Article

A Cochlear-Implant Processor for Encoding Music and Lowering Stimulation Power

Adv. Bionics, Sylmar
IEEE Pervasive Computing (Impact Factor: 2.1). 02/2008; 7(1):40-48. DOI: 10.1109/MPRV.2008.3
Source: IEEE Xplore

ABSTRACT Cochlear implants (CIs), or bionic ears, restore hearing in profoundly deaf (greater than -90 dB hearing loss) patients. They function by transforming frequency patterns in sound into corresponding spatial electrode-stimulation patterns for the auditory nerve. Over the past 20 years, improvements in sound-processing strategies, in the number of electrodes and channels, and in the rate of stimulation have yielded improved sentence and word recognition scores in patients. Next- generation implants will be fully implanted inside the patient's body. Consequently, power consumption requirements for signal processing will be very stringent.

1 Bookmark
 · 
106 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Information is represented by the states of physical devices. It costs energy to transform or maintain the states of these physical devices. Thus, energy and information are deeply linked. This deep link allows the articulation of ten information-based principles for ultra low power design that apply to biology or electronics, to analog or digital systems, and to electrical or nonelectrical systems, at small or large scales. In this tutorial brief, we review these key principles along with examples of how they have been applied in practical electronic systems.
    Circuits and Systems II: Express Briefs, IEEE Transactions on 04/2012; 59(4):193-198. DOI:10.1109/TCSII.2012.2188451 · 1.19 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents the design and experimental results of a cochlea filter in analog very large scale integration (VLSI) which highly resembles physiologically measured response of the mammalian cochlea. The filter consists of three specialized sub-filter stages which respectively provide passive response in low frequencies, actively tunable response in mid-band frequencies and ultra-steep roll-off at transition frequencies from pass-band to stop-band. The sub-filters are implemented in balanced ladder topology using floating active inductors. Measured results from the fabricated chip show that wide range of mid-band tuning including gain tuning of over 20dB, Q factor tuning from 2 to 19 as well as the bio-realistic center frequency shift are achieved by adjusting only one circuit parameter. Besides, the filter has an ultra-steep roll-off reaching over 300 dB/dec. By changing biasing currents, the filter can be configured to operate with center frequencies from 31 Hz to 8 kHz. The filter is 9(th) order, consumes 59.5 ∼ 90.0 μW power and occupies 0.9 mm(2) chip area. A parallel bank of the proposed filter can be used as the front-end in hearing prosthesis devices, speech processors as well as other bio-inspired auditory systems owing to its bio-realistic behavior, low power consumption and small size.
    IEEE Transactions on Biomedical Circuits and Systems 07/2014; DOI:10.1109/TBCAS.2014.2328321 · 3.15 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper proposes an integrated event-based binaural silicon cochlea system aimed at efficient spatial audition and auditory scene analysis. The cochlea chip has a matched pair of digitally-calibrated 64-stage cascaded analog second-order filter banks with 512 pulse-frequency modulated (PFM) address-event representation (AER) outputs. The quality factors (Qs) of channels are individually adjusted by local DACs. The 2P4M 0.35 um CMOS chip consumes an average power of 14 mW including its integrated microphone preamplifiers and biasing circuits. Typical speech data rates are 10 k to 100 k events per second (eps) with peak output rates of 10 Meps. The event timing jitter is 2 us for a 250 mVpp input. It is shown that the computational cost of an event-driven source localization application can be up to 40 times lower when compared to a conventional cross-correlation approach.
    IEEE Transactions on Biomedical Circuits and Systems 01/2014; 8(4):453-464. DOI:10.1109/TBCAS.2013.2281834 · 3.15 Impact Factor

Preview (2 Sources)

Download
0 Downloads
Available from