For end-stage renal disease patients undergoing hemodialysis, thrombosis caused by stenosis hinders the long-term use of vascular access. However, traditional spectral bruit analysis techniques for detecting the severity of vascular access stenosis are not robust. Accordingly, the present study proposes an automated method for mimicking a trained practitioner in performing the auscultation process. In the proposed approach, the bruit obtained using a standard phonoangiographic method is transformed into the time-frequency domain, and two spectro-temporal features, namely the auditory spectrum flux and the auditory spectral centroid, are then extracted. The distributions of the two features are analyzed using a multivariate Gaussian distribution (MGD) model. Finally, the distribution parameters of the MGD model are used to detect the presence (or otherwise) of vascular access stenosis. The validity of the proposed approach is investigated using the phonoangiography signals obtained from 16 hemodialysis patients with straight arteriovenous grafts over the upper arm region. The results show that the MGD covariance matrix coefficient of the auditory spectral centroid feature yields an accuracy of 83.87 % in detecting significant vascular access stenosis. Thus, the proposed method has significant potential for the applications of vascular access stenosis detection.

A stimulus driver circuit for a micro-stimulator used in an implantable device is presented in this paper. For epileptic seizure control, the target of the driver was to output 30 µA stimulus currents when the electrode impedance varied between 20 and 200 kΩ. The driver, which consisted of the output stage, control block and adaptor, was integrated in a single chip. The averaged power consumption of the stimulus driver was 0.24-0.56 mW at 800 Hz stimulation rate. Fabricated in a 0.35 µm 3.3 V/24 V CMOS process and applied to a closed-loop epileptic seizure monitoring and controlling system, the proposed design has been successfully verified in the experimental results of Long-Evans rats with epileptic seizures.