NCT05803512

Predicting Female Pelvic Tilt and Lumbar Angle Using Machine Learning in Case of Urinary Incontinence and Sexual Dysfunction

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 92 (actual)
• Sponsor: Deraya University · Academic / Other
• Sex: Female
• Age: 30 Years – 40 Years
• Healthy volunteers: —

Summary

The purpose of this study is to Predicting female pelvic tilt and lumbar angle using machine learning in case of urinary incontinence and sexual dysfunction

Detailed description

92 patients were distributed randomly into two groups. The first group will be measured pelvic tilt, lumbar angle by spinal mouse and force of contraction of pelvic floor muscles by ultrasound imaging, UDI-6 and FSFI questionnaires for urinary incontinence female The second group will be measured pelvic tilt, lumbar angle by spinal mouse device and force of contraction of pelvic floor muscles by ultrasound imaging, UDI-6 and FSFI questionnaires for normal females. Patients will be examined by radiologist with medical ultrasound imaging and by me with spinal mouse device.

Conditions

• The Purpose of This Study is to Predicting Female Pelvic Tilt and Lumbar Angle Using Machine Learning in Case of Urinary Incontinence and Sexual Dysfunction

Timeline

• Start date: 2023-02-01
• Primary completion: 2023-04-01
• Completion: 2023-04-15
• First posted: 2023-04-07
• Last updated: 2023-09-26

Locations

1 site across 1 country: Egypt