As a resubmission, the proposed five-year plan will train me and foster my launch into an independent interdisciplinary research career. My multidisciplinary background in Biomedical Engineering, Electrical Engineering and Mechanical Engineering fields and my outstanding experience in advanced biomechanical modeling and electrophysiological modeling research have fostered my interest and given me unique advantages in conducting interdisciplinary biomedical research in Urinary Incontinence (UI). The immediate goal is to prepare for a career as an independent scientist and to develop a novel subject-specific electromechanical pelvic model based urethrovaginal support and urethral function assessment (UUFA) technique to minimally invasively and quantitatively assess these two etiologic factors and to investigate the specific changes associated with aging effects that cause the increase in prevalence of SUI in women. The central hypothesis behind this research is that urethrovaginal support and urethral function in women and aging effects on female SUI can be minimally invasively and quantitatively assessed and characterized using a subject-specific pelvic modeling approach. Primary Hypothesis #1 is that urethral function in women can be minimally invasively and quantitatively assessed using a subject-specific electrophysiological pelvic modeling approach. Primary Hypothesis #2 is that urethrovaginal support function in women can be non-invasively and quantitatively assessed using a subject-specific biomechanical pelvic modeling approach. Primary Hypothesis #3 is that aging will cause poor urethrovaginal support and/or urethral dysfunction which will lead to SUI. Primary Hypothesis #4 is that a female continence profile can be created to predict the status of continence in women in women clinically and to suggest optimal therapeutic modalities for specific patients. We propose four Specific Aims (SA) to test these Hypotheses: SA #1: To develop a subject- specific electrophysiological pelvic model based periurethral muscle fatigue assessment (UMFA) technique to minimally invasively and quantitatively assess urethral function in women. Primary Hypothesis #1 will be tested. SA #2: To develop a subject-specific biomechanical pelvic model based urethrovaginal support function assessment (USFA) technique to non-invasively and quantitatively assess urethrovaginal support function in women. Primary Hypothesis #2 will be tested. SA #3: To investigate aging effects on urethral function and urethrovaginal support in young/elderly female subjects with/without SUI using the UUFA technique which consists of the UMFA and USFA techniques. Primary Hypothesis #3 will be tested. SA #4: To develop a female SUI profile as a clinical standard of female SUI by utilizing the UUFA technique to quantitatively characterize SUI etiologic factors in urethrovaginal support and urethral function in women. Primary Hypothesis #4 will be tested. At the completion of this project, it is our expectation that we will have established and validated the UUFA technique and the feasibility of its application in clinical studies, and have achieved a better understanding of the contributions of specific changes associated with aging and menopause to these etiologic factors in women.
In this research proposal an urethrovaginal support and urethral function assessment (UUFA) technique will be developed based on an advanced electromechanical pelvis modeling approach. The primary impact of this research would lead to a minimally invasive technique to quantitatively assess urethrovaginal support and urethra function in women which are common etiologic factors associated with stress urinary incontinence (SUI). The UUFA technique will further help us characterize the specific changes associated with aging that cause the increase in prevalence of SUI in women.
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|Peng, Yun; Zhang, Yingchun (2017) Improving the repeatability of Motor Unit Number Index (MUNIX) by introducing additional epochs at low contraction levels. Clin Neurophysiol 128:1158-1165
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|Peng, Yun; He, Jinbao; Yao, Bo et al. (2016) Motor unit number estimation based on high-density surface electromyography decomposition. Clin Neurophysiol 127:3059-3065
|Liu, Yang; Ning, Yong; Li, Sheng et al. (2015) Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings. Int J Neural Syst 25:1550024
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