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In this paper, we propose a new approach to the analysis and modeling of esophageal manometry (EGM) data to assist the diagnosis of esophageal motility disorders in humans. The proposed approach combines three techniques, namely, wavelet decomposition (WD), nonlinear pulse detection technique (NPDT), and statistical pulse modeling. Specifically, WD is applied to the filtering of the EGM data, which...
Wavelet decomposition is gaining attention as a novel signal processing tool for analyzing nonlinear time-series. Compared to traditional Fourier transform, wavelet transform better represents functions exhibiting discontinuities and sudden changes. As such, wavelet-based techniques are strong candidates for the analysis of bio-signals (e.g. gastric and esophageal signals), in which, sudden changes...
This keynote address covers methods employed to design highly reliable microsystems intended to build smart medical devices such as sensors and microstimulators. Advanced circuit techniques are used to make low-power low-voltage high reliability interfaces dedicated to wirelessly power up and bidirectional exchange various types of data with implantable devices. Special attention is paid to power...
This paper concerns the design and implementation of a new implantable Neuro-Monito-Stimulation System (NMSS) for the urinary tract rehabilitation in paraplegics. In addition to selective stimulation for voluntary micturition and permanent stimulation for reduction of the detrusor overactivity, the NMSS includes telemetry capabilities of electrodes-tissues contact. Resistance up to 10 kOmega could...
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