This study aims to evaluate users’ attention levels under different lighting environments by measuring and analyzing brainwaves. Participants are asked to perform paper-based tests in a simulated office environment, while their brainwave signals are recorded. Each session of the experiment includes two tests to find the target words, 10 minutes each in Chinese and English, followed by 5-minute relaxation with closed eyes. The process is carried out in 12 lighting scenarios arranged by the Latin-square design, with the illuminance at 4 levels (250, 500, 750, 1000 lx) and the correlated color temperature at 3 levels (2690K, 3840K, 4990K). The acquired brainwave signals are processed by Hilbert-Huang transform to find the marginal spectra of intrinsic mode functions. The marginal spectra are then used to compute the corresponding powers in the alpha, beta, and gamma bands, which are called the band powers. By collecting the band power data of 24 participants, the power histogram in each band is plotted and normalized to be the probability density function. The receiver operating characteristic (ROC) analysis is then utilized to suggest the candidates of attention index based on the classification accuracy of binary discrimination tasks. The area under the ROC curve (AUC) for comparing the working and relaxing states is more than 0.85, which indicates sufficient classification accuracy. Moreover, the AUC between different lighting scenarios can be more than 0.65. According to the results, we have confirmed that the method has the potential for attention evaluation of office lighting environments.
Cardiovascular disease (CVD), the leading cause of death worldwide, has been viewed as one of the major problems for wealthy and industrialized nations for decades, and the need for rapid detection and timely diagnosis has the utmost importance. Cardiac troponin I (cTnI) is a promising biomarker for early diagnosis of acute myocardial infarction (AMI). Hence, the development of immunoassay based biosensor for cTnI is necessary. Over the past decades, there have been extensive researches regarding cTnI detection, including colorimetric, fluorescence, paramagnetic, electrochemical, and surface plasmon resonance. However, conventional laboratory methods are time-consuming and require expensive and bulky equipment. In light of this, the need for point of care testing becomes more crucial. Here, we use a programmable microcontroller unit (MCU) to operate the device. A digital-to-analog converter (DAC) is used to deliver a modulating signal to LEDs, and then the modulated light excites the samples in the microfluidic reaction wells. The signals from the sample and control group are obtained by two photodetectors individually. They will be amplified and demodulated through the lock-in amplifier and digitized by analog-to-digital converters (ADC) to the MCU. And the collected data will be presented on the device and uploaded synchronically to the smartphone via Bluetooth. The whole processing time is less than 5 minutes. Next, we use the microfluidic platform to simplify complicated laboratory procedures. In our study, we focus on using cTnI to detect the samples in the human serum or blood. In order to solve low efficacy caused by the non-specific binding, we used Zwitterionic carboxybetaine disulfide (CB) as a self-assembled monolayer in the experimental design. The use of self-assembled monolayer can not only decrease non-specific binding problem but also shorten the analysis time.
Oral cavity cancer is one of the most common malignancies. Development of immunoassay based biosensor for interleukin-8 (IL-8) protein is required. The miniaturization of the device is also necessary in order to provide ready-touse portable diagnostic tools (point of care diagnostic) for clinical uses. In the current study, a compact, portable and reliable biomarker detecting and analyzing system is presented. The light absorption analysis was performed by a low-cost and portable optical sensor device. We used a programmable microcontroller unit (MCU) to operate the device. A digitalto-analog converter (DAC) was used to deliver a modulating signal to LEDs, and then the modulated light excited the samples in the microfluidic detection chamber. The signals from the sample and control group were obtained by two photodetectors individually. The photodetectors were amplified and demodulated through the lock-in amplifier, and digitized by analog-to-digital converters (ADC) to the MCU. After that, the analyzed data was uploaded to the smartphone via Bluetooth. The device demonstrates a good measurement accuracy and shorter detection time compared to conventional methods.
Human blood analysis has provided rich information in rapid clinical diagnosis. Different from conventional blood cell counting method which is environment-dependent and costly, this study proposes an advanced blood cells imaging method at micron-scale to reduce the size of the equipment and decrease the total cost of testing. This approach applies the deep learning method and a convolutional neural network in reconstructing object images from the diffraction patterns. The holographic image is extracted by the convolution layer and the feature classification of the hidden layer rapidly identifies each diffraction pattern of the holographic image. The mean IoU for masks generated from the hologram is 0.876. Consequently, this deep learning approach is significantly more preferable to conventional calculation. It, thus, provides a portable, compact and cost-effective contrast-enhanced microholography system for clinical diagnosis.
For instant recognition of visual attentiveness, we established a set of studies based on signal conversion and machine learning of electroencephalogram (EEG). In this work, we invited twelve participants who were asked to play testing games for ensuing paying visual attention or to take a rest for a relaxed state. The brainwaves of participants were recorded by an EEG monitor during the experiments. EEG signals were transferred from time-domain into frequency-domain signals by fast Fourier transform (FFT) to obtain the frequency distributions of brainwaves of different visual attention states. The frequency information was then inputted into a probabilistic neural network (PNN) to build a discrimination model and to learn the rules that could determine an EEG epoch belongs to paying attention or not. As a type of supervised feedforward neural networks, PNN benefits high training speed and good error tolerance which is suitable for instant classification tasks. Given a set of training samples, PNN can train the predictable model of the specific EEG features by supervised learning algorithm, performing a classifier for visual attentiveness. In this paper, the proposed method successfully offers efficient differentiation for the assessment of visual attentiveness using FFT and PNN. The predictive model can distinguish the EEG epoch with attentive or relaxed states, which has an average accuracy higher than 82% for twelve participants. This attention classifier is expected to aid smart lighting control, specifically in assessing how different lighting situations will influence users’ visual work concentration.
Bullet-shaped LEDs are commonly used in self-luminous traffic signs as LED-dotted matrices due to their low cost, simplicity, robustness, and ease of installation. We proposed a simple low-cost method that creates a model suitable for the high manufacturing tolerance found in bullet-shaped LEDs. The method starts from measuring multiple one-dimensional angular intensity patterns at interested distances from multiple LEDs to form a database, including distances at 10, 15, 20, 25, 35, 50, and 100 mm. Their normalized cross-correlations are then calculated to find the batch that has the most similarity and base our model off that batch. Finally, we validate the model via Monte Carlo simulations in comparison to the original one-dimensional angular intensity patterns in the database. The platform demonstrated to obtain an average of 99% in normalized cross correlation between different batches of the same model LED, and a model of that LED is currently under development.
To investigate the legibility and visual comfort of LED traffic signs, an ergonomic experiment is performed on four custom-designed LED traffic signs, including three self-luminous ones as LED lightbox, LED backlight and regional LED backlight, and one non-self-luminous sign with external LED lighting. The four signs are hanged side-by-side and evaluated by observers through questionnaires. The signage dimension is one-sixth of the real freeway traffic signs, and the observation distance is 25 m. The luminance of three self-luminous signs is 216 cd/m2. The illuminance of external LED lighting is 400 lux on the traffic sign. The ambient illuminance is 2.8 and 6.0 lux in two rounds. The results show that self-luminous traffic signs provide superior legibility, visual comfort and user preference than the non-self-luminous one. Among the three self-luminous signs, regional LED backlight is most susceptible to the ambient illumination. LED lightbox has significantly better preference score than LED backlight under darker ambient lighting. Only LED lightbox has significantly better visual comfort than external LED lighting in the brighter environment. Based on the four LED traffic signs evaluated in this study, we suggest LED lightbox as the prior choice. Further investigations on the effect of ambient illumination and other designs of self-luminous traffic signs are in progress.
The subaperture stitching interferometry is a technique suitable for testing high numerical-aperture optics, large-diameter spherical lenses and aspheric optics. In the stitching process, each subaperture has to be placed at its correct position in a global coordinate, and the positioning precision would affect the accuracy of stitching result. However, the mechanical limitations in the alignment process as well as vibrations during the measurement would induce inevitable subaperture position uncertainties. In our previous study, a rotational scanning subaperture stitching interferometer has been constructed. This paper provides an iterative algorithm to correct the subaperture position without altering the interferometer configuration. Each subaperture is first placed at its geometric position estimated according to the F number of reference lens, the measurement zenithal angle and the number of pixels along the width of subaperture. By using the concept of differentiation, a shift compensator along the radial direction of the global coordinate is added into the stitching algorithm. The algorithm includes two kinds of compensators: one for the geometric null with four compensators of piston, two directional tilts and defocus, and the other for the position correction with the shift compensator. These compensators are computed iteratively to minimize the phase differences in the overlapped regions of subapertures in a least-squares sense. The simulation results demonstrate that the proposed method works to the position accuracy of 0.001 pixels for both the single-ring and multiple-ring configurations. Experimental verifications with the single-ring and multiple-ring data also show the effectiveness of the algorithm.
Sub-aperture testing methods are widely used in optical shops to test surface deformations of large diameter, high
numerical aperture, or aspherical lens surfaces. We are proposing a novel 4 axis vibration modulated interferometer for
subaperture testing. This interferometer takes advantage of the rotationally symmetric property of the optical lens and
measures the lens surface against its symmetry axis rotationally. By adapting a synchronous random phase modulation
measurement, interferometric data is acquired on the fly when the lens is being rotated. The vibration modulated
interference phase is then calculated and stitched into a complete lens surface map by least squared fitting. This method
has advantages over the prior methods in that it acquires the interferogram in a much shorter acquisition time, even with
lower requirements on the optics and mechanical hardware. The stitch error is then significantly decreased by increasing
both the lateral resolution of sub-aperture and the reduced position uncertainty of the stitched sub-aperture phase maps.
A measurement on a mild asphere is demonstrated to prove the feasibility of the proposed interferometer.
An aspheric testing system based on subaperture stitching interferometry has been developed. A procedure involving
subaperture aberration compensation and radial position scanning was established to resolve discrepancies in the
overlapped regions. During the aspheric measuring process, the Fizeau-interferometer axis, the optical axis of the
asphere, and the mechanical rotation axis have to be aligned. Due to the tolerance of alignment mechanisms, subaperture
interferograms would be contaminated by various amounts of aberrations associated with the rotation angle. These
aberrations introduce large inconsistencies between adjacent subapertures in the stitching algorithm. Zernike coefficients
of the subapertures in one annulus were examined and each coefficient term was found to be a sinusoidal function of the
rotation angle. To eliminate the influence of misalignments, each subaperture was compensated with appropriate
amounts of coma and astigmatism to make the resulting Zernike coefficients converge to the mean values of the
sinusoidal functions. In addition, the determination of the overlapped regions relies on the precise estimate of the
distance between the center of each subaperture and the center of the aspheric optics. This distance was first provided by
the encoder and then estimated by position scanning along the radial direction pixel-by-pixel in numerical computations.
The means of the standard deviation in the overlapped regions in the simulation and the experimental measurement of an
aspheric lens were 0.00004 and 0.06 waves, respectively. This demonstrates the reliability of the subaperture aberration
compensation and position scanning process.
A biometry-based human eye model was developed by using the empirical anatomic and optical data of ocular parameters. The gradient refractive index of the crystalline lens was modeled by concentric conicoid isoindical surfaces and was adaptive to accommodation and age. The chromatic dispersion of ocular media was described by Cauchy equations. The intraocular scattering model was composed of volumetric Mie scattering in the cornea and the crystalline lens, and a diffusive-surface model at the retina fundus. The retina was regarded as a Lambertian surface and was assigned its corresponding reflectance at each wavelength. The optical performance of the eye model was evaluated in CodeV and ASAP and presented by the modulation transfer functions at single and multiple wavelengths. The chromatic optical powers obtained from this model resembled that of the average physiological eyes. The scattering property was assessed by means of glare veiling luminance and compared with the CIE general disability glare equation. By replacing the transparent lens with a cataractous lens, the disability glare curve of cataracts was generated to compare with the normal disability glare curve. This model has high potential for investigating visual performance in ordinary lighting and display conditions and under the influence of glare sources.
An intraocular scattering model was constructed in human eye model and experimentally verified. According to the
biometric data, the volumetric scattering in crystalline lens and diffusion at retina fundus were developed. The scattering
parameters of cornea, including particle size and obscuration ratio, were varied to make the veiling luminance of the eye
model matching the CIE disability glare general formula. By replacing the transparent lens with a cataractous lens, the
disability glare curve of cataracts was generated and compared with that of transparent lenses. The MTF of the
intraocular scattering model showed nice correspondence with the data measured by a double-pass experiment.
A subaperture stitching algorithm was developed for testing aspheric surfaces. The full aperture was divided into one
central circular region plus several partially-overlapping annuli. Each annulus was composed of partially-overlapping
circular subapertures. The phase map in each subaperture was obtained through the phase-shifting interferometry and
retrieved by an iterative tilt-immune phase-shifting algorithm and a Zernike-polynomial-based phase-unwrapping
process. All subapertures in one annulus were stitched simultaneously in least-squares sense. By eliminating the
relative piston and tilt between adjacent subapertures, the sum of squared errors in the overlapped regions was
minimized. The phase stitching between annuli also utilized the least-squares method in the overlapped region.
Simulation results on a test wavefront with 30-wave spherical aberrations demonstrated the effectiveness of the proposed
algorithm. The rms phase residue after the phase-shifting, phase-unwrapping and phase-stitching processes was 0.006
waves, which met the precision requirement of common interferometers. This algorithm should be applicable to general
surfaces in subaperture stitching interferometry.
A biometry-based human eye model was developed by using the empirical anatomic and optical data of ocular
parameters. The gradient refractive index of the crystalline lens was modeled by concentric conicoid isoindical surfaces
and was adaptive to accommodation and age. The chromatic dispersion of homogeneous ocular media was described
by Cauchy equations. The gradient equations for the refractive index of crystalline lens were modified at particular
wavelengths according to the same dispersion model. Mie scattering was introduced to simulate volumetric light
scattering in the crystalline lens.
The optical performance of the eye model was evaluated in CodeV and ASAP and presented by the modulation transfer
function (MTF) at single and multiple wavelengths. The chromatic optical powers obtained from this model matched
that of physiological eyes. The scattering property was assessed by means of glare veiling luminance and compared
with CIE general disability glare equation. This model is highly potential for investigating visual performance in
ordinary lighting and display conditions and under the influence of glare sources.
A dynamic surface-plasmon-resonance (SPR) imaging sensor was developed to realize high-resolution high-throughput
applications. The SPR device consisted of a half-cylinder prism, 47.5nm-thick gold thin film and a custom-designed
flow cell to construct the Kretschmann configuration. A cylindrical lens pair in conjunction with the half-cylinder
prism was used to simplify the optical alignment procedure and to ensure plane-wave propagation inside the prism.
Phase-shifting interferometry was implemented by using a piezoelectric transducer (PZT) driven by a triangular voltage
waveform. A CCD camera was employed to acquire the sequential interference patterns required for phase calculations.
A reference signal obtained from a photodiode before the SPR device was used to compensate the system instability from
the laser intensity, environmental disturbances, and mechanical vibrations from the PZT. Integrating-bucket data
acquisition was realized with the synchronization between the photodiode and the CCD camera to preserve the dynamic
capability of the SPR sensor. System evaluations were performed by salt-water mixture measurements and gold-spot
array imaging. The achieved phase-measurement stability was 0.40 degrees and the system sensitivity was 5.14×104
degree/RIU (refractive index unit). The corresponding system resolution was 7.8×10-6 RIU. This SPR imager is
anticipated to find applications in studying biomolecular interactions with high resolution, stability, throughput and
dynamic capability.
Laser encoders overcome the fundamental resolution limit of geometrical optical encoders by cleverly converting the diffraction limit to phase coded information so as to facilitate nanometer displacement measurement. As positioning information was coded within the optical wavefront of laser encoders, interferometry principles thus must be adopted within the design of the laser encoders. This effect has posed a very strong alignment tolerance among various components of the whole laser encoder, which in turn impose a serious user adaptation bottleneck. Out of all alignment tolerance, the head-to-scale alignment tolerance represents the most important hindrance for wider applications. Improving the IBM laser optical encoder design by taking into the consideration of manufacturing tolerance of various optical components, an innovative linear laser encoder with very high head-to-scale tolerance is presented in this article. Efficiency of the TE/TM incident light beams on the grating scale used are examined theoretically and verified experimentally so as to provide design optimizations of the grating scale. Effect of various grating scale, quartz master or polymer-based grating replicate, is also detailed. Signal processing used to decoded the quadrature based positioning optical signal is also studied. Experimental results that verify the resolutions of the tabletop laser encoder prototype by comparing the decoded quadrature signal and a HP laser interferometer output signal is also presented.
Diffractive optical elements (DOE) have been widely used in both scientific and industrial applications. Optical wavefront measurements are one of the most important methodologies in verifying the performance of DOEs. Due to its non-destructive nature, ease of implementation, and relative short operation time, optical interferometry-based systems for wavefront measurements remain popular. The advantages and drawbacks of a non-common path and common path interferometry technique are examined first within this article.
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