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Wearable Devices for Continuous Monitoring of Bladder Function: A Review of Current Approaches and Future Perspectives

Gökhan ECER,Erkan ARSLAN

  • Gökhan ECER: KONYA BEYHEKİM EĞİTİM ARAŞTIRMA HASTANESİ
  • Erkan ARSLAN: Necmettin Erbakan Üniversitesi Tıp Fakültesi
  •  Year : 2026
  •  Vol : 6
  •  Issue : 1
  •  Page : 42-49
The integration of artificial intelligence (AI) and wearable technologies into healthcare has driven significant progress in patient monitoring, especially in diagnosing and managing urological disorders. These innovations allow continuous, non-invasive, and patient friendly monitoring of bladder functions. In conditions such as urinary incontinence, neurogenic bladder, benign prostatic hyperplasia, and bladder outlet obstruction, conventional methods lack continuous tracking capabilities and may reduce patient comfort. This review assesses artificial intelligence integrated wearable systems, focusing on their technical features, clinical potential , accuracy , advantages , and limitations. Currently, systems using ultrasound, microwave, electrical bioimpedance, capacitive sensors, near-infrared spectroscopy (NIRS), electromyography (EMG), and optical sensors are under development. Integrated with artificial intelligencealgorithms, these technologies can track bladder filling, voiding time, and functional capacity with high accuracy in real time. This study systematically reviewed research from the past decade and compared devices based on clinical efficiency, usability, safety, and market availability. Ultrasound based devices are the most developed and commercially available among all technologies. Microwave and bioimpedance methods, however, remain experimental and require further validation. The analytical strength of artificial intelligence enhances the integration of these systems into clinical decision-making and supports personalized treatment approaches. Nevertheless, further prospective and randomized clinical studies are essential, particularly in pediatric, geriatric, and special patient populations. Ultrasound systems appear closest to clinical use, while microwave and bioimpedance technologies still demand more validation. artificial intelligence's data processing capabilities improve integration into clinical workflows and enable tailored patient care. Still, broader trials in varied patient groups are needed for widespread clinical implementation.
Conflict of interest : The authors declare that they have no conflict of interest.

This article is published under the CC BY-NC 4.0 license.
Mevlana Tıp Bilimleri
2026, Vol6, Issue1
E-ISSN: 2757-976X
Received : , Accepted : , Published Online :

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