IEEE transactions on biomedical circuits and systems最新文献

Low-intensity focused ultrasound (FUS) is an emerging non-invasive and spatially/temporally precise method for modulating the firing rates and patterns of peripheral nerves. This paper describes an image-guided platform for chronic and patient-specific FUS neuromodulation. The system uses custom wearable probes containing separate ultrasound imaging and modulation transducer arrays realized using piezoelectric transducers assembled on a flexible printed circuit board (PCB). Dual-mode probes operating around 4 MHz (imaging) and 1.3 MHz (modulation) were fabricated and tested on tissue phantoms. The resulting B-mode images were analyzed using a template-matching algorithm to estimate the location of the target nerve and then direct the modulation beam toward the target. The ultrasound transmit voltage used to excite the modulation array was optimized in real-time by automatically regulating functional feedback signals (the average rates of emulated muscle twitches detected by an on-board motion sensor) through a proportional and integral (PI) controller, thus providing robustness to inter-subject variability and probe positioning errors. The proposed closed-loop neuromodulation paradigm was experimentally demonstrated in vitro using an active tissue phantom that integrates models of the posterior tibial nerve and nearby blood vessels together with embedded sensors and actuators.

This paper proposed an event-driven clockless level-crossing ADC (LC-ADC) suitable for biomedical applications. Thanks to the LC loop, the sampling rate of the converter automatically adapts to the input activities. Activity-dependent power consumption and data compression can thus be realized, saving system power, especially during time-sparse signal acquisition. Meanwhile, a SAR-assisted loop is exploited to resolve the loop-delay-induced distortion in conventional LC-ADC. Therefore, the resolution and power efficiency of the LC-ADC are improved effectively while maintaining the event-driven feature. Implemented in a 55nm process, the proposed LC-ADC achieves a scalable power consumption and a peak SNDR of 62.2dB for a 20kHz input. It also achieves a Walden FoM of 29.7fJ/conv.-step and a Schreier FoM of 158.6dB, which is best in class, without using off-chip calibration. Sub μW power is realized when the input frequency is below 1.5kHz. The proposed LC-ADC is also verified by simulated electrocardiogram (ECG), neural spike, and electromyogram (EMG) signals. It provides a ~7X data compression for ECG input, providing an attractive solution for time-sparse signal acquisition in biomedical applications.

This article describes a low noise and ultra-high input impedance active electrode (AE) interface chip for dry-electrode EEG recording. To compensate the input parasitic capacitance and the ESD leakage, power/ground/ESD bootstrapping is proposed. This design integrates chopping stabilization technique to suppress flicker noise of the amplifier which has never been tackled in previous bootstrapped AE design. Both on-chip and off-chip input routing is active shielded to minimize wire parasitic. Fabricated in a 0.18μm CMOS process, the AE core occupies about 0.056mm2 and draws 17.95μA from a 1.8V supply. The proposed AE achieves 100GΩ input impedance at 50Hz and over 1GΩ at 1kHz with a low input-referred noise of 382nVrms integrated from 0.5Hz to 70Hz. This design is the first 100GΩ@50Hz input impedance chopper stabilized AE compared to the state-of-the-art. Dry-electrode EEG recording capability of the proposed AE are verified on three types of experiments including spontaneous α-wave, event related potential and steady-state visual evoked potential.