Biomedical Circuits and Systems Dedicated for Sensing and Neurostimulation: Case study on Urinary Bladder dysfunctions
Bibliographic record
Abstract
This paper covers circuits and systems techniques for the construction of high reliability biosensing and neurostimulation smart medical devices. Such microsystems are dedicated for interconnections through the peripheral neural systems. Case study related to applications such as bladder control is discussed. Available electrical neurostimulation techniques for the rehabilitation of urinary bladder functions do not allow an adequate voiding due to dyssynergia between the bladder and the sphincter. A new implantable stimulator, built with commercially available electronic components, was designed to overcome these difficulties. The proposed system performs two types of stimulations: Selective Stimulation for bladder voiding and Permanent Stimulation to reduce the bladder overactivity symptoms. Also, a fully integrated extended version of the stimulator is achieved with the additional ability to monitor the electrodes-nerve contact impedance variations in order to detect electrodes faults or nerve physiology changes. The implemented full custom device provides a reliable stimulation technique and addresses the lack of features (programmable parameters, user-friendly interface and waveform flexibility) of the previous stimulation devices. Experimental results of the fabricated chip confirm its functionality. The microstimulator generates a wide range of stimuli waveforms with variable parameters and its modular architecture makes it an expandable multichannel stimulation system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".