Integrated programmable neurostimulator to recuperate the bladder functions
Bibliographic record
Abstract
Electrical neurostimulation has been used intensively to recuperate the bladder functions. Available techniques do not allow the adequate voiding due to the dyssynergia between the bladder and the sphincter. We proposed a new integrated stimulator designed to allow the recuperation of the bladder functions. The stimulation system, which is an integrated version of a previously proposed stimulator made by our research team, has been extended with some new functionalities. It performs flexible selective stimulations for bladder voiding, a continuous stimulation for suppression of the bladder hyperreflexia and includes a measurement technique to monitor the electrodes-nerve contact allowing the detection of any variation of the nerve impedance or breaking of the electrodes. The stimulation parameters (amplitude, width, frequency) are sent wirelessly by an external controller and are stored in a RAM. An on-chip calibration circuitry provides an efficient and reliable stimulation technique and a voltage regulator supplies the power for the digital core. The modular architecture of the design makes the device an expandable multichannel stimulation system. The stimulator has been designed in the CMOS 0.18 /spl mu/m technology and can supply up to 3 mA in a 1 k/spl Omega/ resistive load. It is a complete and efficient stimulation system using fully programmable parameters allowing the recuperation of the bladder functions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".