This paper reports on the design, implementation, and test of a stimulation back-end, for an implantable retinal prosthesis. In addition to traditional rectangular pulse shapes, the circuit features biphasic stimulation pulses with both rising and falling exponential shapes, whose time constants are digitally programmable. A class-B second generation current conveyor is used as a wide-swing, high-output-resistance stimulation current driver, delivering stimulation current pulses of up to ±96 μA to the target tissue. Duration of the generated current pulses is programmable within the range of 100 μs to 3 ms. Current-mode digital-to-analog converters (DACs) are used to program the amplitudes of the stimulation pulses. Fabricated using the IBM 130 nm process, the circuit consumes 1.5×1.5 mm of silicon area. According to the measurements, the DACs exhibit DNL and INL of 0.23 LSB and 0.364 LSB, respectively. Experimental results indicate that the stimuli generator meets expected requirements when connected to electrode-tissue impedance of as high as 25 k Ω. Maximum power consumption of the proposed design is 3.4 mW when delivering biphasic rectangular pulses to the target load. A charge pump block is in charge of the upconversion of the standard 1.2-V supply voltage to ±3.3V.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/TNSRE.2016.2542112 | DOI Listing |
J Acoust Soc Am
September 2024
School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, China.
A speech intelligibility (SI) prediction model is proposed that includes an auditory preprocessing component based on the physiological anatomy and activity of the human ear, a hierarchical spiking neural network, and a decision back-end processing based on correlation analysis. The auditory preprocessing component effectively captures advanced physiological details of the auditory system, such as retrograde traveling waves, longitudinal coupling, and cochlear nonlinearity. The ability of the model to predict data from normal-hearing listeners under various additive noise conditions was considered.
View Article and Find Full Text PDFJ Neural Eng
September 2023
Department of Biomedical Engineering, University of California Irvine (UCI), Irvine, CA 92697, United States of America.
Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers.
View Article and Find Full Text PDFFront Neuroinform
March 2023
Medizinische Hochschule Hannover, Hannover, Germany.
Speech understanding in cochlear implant (CI) users presents large intersubject variability that may be related to different aspects of the peripheral auditory system, such as the electrode-nerve interface and neural health conditions. This variability makes it more challenging to proof differences in performance between different CI sound coding strategies in regular clinical studies, nevertheless, computational models can be helpful to assess the speech performance of CI users in an environment where all these physiological aspects can be controlled. In this study, differences in performance between three variants of the HiRes Fidelity 120 (F120) sound coding strategy are studied with a computational model.
View Article and Find Full Text PDFTrends Hear
January 2023
Department of Otolaryngology, 9177Hannover Medical School, Hannover, Germany.
Cochlear implants (CIs) are implantable medical devices that can partially restore hearing to people suffering from profound sensorineural hearing loss. While these devices provide good speech understanding in quiet, many CI users face difficulties when listening to music. Reasons include poor spatial specificity of electric stimulation, limited transmission of spectral and temporal fine structure of acoustic signals, and restrictions in the dynamic range that can be conveyed via electric stimulation of the auditory nerve.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
November 2021
Stimulation of target neuronal populations using optogenetic techniques during specific sleep stages has begun to elucidate the mechanisms and effects of sleep. To conduct closed-loop optogenetic sleep studies in untethered animals, we designed a fully integrated, low-power system-on-chip (SoC) for real-time sleep stage classification and stage-specific optical stimulation. The SoC consists of a 4-channel analog front-end for recording polysomnography signals, a mixed-signal machine-learning (ML) core, and a 16-channel optical stimulation back-end.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!