Dielectrophoretically Assembled SWCNTs Networks on SU-8 Substrate for PEG/SWCNTs Composite Gas Sensor.

This study proposed a SU-8 based gas sensor, integrated with heater and sensing electrodes, to develop a multi-channel gas sensor with PEG/SWCNTs composite films. The impedance of single-walled carbon nanotubes (SWCNTs) on each sensing electrode was well controlled via dielectrophoresis technology. To investigate dielectrophoretic mobility characteristics, the concentric circular sensing electrode has three different spacing between the inner and outer electrodes, including 10 µm, 15 µm, and 20 µm. The electrodes were applied with a 5 MHz AC source with a voltage ranging from 1 Vpp to 5 Vpp. Polyethylene glycol (PEG) was deposited on the gas sensor via drop casting. The fabricated gas sensor was operated at different working temperatures, including 25 °C, 40 °C, 50 °C and 60 °C, to examine the sensing response. The response results revealed that the PEG/SWCNTs composites gas sensor with 60 °C working temperature exhibited the ability to detect 80 ppm ethanol vapor.

Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection.

This aim of this study was to find effective spectral bands for the early detection of oral cancer. The spectral images in different bands were acquired using a self-made portable light-emitting diode (LED)-induced autofluorescence multispectral imager equipped with 365 and 405 nm excitation LEDs, emission filters with center wavelengths of 470, 505, 525, 532, 550, 595, 632, 635, and 695 nm, and a color image sensor. The spectral images of 218 healthy points in 62 healthy participants and 218 tumor points in 62 patients were collected in the ex vivo trials at China Medical University Hospital. These ex vivo trials were similar to in vivo because the spectral images of anatomical specimens were immediately acquired after the on-site tumor resection. The spectral images associated with red, blue, and green filters correlated with and without nine emission filters were quantized by four computing method, including summated intensity, the highest number of the intensity level, entropy, and fractional dimension. The combination of four computing methods, two excitation light sources with two intensities, and 30 spectral bands in three experiments formed 264 classifiers. The quantized data in each classifier was divided into two groups: one was the training group optimizing the threshold of the quantized data, and the other was validating group tested under this optimized threshold. The sensitivity, specificity, and accuracy of each classifier were derived from these tests. To identify the influential spectral bands based on the area under the region and the testing results, a single-layer network learning process was used. This was compared to conventional rules-based approaches to show its superior and faster performance. Consequently, four emission filters with the center wavelengths of 470, 505, 532, and 550 nm were selected by an AI-based method and verified using a rule-based approach. The sensitivities of six classifiers using these emission filters were more significant than 90%. The average sensitivity of these was about 96.15%, the average specificity was approximately 69.55%, and the average accuracy was about 82.85%.

A High-Efficiency Driver Circuit for a Gas-Sensor Microheater Based on a Switch-Mode DC-to-DC Converter.

Low power consumption is one of the critical factors for successful Internet of Things (IoT) applications. In such applications, gas sensors have become a main source of power consumption because energy conversion efficiency of the microheater is relative over a wide range of operating temperatures. To improve the energy-conversion efficiency of gas-sensor microheaters, this paper proposes integrated switch-mode DC-to-DC power converter technology which we compare with traditional driving methods such as pulse-width modulation and the linear mode. The results indicate that energy conversion efficiency with this proposed method remains over 90% from 150 °C to 400 °C when using a 3.0, 4.2 and 5.0 V power supply. Energy-conversion efficiency increases by 1-74% compared with results obtained using the traditional driving methods, and the sensing film still detects alcohol and toluene at 200 °C and 280 °C, respectively, with high energy conversion efficiency. These results show that the proposed method is useful and should be further developed to drive gas-sensor microheaters, and then integrated into the circuits of the complementary metal-oxide-semiconductor micro electro mechanical systems (CMOS-MEMS).

Sensitivity Enhancement of Acetone Gas Sensor using Polyethylene Glycol/Multi-Walled Carbon Nanotubes Composite Sensing Film with Thermal Treatment.

There is a need to develop a chemiresistive gas sensor equipped with a thermostat over a wide area for the sensor, which can protect the sensor from the influence of ambient temperature due to the uniform temperature of the thermostat. In this paper, we demonstrated an acetone gas sensor based on a polyethylene glycol (PEG)/Multi-walled Carbon Nanotubes (MWCNTs) composite film, which was equipped with a thermostat. The sensor was operated at modest working temperatures for sensor sensitivity enhancement. The optimum design of the polyimide-based thermostat with widely uniform thermal distribution was investigated in detail. It was found that the temperature uniformity of the thermostat was achieved using double spiral geometry. The experimental results of the sensor response showed that the PEG/MWCNTs composite film with a moderate working temperature revealed a higher sensitivity than that without thermal treatment. Moreover, the sensing mechanisms of the PEG/MWCNTs composite gas sensor to acetone vapor were studied as well.

Ultrahigh-Density 256-Channel Neural Sensing Microsystem Using TSV-Embedded Neural Probes.

Highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this paper, a 256-channel neural sensing microsystem with a sensing area of 5 × 5 mm 2 is presented based on 2.5-D through-silicon-via (TSV) integration. This microsystem composes of dissolvable µ-needles, TSV-embedded µ-probes, 256-channel neural amplifiers, 11-bit area-power-efficient successive approximation register analog-to-digital converters, and serializers. This microsystem can detect 256 electrocorticography and local field potential signals within a small area of 5 mm × 5 mm. The neural amplifier realizes 57.8 dB gain with only 9.8 µW per channel. The overall power of this microsystem is only 3.79 mW for 256-channel neural sensing. A smaller microsystem with dimension of 6 mm × 4 mm has been also implanted into rat brain for somatosensory evoked potentials (SSEPs) recording by using contralateral and ipsilateral electrical stimuli with intensity from 0.2 to 1.0 mA, and successfully observed different SSEPs from left somatosensory cortex of a rat.

Portable LED-induced autofluorescence spectroscopy for oral cancer diagnosis.

Oral cancer is a serious and growing problem in many developing and developed countries. To improve the cancer screening procedure, we developed a portable light-emitting-diode (LED)-induced autofluorescence (LIAF) imager that contains two wavelength LED excitation light sources and multiple filters to capture ex vivo oral tissue autofluorescence images. Compared with conventional means of oral cancer diagnosis, the LIAF imager is a handier, faster, and more highly reliable solution. The compact design with a tiny probe allows clinicians to easily observe autofluorescence images of hidden areas located in concave deep oral cavities. The ex vivo trials conducted in Taiwan present the design and prototype of the portable LIAF imager used for analyzing 31 patients with 221 measurement points. Using the normalized factor of normal tissues under the excitation source with 365 nm of the central wavelength and without the bandpass filter, the results revealed that the sensitivity was larger than 84%, the specificity was not smaller than over 76%, the accuracy was about 80%, and the area under curve of the receiver operating characteristic (ROC) was achieved at about 87%, respectively. The fact shows the LIAF spectroscopy has the possibilities of ex vivo diagnosis and noninvasive examinations for oral cancer.

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 Wearable and Wireless Gas-Sensing System Using Flexible Polymer/Multi-Walled Carbon Nanotube Composite Films.

In this study, an integrated flexible gas sensor was developed based on a polymer/multi-walled carbon nanotube composite film by using Bluetooth wireless communication/interface technology. Polymer/multi-walled carbon nanotube composite films were deposited over a polyimide flexible substrate for building a gas sensor array by using a drop-casting method. Sensor response was acquired through interdigitated electrodes and multi-channel sensor boards, which were linked to a Bluetooth wireless transceiver. Additionally, a double-spiral-shaped heater was built into the backside of the gas sensor array as a thermostat to protect it from the influence of ambient temperature. Multi-channel sensing responses were read on a display screen via a smartphone application (app). The advantages of this system include light weight, low cost, highly integrated sensors, wireless telecommunication, and real-time functioning. Thus, it is a promising candidate for deployment in a wearable gas-sensing system used to study air pollution.

Effects of Operating Temperature on Droplet Casting of Flexible Polymer/Multi-Walled Carbon Nanotube Composite Gas Sensors.

This study examined the performance of a flexible polymer/multi-walled carbon nanotube (MWCNT) composite sensor array as a function of operating temperature. The response magnitudes of a cost-effective flexible gas sensor array equipped with a heater were measured with respect to five different operating temperatures (room temperature, 40 °C, 50 °C, 60 °C, and 70 °C) via impedance spectrum measurement and sensing response experiments. The selected polymers that were droplet cast to coat a MWCNT conductive layer to form two-layer polymer/MWCNT composite sensing films included ethyl cellulose (EC), polyethylene oxide (PEO), and polyvinylpyrrolidone (PVP). Electrical characterization of impedance, sensing response magnitude, and scanning electron microscope (SEM) morphology of each type of polymer/MWCNT composite film was performed at different operating temperatures. With respect to ethanol, the response magnitude of the sensor decreased with increasing operating temperatures. The results indicated that the higher operating temperature could reduce the response and influence the sensitivity of the polymer/MWCNT gas sensor array. The morphology of polymer/MWCNT composite films revealed that there were changes in the porous film after volatile organic compound (VOC) testing.

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.

Toward a Wirelessly Powered On-Lens Intraocular Pressure Monitoring System.

This paper presents a wireless on-lens intraocular pressure monitoring system, comprising a capacitance-to-digital converter and a wirelessly powered radio-frequency identification (RFID)-compatible communication system, for sensor control and data communication. The capacitive sensor was embedded on a soft contact lens of 200 µm thickness using commercially available biocompatible lens material, to improve compliance and reduce user discomfort. The sensor chip was shown to achieve effective number of bits greater than 10 over a capacitance range up to 50 pF while consuming only 64-µW power. The on-lens capacitive sensor could detect dielectric variation caused by changes in water content from a distance of 2 cm by using incident power from an RFID reader at 20 dBm. The maximum detectable distance was 11 cm with 30-dBm incident RF power. The rise in eye tissue temperature under 30-dBm RF exposure over an interval of 1 s was simulated and found to be less than 0.01°C.

A double-sided, single-chip integration scheme using through-silicon-via for neural sensing applications.

We present a new double-sided, single-chip monolithic integration scheme to integrate the CMOS circuits and MEMS structures by using through-silicon-via (TSV). Neural sensing applications were chosen as the implementation example. The proposed heterogeneous device integrates standard 0.18 µm CMOS technology, TSV and neural probe array into a compact single chip device. The neural probe array on the back-side of the chip is connected to the CMOS circuits on the front-side of the chip by using low-parasitic TSVs through the chip. Successful fabrication results and detailed characterization demonstrate the feasibility and performance of the neural probe array, TSV and readout circuitry. The fabricated device is 5 × 5 mm(2) in area, with 16 channels of 150 µm-in-length neural probe array on the back-side, 200 µm-deep TSV through the chip and CMOS circuits on the front-side. Each channel consists of a 5 × 6 probe array, 3 × 14 TSV array and a differential-difference amplifier (DDA) based analog front-end circuitry with 1.8 V supply, 21.88 µW power consumption, 108 dB CMRR and 2.56 µVrms input referred noise. In-vivo long term implantation demonstrated the feasibility of presented integration scheme after 7 and 58 days of implantation. We expect the conceptual realization can be extended for higher density recording array by using the proposed method.

An RFID-based on-lens sensor system for long-term IOP monitoring.

In this paper, an RFID-based on-lens sensor system is proposed for noninvasive long-term intraocular pressure monitoring. The proposed sensor IC, fabricated in a 0.18um CMOS process, consists of capacitive sensor readout circuitry, RFID communication circuits, and digital processing units. The sensor IC is integrated with electroplating capacitive sensors and a receiving antenna on the contact lens. The sensor IC can be wirelessly powered, communicate with RFID compatible equipment, and perform IOP measurement using on-lens capacitive sensor continuously from a 2cm distance while the incident power from an RFID reader is 20 dBm. The proposed system is compatible to Gen2 RFID protocol, extending the flexibility and reducing the self-developed firmware efforts.

Design and analysis of wearable pupillometer for autonomic neuropathy of diabetic patients.

Diabetes is a familiar disease in modern society. In the early stage of diabetes, symptoms are unobvious, but they usually induce diabetic autonomic neuropathy or, worse, cardiovascular autonomic neuropathy. Pupillometers are effective instruments for observing human pupils. This article presents a novel wearable pupillometer design, without external light artifacts, and an embedded algorithm with blinking elimination, which investigates autonomic neuropathy through recording pupil dynamics triggered by an external sensitive invisible light source. The pupillometer is experimented on 36 healthy subjects and 10 diabetic patients under four different colors (white, red, green, and blue) as well as two different light intensities: 50 and 500 mcd. Ten parameters derived from pupil diameter, pupil response time, and pupil response speed will be evaluated for the healthy subjects and diabetic patients. The results show that three in four parameters related to pupil diameters, one in four related to light intensities, and one in two related to pupil response speed could have significant differences (p<0.05) between healthy subjects and diabetic patients. These parameters obtain over 85% sensitivity, 83% specificity, and 88% accuracy. The pupillometer is proven reliable, effective, portable, and inexpensive for diagnosing diabetes in an early stage.

Research of accommodative microfluctuations caused by visual fatigue based on liquid crystal and laser displays.

Different levels of visual fatigue in the human eye depend on different color-formation methods and image quality. This paper uses the high-frequency component of the spectral power of accommodative microfluctuations as a major objective indicator for analyzing the effects of visual fatigue based on various displays, such as color-formation displays and 3D displays. Also, a questionnaire is used as a subjective indicator. The results are that 3D videos cause greater visual fatigue than 2D videos (p<0.001), the shutter-type 3D display causes visual fatigue more than the polarized type (p=0.012), the display of the time-sharing method causes greater visual fatigue than the spatial-formation method (p=0.008), and there is no significance between various light source modules of displays (p=0.162). In general, people with normal color discrimination have more visual fatigue than those with good color discrimination (p<0.001). Therefore, this paper uses the high-frequency component of accommodative microfluctuations to evaluate the physiological stress or strain by overexerting the visual system, and can compare the level of visual fatigue between various displays.

2.5D heterogeneously integrated microsystem for high-density neural sensing applications.

Heterogeneously integrated and miniaturized neural sensing microsystems are crucial for brain function investigation. In this paper, a 2.5D heterogeneously integrated bio-sensing microsystem with µ-probes and embedded through-silicon-via (TSVs) is presented for high-density neural sensing applications. This microsystem is composed of µ-probes with embedded TSVs, 4 dies and a silicon interposer. For capturing 16-channel neural signals, a 24 × 24 µ-probe array with embedded TSVs is fabricated on a 5×5 mm(2) chip and bonded on the back side of the interposer. Thus, each channel contains 6 × 6 µ -probes with embedded TSVs. Additionally, the 4 dies are bonded on the front side of the interposer and designed for biopotential acquisition, feature extraction and classification via low-power analog front-end (AFE) circuits, area-power-efficient analog-to-digital converters (ADCs), configurable discrete wavelet transforms (DWTs), filters, and a MCU. An on-interposer bus ( µ-SPI) is designed for transferring data on the interposer. Finally, the successful in-vivo test demonstrated the proposed 2.5D heterogeneously integrated bio-sensing microsystem. The overall power of this microsystem is only 676.3 µW for 16-channel neural sensing.

Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections.

Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).

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.

DNA sequencing using electrical conductance measurements of a DNA polymerase.

The development of personalized medicine-in which medical treatment is customized to an individual on the basis of genetic information-requires techniques that can sequence DNA quickly and cheaply. Single-molecule sequencing technologies, such as nanopores, can potentially be used to sequence long strands of DNA without labels or amplification, but a viable technique has yet to be established. Here, we show that single DNA molecules can be sequenced by monitoring the electrical conductance of a phi29 DNA polymerase as it incorporates unlabelled nucleotides into a template strand of DNA. The conductance of the polymerase is measured by attaching it to a protein transistor that consists of an antibody molecule (immunoglobulin G) bound to two gold nanoparticles, which are in turn connected to source and drain electrodes. The electrical conductance of the DNA polymerase exhibits well-separated plateaux that are ~3 pA in height. Each plateau corresponds to an individual base and is formed at a rate of ~22 nucleotides per second. Additional spikes appear on top of the plateaux and can be used to discriminate between the four different nucleotides. We also show that the sequencing platform works with a variety of DNA polymerases and can sequence difficult templates such as homopolymers.