Jin-Chern Chiou

Noninvasive Neural Prostheses Using Mobile and Wireless EEG

Neural prosthetic technologies have helped many patients by restoring vision, hearing, or movement and relieving chronic pain or neurological disorders. While most neural prosthetic systems to date have used invasive or implantable devices for patients with inoperative or malfunctioning external body parts or internal organs, a much larger population of ldquohealthyrdquo people who suffer episodic or progressive cognitive impairments in daily life can benefit from noninvasive neural prostheses. For example, reduced alertness, lack of attention, or poor decision-making during monotonous, routine tasks can have catastrophic consequences. This study proposes a noninvasive mobile prosthetic platform for continuously monitoring high-temporal resolution brain dynamics without requiring application of conductive gels on the scalp. The proposed system features dry microelectromechanical system electroencephalography sensors, low-power signal acquisition, amplification and digitization, wireless telemetry, online artifact cancellation, and signal processing. Its implications for neural prostheses are examined in two sample studies: 1) cognitive-state monitoring of participants performing realistic driving tasks in the virtual-reality-based dynamic driving simulator and 2) the neural correlates of motion sickness in driving. The experimental results of these studies provide new insights into the understanding of complex brain functions of participants actively performing ordinary tasks in natural body positions and situations within real operational environments.

Using novel MEMS EEG sensors in detecting drowsiness application

Electroencephalographic (EEG) analysis has been widely adopted for the monitoring of cognitive state changes and sleep stages because abundant information in EEG recording reflects changes in drowsiness, arousal, sleep, and attention, etc. In this study, micro-electro-mechanical systems (MEMS) based silicon spiked electrode array, namely dry electrodes, are fabricated and characterized to bring EEG monitoring to the operational workplaces without requiring conductive paste or scalp preparation. An isotropic/anisotropic reactive ion etching with inductive coupled plasma (RIE-ICP) micromachining fabrication process was developed to manufacture the needle-like micro probes to pierce the stratum corneum of skin and obtain superior electrically conducting characteristics. This article reports a series of prosperity testing and evaluations of continuous EEG recordings. Our results suggest that the dry electrodes have advantages in electrode-skin interface impedance, signal intensity and size over the conventional (wet) electrodes. In addition, we also developed an EEG-based drowsiness estimation system that consists of the dry-electrode array, power spectrum estimation, principal component analysis (PCA)-based EEG signal analysis, and multivariate linear regression to estimate driverpsilas drowsiness level in a virtual-reality-based dynamic driving simulator to demonstrate the potential applications of the MEMS electrodes in operational environments.

A Low-Power Bio-Potential Acquisition System with Flexible PDMS Dry Electrodes for Portable Ubiquitous Healthcare Applications

This work describes a bio-potential acquisition system for portable ubiquitous healthcare applications using flexible polydimethylsiloxane dry electrodes (FPDEs) and a low-power recording circuit. This novel FPDE used Au as the skin contact layer, which was made using a CO2 laser and replica method technology. The FPDE was revised from a commercial bio-potential electrode with a conductive snap using dry electrodes rather than wet electrodes that proposed reliable and robust attachment for the purpose of measurement, and attaching velcro made it wearable on the forearm for bio-potential applications. Furthermore, this study proposes a recording device to store bio-potential signal data and provides portability and low-power consumption for the proposed acquisition system. To acquire differential bio-potentials, such as electrocardiogram (ECG) signals, the proposed recording device includes a low-power front-end acquisition chip fabricated using a complementary metal-oxide-semiconductor (CMOS) process, a commercial microcontroller (MSP430F149), and a secure digital (SD) card for portable healthcare applications. The proposed system can obtain ECG signals efficiently and are comfortable to the skin. The power consumption of the system is about 85 mW for continuous working over a 3 day period with two AA batteries. It can also be used as a compact Holter ECG system.

VBM Reveals Brain Volume Differences between Parkinson’s Disease and Essential Tremor Patients

Symptoms of essential tremor (ET) are similar to those of Parkinson’s disease (PD) during their initial stages. Presently, there are few stable biomarkers available on a neuroanatomical level for distinguishing between these two diseases. However, few investigations have directly compared the changes in brain volume and assessed the compensatory effects of a change in the parts of the brain associated with PD and with ET. To determine the compensatory and/or degenerative anatomical changes in the brains of PD and ET patients, the present study tested, via two voxel-based morphometry (VBM) approaches (Basic vs. DARTEL VBM processing), the anatomical brain images of 10 PD and 10 ET patients, as well as of 13 age-matched normal controls, obtained through a 3T magnetic resonance scanner. These findings indicate that PD and ET caused specific patterns of brain volume alterations in the brains examined. In addition, our observations also revealed compensatory effects, or self-reorganization, occurring in the thalamus and the middle temporal gyrus in the PD and ET patients, due perhaps in part to the enhanced thalamocortical sensorimotor interaction and the head-eye position readjustment, respectively, in these PD and ET patients. Such a distinction may lend itself to use as a biomarker for differentiating between these two diseases.

Wearable and Wireless Brain-Computer Interface and Its Applications

This study extends our previous work on mobile & wireless EEG acquisition to a truly wearable and wireless human-machine interface, NCTU Brain-Computer-Interface-headband (BCI-headband), featuring: (1) dry Micro-Electro-Mechanical System (MEMS) EEG electrodes with 400 ganged contacts for acquiring signals from non-hairy sites without use of gel or skin preparation; (2) a miniature data acquisition circuitry; (3) wireless telemetry; and (4) online signal processing on a commercially available cell phone or a lightweight, wearable digital signal processing module. The applicability of the NCTU BCI-headband to EEG monitoring in real-world environments was demonstrated in a sample study: cognitive-state monitoring and management of participants performing normal tasks.

Through-silicon-via-based double-side integrated microsystem for neural sensing applications

This paper presents a Through-Silicon-Via (TSV) based double-side integrated microsystem for brain neural sensing applications. Figure 6.3.1 shows the structure of the double-side integrated microsystem. MEMS neural microprobe array and low-power CMOS readout circuit are fabricated on two sides of the same silicon substrate, and TSVs are used to form a low impedance interconnection between the microprobe and CMOS circuitry, thus providing the shortest signal transmission distance from sensors to circuits. The low parasitic impedance of TSV minimizes transmission loss and noise. The overall chip is 5x5mm2, 350μm in thickness including 150μm probe height and 200μm TSV height, respectively. A total of 480 microprobes is divided into 4x4 sensing areas, forming 16channels. 16 TSV arrays are used to connect the microprobe outputs to 16 readout circuits fabricated on the opposite side of the silicon substrate. The proposed structure allows stacking of other CMOS chips onto the circuit side by TSV 3D IC technique.

Closed-loop fuzzy control of torsional micromirror with multiple electrostatic electrodes

The micromirror device that can achieve analog behavior plays a very important role in optical MEMS. However, traditional electrostatic micromirror device driven by a single electrode can not achieve the analog behavior due to its nonlinear transfer characteristic. In this regard, the concept of multiple-electrodes-controlled mirror device is proposed previously to overcome the above mentioned drawback. The experimental results have motivated us to make more efforts to improve the performance such as operating frequency of the proposed micromirror device. In order to increase the operating frequency, the transient behavior of the mirror must be improved first. In this article, we show that fuzzy control technology is a good candidate to improve the transient behavior of the proposed device.

A contact lens sensor system with a micro-capacitor for wireless intraocular pressure monitoring

This paper proposes a novel micro-capacitor sensor for intraocular pressure (IOP) measurement on soft contact lens. The sensor was designed and fabricated by using MEMS fabrication technologies. The contact lens is for wearing on a cornea such that a curvature of the contact lens corresponds substantially to that of the cornea, and is preferably made of Hydroxyethylmethacrylate (HEMA) by cast-molding method of soft contact lens for high oxygen permeability and comfortable long-duration wearing. The prototype without wireless antenna has been implemented with a sensitivity of 0.43 pF/mmHg in measurement of human eye like balloon pressure test between 100 mmHg and 180 mmHg. The results show its high stability and reproducibility in a series of repeatable pressure variation. In future work the micro-capacitor will be tested on enucleated porcine eyes with better and integrated with a radio frequency integrated circuit and antenna on soft contact lens so that IOP value could be transferred to voltage value via capacitor to voltage converter and transmits IOP sensing signal by wireless telemetry system.

A Wirelessly Powered Smart Contact Lens with Reconfigurable Wide Range and Tunable Sensitivity Sensor Readout Circuitry

This study presented a wireless smart contact lens system that was composed of a reconfigurable capacitive sensor interface circuitry and wirelessly powered radio-frequency identification (RFID) addressable system for sensor control and data communication. In order to improve compliance and reduce user discomfort, a capacitive sensor was embedded on a soft contact lens of 200 μm thickness using commercially available bio-compatible lens material and a standard manufacturing process. The results indicated that the reconfigurable sensor interface achieved sensitivity and baseline tuning up to 120 pF while consuming only 110 μW power. The range and sensitivity tuning of the readout circuitry ensured a reliable operation with respect to sensor fabrication variations and independent calibration of the sensor baseline for individuals. The on-chip voltage scaling allowed the further extension of the detection range and prevented the implementation of large on-chip elements. The on-lens system enabled the detection of capacitive variation caused by pressure changes in the range of 2.25 to 30 mmHg and hydration level variation from a distance of 1 cm using incident power from an RFID reader at 26.5 dBm.

A Comparison of Independent Event-Related Desynchronization Responses in Motor-Related Brain Areas to Movement Execution, Movement Imagery, and Movement Observation

Electroencephalographic (EEG) event-related desynchronization (ERD) induced by movement imagery or by observing biological movements performed by someone else has recently been used extensively for brain-computer interface-based applications, such as applications used in stroke rehabilitation training and motor skill learning. However, the ERD responses induced by the movement imagery and observation might not be as reliable as the ERD responses induced by movement execution. Given that studies on the reliability of the EEG ERD responses induced by these activities are still lacking, here we conducted an EEG experiment with movement imagery, movement observation, and movement execution, performed multiple times each in a pseudorandomized order in the same experimental runs. Then, independent component analysis (ICA) was applied to the EEG data to find the common motor-related EEG source activity shared by the three motor tasks. Finally, conditional EEG ERD responses associated with the three movement conditions were computed and compared. Among the three motor conditions, the EEG ERD responses induced by motor execution revealed the alpha power suppression with highest strengths and longest durations. The ERD responses of the movement imagery and movement observation only partially resembled the ERD pattern of the movement execution condition, with slightly better detectability for the ERD responses associated with the movement imagery and faster ERD responses for movement observation. This may indicate different levels of involvement in the same motor-related brain circuits during different movement conditions. In addition, because the resulting conditional EEG ERD responses from the ICA preprocessing came with minimal contamination from the non-related and/or artifactual noisy components, this result can play a role of the reference for devising a brain-computer interface using the EEG ERD features of movement imagery or observation.