A system-on-chip for an invisible, fully-implantable cochlear implant is presented. Implantable acoustic sensing is achieved by interfacing the SoC to a piezoelectric sensor that detects the sound-induced motion of the middle ear. Measurements from human cadaveric ears demonstrate that the sensor can detect sounds between 40 and 90 dB SPL over the speech bandwidth. A highly-reconfigurable digital sound processor enables system power scalability by reconfiguring the number of channels, and provides programmable features to enable a patient-specific fit. A mixed-signal arbitrary waveform neural stimulator enables energy-optimal stimulation pulses to be delivered to the auditory nerve. The energy-optimal waveform is validated with in-vivo measurements from four human subjects which show a 15% to 35% energy saving over the conventional rectangular waveform. Prototyped in a 0.18 μm high-voltage CMOS technology, the SoC in 8-channel mode consumes 572 μW of power including stimulation. The SoC integrates implantable acoustic sensing, sound processing, and neural stimulation on one chip to minimize the implant size, and proof-of-concept is demonstrated with measurements from a human cadaver ear.

A power-scalable SAR ADC for sensor applications is presented. The ADC features a reconfigurable 5-to-10-bit DAC whose power scales exponentially with resolution. At low resolutions where noise and linearity requirements are reduced, supply voltage scaling is leveraged to further reduce the energy-per-conversion. The ADC operates up to 2MS/s at 1V and 5kS/s at 0.4V, and its power scales linearly with sample rate down to leakage levels of 53nW at 1V and 4nW at 0.4V. Leakage power-gating during a SLEEP mode in between conversions reduces total power by up to 14% at sample rates below 1kS/s. Prototyped in a low-power 65nm CMOS process, the ADC in 10-bit mode achieves an INL and DNL of 0.57LSB and 0.58LSB respectively at 0.6V, and the Nyquist SNDR and SFDR are 55dB and 69dB respectively at 0.55V and 20kS/s. The ADC achieves an optimal FOM of 22.4fJ/conversion-step at 0.55V in 10-bit mode. The combined techniques of DAC resolution and voltage scaling maximize efficiency at low resolutions, resulting in an FOM that increases by only 7× over the 5-bit scaling range, improving upon a 32× degradation that would otherwise arise from truncation of bits from an ADC of fixed resolution and voltage.

Pressure ulcers are painful sores that arise from prolonged exposure to high pressure points, which restricts blood flow and leads to tissue necrosis. This is a common occurrence among patients with impaired mobility, diabetics and the elderly. In this work, a flexible pressure monitoring system for pressure ulcer prevention has been developed. The prototype consists of 99 capacitive pressure sensors on a 17-cm x 22-cm sheet which is flexible in two dimensions. Due to its low cost, the sensor sheet can be disconnected from the reusable electronics and be disposed of after use, suitable for a clinical setting. Each sensor has a resolution of better than 2-mmHg and a range of 50-mmHg and offset is calibrated in software. Realtime pressure data is displayed on a computer. A maximum sampling rate of 12-Hz allows for continuous monitoring of pressure points.

The cochlear implant (CI) is the most successful neural prosthesis, restoring the sensation of sound in people with severe-to-profound hearing loss by electrically stimulating the cochlear nerve. Existing CIs have an external, visible unit, and an internal, surgically-placed unit. There are significant challenges associated with the external unit, as it has limited utility and CI users often report a social stigma associated with prosthesis visibility. A fully-implantable CI (FICI) would address these issues. However, the volume constraint imposed on the FICI requires less power consumption compared to today’s CI. Because neural stimulation by CI electrodes accounts for up to 90% of power consumption, reduction in stimulation power will result directly in CI power savings. To determine an energy-efficient waveform for cochlear nerve stimulation, we used a genetic algorithm approach, incorporating a computational model of a single mammalian myelinated cochlear nerve fiber coupled to a stimulator-electrode-tissue interface. The algorithm’s prediction was tested in vivo in human CI subjects. We find that implementation of a non-rectangular biphasic neural stimulation waveform may result in up to 25% charge savings and energy savings within the comfortable range of hearing for CI users. The alternative waveform may enable future development of a FICI.

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