Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection.

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0-6.3%, the respiration detection was 0-9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.

Vertical and bevel-structured SiC etching techniques incorporating different gas mixture plasmas for various microelectronic applications.

This study presents a detailed fabrication method, together with validation, discussion, and analysis, for state-of-the-art silicon carbide (SiC) etching of vertical and bevelled structures by using inductively coupled plasma reactive ion etching (ICP-RIE) for microelectronic applications. Applying different gas mixtures, a maximum bevel angle of 87° (almost vertical), large-angle bevels ranging from 40° to 80°, and small-angel bevels ranging from 7° to 17° were achieved separately using distinct gas mixtures at different ratios. We found that SF6 with additive O2 was effective for vertical etching, with a best etching rate of 3050 Å/min. As for the large-angle bevel structures, BCl3 + N2 gas mixtures show better characteristics, exhibiting a controllable and large etching angle range from 40° to 80° through the adjustment of the mixture ratio. Additionally, a Cl2 + O2 mixture at different ratios is applied to achieve a small-angel bevels ranging from 7° to 17°. A minimum bevel angel of approximately 7° was achieved under the specific volume of 2.4 sccm Cl2 and 3.6 sccm O2. These results can be used to improve performance in various microelectronic applications including MMIC via holes, PIN diodes, Schottky diodes, JFETs' bevel mesa, and avalanche photodiode fabrication.

Design and Fabrication of Implantable Neural Probes with Monolithically Integrated Light-Emitting Diodes for Optogenetic Applications.

We report an implantable neural probe with monolithically integrated light-emitting diodes (LEDs) and recording site for optogenetic applications. The device were designed and fabricated with 2-inch gallium nitride on silicon epitaxial wafer. The neural probe consisted of three µLEDs (a mesa size of 310 × 41 mm2) and four electrical recording sites, which had a total length of 6.72 mm (PCB bonding region + implanting region). The designed implantable neural probe was successfully processed by the conventional LED fabrication and Si microfabrcation. These methods can offer relatively rapid and easy fabrication. For fabricated µLEDs, the optical and electrical properties were measured and characterized. At 1 mA, the emission wavelength was around 460 nm and it was slightly blue-shifted with the increase of injection current. Also, the optical power density was about 1 mW/mm2 at an electrical input power of 3.5 mW, and it was increased to 6.3 mW/mm2 at 24 mW.

Characterization of topographically specific sleep spindles in mice.

STUDY OBJECTIVE: Sleep spindles in humans have been classified as slow anterior and fast posterior spindles; recent findings indicate that their profiles differ according to pharmacology, pathology, and function. However, little is known about the generation mechanisms within the thalamocortical system for different types of spindles. In this study, we aim to investigate the electrophysiological behaviors of the topographically distinctive spindles within the thalamocortical system by applying high-density EEG and simultaneous thalamic LFP recordings in mice. DESIGN: 32-channel extracranial EEG and 2-channel thalamic LFP were recorded simultaneously in freely behaving mice to acquire spindles during spontaneous sleep. SUBJECTS: Hybrid F1 male mice of C57BL/6J and 129S4/svJae. MEASUREMENTS AND RESULTS: Spindle events in each channel were detected by spindle detection algorithm, and then a cluster analysis was applied to classify the topographically distinctive spindles. All sleep spindles were successfully classified into 3 groups: anterior, posterior, and global spindles. Each spindle type showed distinct thalamocortical activity patterns regarding the extent of similarity, phase synchrony, and time lags between cortical and thalamic areas during spindle oscillation. We also found that sleep slow waves were likely to associate with all types of sleep spindles, but also that the ongoing cortical decruitment/ recruitment dynamics before the onset of spindles and their relationship with spindle generation were also variable, depending on the spindle types. CONCLUSION: Topographically specific sleep spindles show distinctive thalamocortical network behaviors.

Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox.

The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.

Cortical source localization of mouse extracranial electroencephalogram using the FieldTrip toolbox.

Neuronal source estimation is a general tool for analyzing spatiotemporal dynamics in human EEG. Despite rapidly-evolving interest in human brain, there are few EEG based source estimation tools in rodent brain. Therefore, we implemented source estimation tool in a mouse model, using the FieldTrip open-source software. High resolution EEGs with a known cortical source were recorded with a recently developed 40-channel polyimide-based microelectrode under optical stimulation on optogenetially engineered mice. To obtain realistic mouse head models, the volume conduction model was extracted from in vitro mouse brain MRIs. Segmented compartments (skin and outer/inner skull) were used to form triangular meshes and then applied to the boundary element method. The high-resolution EEGs recorded during various optogenetic stimulation of the mouse brain were inversely source reconstructed using minimum-norm estimate. Estimated source locations and strengths were reconstructed, and their error was calculated to evaluate FieldTrip-based source localization algorithm. In summary, source localization imaging of the mouse brain was successfully achieved, using freely-available open source software. This will be useful to investigate the functional dynamics of mouse brain in noninvasive measure.