A 4 µW/Ch analog front-end module with moderate inversion and power-scalable sampling operation for 3-D neural microsystems.

We report an analog front-end prototype designed in 0.25 µm CMOS process for hybrid integration into 3-D neural recording microsystems. For scaling towards massive parallel neural recording, the prototype has investigated some critical circuit challenges in power, area, interface, and modularity. We achieved extremely low power consumption of 4 µW/channel, optimized energy efficiency using moderate inversion in low-noise amplifiers (K of 5.98 × 108 or NEF of 2.9), and minimized asynchronous interface (only 2 per 16 channels) for command and data capturing. We also implemented adaptable operations including programmable-gain amplification, power-scalable sampling (up to 50 kS/s/channel), wide configuration range (9-bit) for programmable gain and bandwidth, and 5-bit site selection capability (selecting 16 out of 128 sites). The implemented front-end module has achieved a reduction in noise-energy-area product by a factor of 5-25 times as compared to the state-of-the-art analog front-end approaches reported to date.

IBCOM (intra-brain communication) microsystem: wireless transmission of neural signals within the brain.

We report our preliminary work to explore a new method of signal transmission for bio-implantable microsystems. Intra-brain communication or IBCOM is a wireless signal transmission method that uses the brain itself as a conductive medium to transmit the data and commands between neural implants and data processing systems outside the brain. Two miniaturized IBCOM (micro-IBCOM) CMOS chips were designed and fabricated for an in vivo test bed to transmit two prerecorded neural signals at different binary frequency shift keying (BFSK) carrier frequencies to validate the feasibility of IBCOM concept. The chips were packaged for full implantation in a rat brain except for external power delivery. The original neural signal waveforms were successfully recovered after being transmitted between two platinum electrodes separated by 15 mm with transmission power less than 650 pJ/bit for the CMOS implementation.

Sleep apnea detection using an adaptive fuzzy logic based screening system.

We report an adaptive diagnostic system for the classification of breathing events for the purpose of detecting sleep apnea syndromes. The system employs two classification engines used in series. The first engine is fuzzy logic-based and generates one of three outcomes for each breathing event: normal, abnormal, and not-sure. The second classification engine is based on a center of gravity engine which is trained using the normal and abnormal events, generated by the first engine, and is specifically designed for sorting out the not-sure events. The fuzzy logic engine can be tuned very conservatively to reduce or eliminate the chance of error at the first stage. Since the second engine is trained adaptively using normal and abnormal data of the same patient, its accuracy is generally better than relying on multi-patient training approaches. The two-step, adaptive nature of the system allows for high accuracy and lends itself well for practical implementation.

Sleep apnea detection and classification using fuzzy logic: clinical evaluation.

We have previously reported a system suitable for detection and classification of sleep apnea syndromes. This paper reports the results of the clinical evaluation of the proposed system. In the current implementation, the system uses breathing signals: nasal flow, thorax movement, and abdomen movement. The detection part of the system uses only the nasal flow signal to detect apnea employing two engines used in series. It then feeds segments labeled as abnormal to the classification part of the system, which uses the center of gravity of each segment to determine the type of abnormality: obstructive, central or hypopnea. In comparison to other systems, this implementation can be shown to be simpler and more accurate. When the low implementation cost is taken into consideration, the proposed system has a substantial potential for being used as a screening device.