Feasibility study of intelligent autonomous determination of the bladder voiding need to treat bedwetting using ultrasound and smartphone ML techniques : Intelligent autonomous treatment of bedwetting.

Unsatisfactory cure rates for the treatment of nocturnal enuresis (NE), i.e. bed-wetting, have led to the need to explore alternative modalities. New treatment methods that focus on preventing enuretic episodes by means of a pre-void alerting system could improve outcomes for children with NE in man...

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Publicado en:Medical & Biological Engineering & Computing Vol. 57; no. 5; pp. 1079 - 1098
Autores principales: Kuru, Kaya, Ansell, Darren, Jones, Martin, De Goede, Christian, Leather, Peter
Formato: Journal Article
Publicado: Springer Nature May2019
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Feasibility study of intelligent autonomous determination of the bladder voiding need to treat bedwetting using ultrasound and smartphone ML techniques : Intelligent autonomous treatment of bedwetting.
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        au:
          Kuru, Kaya
          Ansell, Darren
          Jones, Martin
          De Goede, Christian
          Leather, Peter
        affil: School of Engineering, University of Central Lancashire, Fylde Rd, PR1 2HE, Preston, UK
      sug:
        subj:
          Enuresis Prevention and Control
          Ultrasonography Equipment and Supplies
          Bladder
          Ultrasonography Methods
          Male
          Child
          Algorithms
          Mobile Applications
          Linear Regression
          Enuresis
          Programming Languages
          Reproducibility of Results
          Pilot Studies
          Ferrans and Powers Quality of Life Index
          Child: 6-12 years
          Male
      ab: Unsatisfactory cure rates for the treatment of nocturnal enuresis (NE), i.e. bed-wetting, have led to the need to explore alternative modalities. New treatment methods that focus on preventing enuretic episodes by means of a pre-void alerting system could improve outcomes for children with NE in many aspects. No such technology exists currently to monitor the bladder to alarm before bed-wetting. The aim of this study is to carry out the feasibility of building, refining and evaluating a new, safe, comfortable and non-invasive wearable autonomous intelligent electronic device to monitor the bladder using a single-element low-powered low-frequency ultrasound with the help of Machine Learning techniques and to treat NE by warning the patient at the pre-void stage, enhancing quality of life for these children starting from the first use. The sensitivity and specificity values are 0.89 and 0.93 respectively for determining imminent voiding need. The results indicate that customised imminent voiding need based on the expansion of the bladder can be determined by applying a single-element transducer on a bladder in intermittent manner. The acquired results can be improved further with a comfortable non-invasive device by adding several more features to the current features employed in this pilot study. Graphical Abstract Ultrasound device design: echoed US pulses reflected from the bladder and related tissues around the bladder is detected. These pulses are analysed, and an alarm is triggered when needed to treat nocturnal enuresis.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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