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Biomedical Interfaces

The research of Biomedical Interfaces is all about innovation of new human machine interfaces through skin, heart, central and peripheral nervous system. The main objectives are to give disable people the ability to feel the world as normal people would, to investigate and understand more about human and animal behavior, to be able to diagnose and treat heart and brain disorders, and to use the model of human organs (e.g. brain, and heart) to develop more efficient machines (e.g. computers, and pumps.In our lab, we are innovating state of the art brain-machine interfaces, high density neural recording and stimulation microsystems, and smart sensors for smart skin interfaces.



BioBolt: A Minimally-Invasive Neural Interface for Wireless Epidural Record by Intra-Skin Communication

Recent technology progresses in CMOS and MEMS technologies have enhanced monitoring capability of neural activities for diagnosis of neural disorders, brain-machine interface and prosthetic applications. Recently, epidural recording gains its attention as an optimal solution for balanced signal fidelity and safety [1, 2]. In this paper, we report a bolt-shape Minimally-Invasive Neural Interface, BioBolt, which have (1) Low-Power Analog Front-Ends, (2) Epidural Record Capability in order to minimize any infection and tissue reaction, and (3) Intra-Skin Communication for low-power data transmission.
Nerual Probe With Optical Stimulation

In this project, we report a neural probe which can selectively stimulate target neurons optically from an integrated optical waveguide and also monitor extracellular neural signals in electrical recording sites. The waveguide is composed of SU-8 core and oxide cladding layer to guide a light from optical source. A U-groove has been formed at the end of the waveguide for easy alignment with an optical fiber. The coupling loss between the optical fiber and waveguide has been measured below -3.7 dB with a waveguide loss of -0.22 dB/mm.
Low-Power Low-Noise Pseudo-Openloop Preamplifier

We report an energy efficient pseudo open-loop amplifier with programmable band-pass filter developed for neural interface systems. The proposed amplifier consumes 400nA at 2.5V power supply. The measured thermal noise level is 85nV/sqrt(Hz) and input-referred noise is 1.69uVrms from 0.3Hz to 1 kHz. The amplifier has a noise efficiency factor of 2.43, the lowest in the differential topologies reported up to date to our knowledge. By programming the switched-capacitor frequency and bias current, we could control the bandwidth of the preamplifier from 138 mHz to 2.2 kHz to meet various application requirements. The entire preamplifier including band-pass filters has been realized in a small area of 0.043mm2 using a 0.25um CMOS technology.
Low-Power Area-Efficient SAR ADC

 We report an area-efficient 8bit SAR ADC using dual capacitor array banks for brain signal interface microsystems. The proposed ADC consumes 680nW and the total chip area is 0.035 mm2. We reduced the area and power by a factor of eight when compared with conventional approaches. If we increase the resolution, the area and power reduction factor exponentially increases in our architecture (e.g., a factor of 16 for 10 bit resolution). The measured SNDR, SFDR, THD, and ENOB are 42.82 ?0.47 dB, 57.90 ?2.82dB, -53.58 ?2.15 dB, and 6.65 ?0.07 bits, respectively.
IBCOM - Intra-Brain Communication for Implantable Devices:

We 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 (?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.
Artificial Smart Skin 1: Dual-Mode Tactile Sensor

In this work, we have proposed and demonstrated a dual mode proximity sensor which can detect not only proximity but also touch of an object for robot assistant applications. The sensor operates in two modes: proximity mode and tactile mode. Initially, the sensor operates in proximity mode until it touches an object. When the proximity mode detects the contact of any objects, the sensor will switch its mode into tactile sensing mode for acquiring an image from an object.
Artificial Smart Skin 2:Normal and Shear Force Measurement

In this research, we report a new flexible capacitive tactile sensor array with the capability of measuring both normal and shear force distribution using polydimethylsiloxane (PDMS) as a base material. A tactile cell consists of two thick PDMS layers with embedded electrodes, an air gap, and a pillar structure. The pillar structure is formed at the center of each tactile cell between the air gap under a large bump. There are four capacitors in a cell to decompose the contact force into normal and shear components...