Data-driven models of pelvic floor muscles dynamics subject to psychological and physiological stimuli

• Published in: IFAC Journal of Systems and Control Vol. 8; p. 100044
• Main Authors: Knorn, Steffi, Varagnolo, Damiano, Melles, Reinhilde, Dewitte, Marieke
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 30.06.2019
• Subjects: Black box; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling; Female sexual dysfunction; Nonlinear models; System identification; Female sexual dysfunction; Black box; Nonlinear models; System identification
• DOI: 10.1016/j.ifacsc.2019.100044
• ISSN: 2468-6018

This paper proposes individualized, dynamical and data-driven models to describe pelvic floor muscle responses in women undergoing vaginal dilation. Specifically, the models describe how the aggregated pressure exerted by the pelvic floor muscles of women change due to physiological and psychological stimuli. Specifically, women experienced inflation of a balloon at the vaginal introitus while watching different short movies such as with or without sexual content. The paper inspects the approximation capabilities of different model structures, such as Hammerstein–Wiener and NARX, for this specific application, and finds the specific model structures and orders that best describe the recorded measurement data. Moreover, the manuscript explores the trade-offs between individualization and averaging of models. More precisely it numerically assesses how models obtained by assuming that each individual has the same response can be used to simulate the responses of different patients. Although the current dataset is drawn from a sample of healthy volunteers, this paper is an initial step towards better understanding women’s responses to vaginal dilation and sexual/nonsexual videos and facilitating individualized medical vaginal dilation treatment.