Implantable CMOS neuro-stimulus chip for visual prosthesis

et al. 2015

Sci. China Inf. Sci.

Self Cite

This paper proposes a novel wavelet neural network algorithm for the continuous and noninvasive dynamic estimation of blood pressure (BP). Unlike prior algorithms, the proposed algorithm capitalizes on the correlation between photoplethysmography (PPG) and BP. Complete BP waveforms are reconstructed based on PPG signals to extract systolic blood pressure (SBP) and diastolic blood pressure (DBP). To improve the robustness, Daubechies wavelet is implemented as the hidden layer node function for the neural network. An optimized neural network structure is proposed to reduce the computational complexity. Further, this paper investigates an inhomogeneous resilient backpropagation (IRBP) algorithm to calculate the weight of hidden layer nodes. The IRBP improves the convergence speed and reconstruction accuracy. Multiparameter intelligent monitoring in Intensive Care (MIMIC) databases, which contain a variety of physiological parameters captured from patient monitors, are used to validate this algorithm. The standard deviation σ between reconstructed and actual BP signals is 4.4797 mmHg, which satisfies the American National Standards of the Association for the Advancement of Medical Instrumentation. The reconstructed BP waveform can be used to extract the SBP and DBP, whose standard deviations σ are 2.91 mmHg and 2.41 mmHg respectively.Keywords photoplethysmogram (PPG), blood pressure (BP), Daubechies wavelet, neural network, inhomogeneous resilient backpropagation (IRBP) CitationLi P, Liu M, Zhang X, et al. Novel wavelet neural network algorithm for continuous and noninvasive dynamic estimation of blood pressure from photoplethysmography.

Section: Introductionmentioning

confidence: 99%

Novel wavelet neural network algorithm for continuous and noninvasive dynamic estimation of blood pressure from photoplethysmography

et al. 2015

Sci. China Inf. Sci.

Self Cite

“…Polymerized siloxanes shell is also used to encapsulate this system according to the biocompatible and hermetic consideration. Recording and stimulation electrodes are integrated in the system, as the polyimide thin-film could also be the substrate of flexible belt electrode [31]. The indifferent electrode in Fig.…”

Section: Stimulation Modulementioning

confidence: 99%

An Implantable Sacral Nerve Root Recording and Stimulation System for Micturition Function Restoration

Wang

IEICE Trans. Inf. & Syst.

et al. 2014

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SUMMARYThis paper provides a prototype neural prosthesis system dedicated to restoring continence and micturition function for patients with lower urinary tract diseases, such as detrusor hyperreflexia and detrusorsphincter dyssynergia. This system consists of an ultra low-noise electroneurogram (ENG) signal recording module, a bi-phasic electrical stimulator module and a control unit for closed-loop bladder monitoring and controlling. In order to record extremely weak ENG signal from extradural sacral nerve roots, the system provides a programmable gain from 80 dB to 117 dB. By combining of advantages of commercial-off-the-shelf (COTS) electronics and custom designed IC, the recording front-end acquires a fairly low input-referred noise (IRN) of 0.69 μV rms under 300 Hz to 3 kHz and high area-efficiency. An on-chip multi-steps single slope analogto-digital converter (ADC) is used to digitize the ENG signals at sampling rate of 10 kSPS and achieves an effective number of bits (ENOB) of 12.5. A bi-phasic current stimulus generator with wide voltage supply range (±0.9 V to ±12.5 V) and variable output current amplitude (0-500 μA) is introduced to overcome patient-depended impedance between electrode and tissue electrolyte. The total power consumption of the entire system is 5.61 mW. Recording and stimulation function of this system is switched by control unit with time division multiplexing strategy. The functionality of this proposed prototype system has been successfully verified through in-vivo experiments from dogs extradural sacral nerve roots. key words: neural prosthesis, functional electrical stimulation,closed-loop bladder control, acute animal experiment, spinal cord injury

“…It will lead to the incidence of age-related diseases growing rapidly such as the hypertension, the heart disease and the diabetes. Therefore, the physiological signals acquisition [1][2][3][4] and processing [5][6][7] are of great interest to scientists and clinicians. The ECG signals processing has developed rapidly, due to the sudden and high mortality rates of heart diseases.…”

Section: Introductionmentioning

confidence: 99%

A low-complexity ECG processing algorithm based on the Haar wavelet transform for portable health-care devices

et al. 2014

Sci. China Inf. Sci.

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This paper presents a simple Electrocardiogram (ECG) processing algorithm for portable healthcare devices. This algorithm consists of the Haar wavelet transform (HWT), the modulus maxima pair detection (MMPD) and the peak position modification (PPM). To lessen the computational complexity, a novel no multiplier structure is introduced to implement HWT. In the MMPD, the HWT coefficient at scale 2 4 is processed to find candidate peak positions of ECG. The PPM is designed to correct the time shift in digital process and accurately determine the location of peaks. Some new methods are proposed to improve anti-jamming performance in MMPD and PPM. Evaluated by the MIT-BIH arrhythmia database, the sensitivity (Se) of QRS detection is 99.53% and the positive prediction (Pr) of QRS detection is 99.70%. The QT database is chosen to fully validate this algorithm in complete delineation of ECG waveform. The mean µ and standard deviation σ between test results and annotations are calculated. Most of σ satisfies the CSE limits which indicates that the results are stable and reliable. A detailed and rigorous computational complexity analysis is presented in this paper. The number of arithmetic operations in N input samples is chosen as the criterion of complexity. Without any multiplication operations, the number of addition operations is only about 16.33N. This algorithm achieves high detection accuracy and the lower computational complexity. Keywords Haar wavelet transform (HWT), modulus maxima pair detection (MMPD), peak position modification (PPM), ECG processing, low complexity, portable health-care devices Citation Li P, Liu M, Zhang X, et al. A low-complexity ECG processing algorithm based on the Haar wavelet transform for portable health-care devices.