Abstract
Traumatic brain injury (TBI) typically causes permanent brain tissue damage, which leads to permanent severe voiding dysfunction. Urinary retention is often refractory to standard therapies, and most patients require self-catheterization, which results in frequent urinary tract infections and reduces quality of life. Deep brain stimulation (DBS) might be a feasible alternative approach for treating bladder disorders in patients with TBI. In this study, we developed a DBS system with a closed-loop control strategy and determined the feasibility of this DBS system for improving bladder voiding function in a TBI animal model. A prototype of the DBS system was designed, fabricated and integrated with a closed-loop control algorithm based on the real-time external urethral sphincter-electromyogram feedback. A series of animal experiments was conducted to determine whether the feedback algorithm accurately detects the bladder status during cystometric measurements. Subsequent animal experiments were conducted to implement this DBS system and determine the performance of the closed-loop strategy for improving bladder functions in the TBI animal model. We successfully implemented a closed-loop algorithm for DBS control, and the accuracy of the bladder voiding phase detection was > 90%. Our system significantly improved the voiding efficiency in TBI rats from 22 to 74%. Although the prototype of the DBS feedback system was fabricated with surface-mounted device components and mounted on a 3D printed circuit board, the design principles and animal experience gathered from this research can serve as a basis for developing a new implantable bladder controller in the future.
Original language | English |
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Pages (from-to) | 337-349 |
Number of pages | 13 |
Journal | Journal of Medical and Biological Engineering |
Volume | 38 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jun 1 2018 |
Keywords
- Closed-loop
- Deep brain stimulation
- Electromyogram
- Traumatic brain injury
- Urinary retention
ASJC Scopus subject areas
- Biomedical Engineering