ArticleAnnals of biomedical engineering2018
Evaluation of Decoding Algorithms for Estimating Bladder Pressure from Dorsal Root Ganglia Neural Recordings.
Article in Annals of biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 29 citations in OpenAlex.
- Chronic stable recording of physiologically evoked neural activity in a mixed autonomic nerve in awake, freely moving normal and experimental cystitis rats.APL bioengineering · 2026Article
- Distribution of bladder afferent activity across the sacral roots in sheep shows marked individual variation: implications for neuroprosthesis design.Frontiers in neuroscience · 2026Article
- Bioelectronic Therapeutics: A Revolutionary Medical Practice in Health Care.Bioelectricity · 2025Review
- Bioelectronic Medicines-A Novel Approach of Therapeutics in Current Epoch.Current pharmaceutical design · 2025Review
- Selective recording of physiologically evoked neural activity in a mixed autonomic nerve using a minimally invasive array.APL bioengineering · 2023Article
- Closed-loop sacral neuromodulation for bladder function using dorsal root ganglia sensory feedback in an anesthetized feline model.Medical & biological engineering & computing · 2022Article
- High-density neural recordings from feline sacral dorsal root ganglia with thin-film array.Journal of neural engineering · 2021Article
- Estimation of Bladder Pressure and Volume from the Neural Activity of Lumbosacral Dorsal Horn Using a Long-Short-Term-Memory-based Deep Neural Network.Scientific reports · 2019Article
- Ultracompliant Carbon Nanotube Direct Bladder Device.Advanced healthcare materials · 2019Article
- Real-Time Bladder Pressure Estimation for Closed-Loop Control in a Detrusor Overactivity Model.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019Article
- Behavioral Monitoring and Neuromodulation of Feline Voiding Function.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2019Article
- Recording single- and multi-unit neuronal action potentials from the surface of the dorsal root ganglion.Scientific reports · 2019Article
- Detecting Bladder Biomarkers for Closed-Loop Neuromodulation: A Technological Review.International neurourology journal · 2018Article
- Detection of Bladder Contractions From the Activity of the External Urethral Sphincter in Rats Using Sparse Regression.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Evaluation of Decoding Algorithms for Estimating Bladder Pressure from Dorsal Root Ganglia Neural Recordings.Annals of biomedical engineering · 2018Article
- Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience.Frontiers in neuroinformatics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
A closed-loop device for bladder control may offer greater clinical benefit compared to current open-loop stimulation devices. Previous studies have demonstrated the feasibility of using single-unit recordings from sacral-level dorsal root ganglia (DRG) for decoding bladder pressure. Automatic online sorting, to differentiate single units, can be computationally heavy and unreliable, in contrast to simple multi-unit thresholded activity. In this study, the feasibility of using DRG multi-unit recordings to decode bladder pressure was examined. A broad range of feature selection methods and three algorithms (multivariate linear regression, basic Kalman filter, and a nonlinear autoregressive moving average model) were used to create training models and provide validation fits to bladder pressure for data collected in seven anesthetized feline experiments. A non-linear autoregressive moving average (NARMA) model with regularization provided the most accurate bladder pressure estimate, based on normalized root-mean-squared error, NRMSE, (17 ± 7%). A basic Kalman filter yielded the highest similarity to the bladder pressure with an average correlation coefficient, CC, of 0.81 ± 0.13. The best algorithm set (based on NRMSE) was further evaluated on data obtained from a chronic feline experiment. Testing results yielded a NRMSE and CC of 10.7% and 0.61, respectively from a model that was trained on data recorded 2 weeks prior. From offline analysis, implementation of NARMA in a closed-loop scheme for detecting bladder contractions would provide a robust control signal. Ultimate integration of closed-loop algorithms in bladder neuroprostheses will require evaluations of parameter and signal stability over time.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.