常与他们对膀胱活动的感知相匹配。定制算法可以自动、成功地识别膀胱收缩,从而触发刺激以抑制膀胱收缩。使用我们的定制算法进行闭环神经调节是可行的,但需要进一步的测试来改进这种方法,以便在家庭环境中使用。