High-throughput volumetric adaptive optical imaging using compressed time-reversal matrix

Deep-tissue optical imaging suffers from the reduction of resolving power due to tissue-induced optical aberrations and multiple scattering noise. Reflection matrix approaches recording the maps of backscattered waves for all the possible orthogonal input channels have provided formidable solutions for removing severe aberrations and recovering the ideal diffraction-limited spatial resolution without relying on fluorescence labeling and guide stars. However, measuring the full input–output response of the tissue specimen is time-consuming, making the real-time image acquisition difficult. Here, we present the use of a time-reversal matrix, instead of the reflection matrix, for fast high-resolution volumetric imaging of a mouse brain. The time-reversal matrix reduces two-way problem to one-way problem, which effectively relieves the requirement for the coverage of input channels. Using a newly developed aberration correction algorithm designed for the time-reversal matrix, we demonstrated the correction of complex aberrations using as small as 2% of the complete basis while maintaining the image reconstruction fidelity comparable to the fully sampled reflection matrix. Due to nearly 100-fold reduction in the matrix recording time, we could achieve real-time aberration-correction imaging for a field of view of 40 × 40 µm2 (176 × 176 pixels) at a frame rate of 80 Hz. Furthermore, we demonstrated high-throughput volumetric adaptive optical imaging of a mouse brain by recording a volume of 128 × 128 × 125 µm3 (568 × 568 × 125 voxels) in 3.58 s, correcting tissue aberrations at each and every 1 µm depth section, and visualizing myelinated axons with a lateral resolution of 0.45 µm and an axial resolution of 2 µm.

Exploring Unobserved Heterogeneity in Cyclists’ Occupying Motorized Vehicle Lane Behaviors at Different Bike Facility Configurations

Cyclists occupying motorized vehicle lanes disrupt road traffic order and increase collisions. Exploring the contributing factors could help develop countermeasures to regulate such behaviors. The purpose of this study is to explore the intrinsic features influencing the behavior of cyclists in occupying motorized vehicle lanes at different bicycle facilities. We investigated a total of 34,631 cycling behavior samples in the urban area of Pingdingshan, China. A Bayesian random parameter logit model was used to account for the unobserved heterogeneous effects. The experimental results of all bike facilities demonstrate that the bike type, dividing strip type, bike lane width, temporary on-street parking, and whether it is a working day significantly affect cyclists’ occupying motorized vehicle lane behaviors. Factors associated with unobserved heterogeneity are age, barriers dividing strip, vehicle lane numbers, bike volume, vehicle volume, and daily recording time intervals. Comparing the estimated model of five type bike lane facilities across different dividing strips, we find that cyclists have a significantly different occupying probability and the heterogeneity factors of the various bike facilities also have their focus. When the non-motorized road conditions become more open, the cyclist behavior becomes more random and the heterogeneity factors become broader.

Non-contact Sleep/Wake Monitoring Using Impulse-Radio Ultrawideband Radar in Neonates

Background: The gold standard for sleep monitoring, polysomnography (PSG), is too obtrusive and limited for practical use with tiny infants or in neonatal intensive care unit (NICU) settings. The ability of impulse-radio ultrawideband (IR-UWB) radar, a non-contact sensing technology, to assess vital signs and fine movement asymmetry in neonates was recently demonstrated. The purpose of this study was to investigate the possibility of quantitatively distinguishing and measuring sleep/wake states in neonates using IR-UWB radar and to compare its accuracy with behavioral observation-based sleep/wake analyses using video recordings.Methods: One preterm and three term neonates in the NICU were enrolled, and voluntary movements and vital signs were measured by radar at ages ranging from 2 to 27 days. Data from a video camcorder, amplitude-integrated electroencephalography (aEEG), and actigraphy were simultaneously recorded for reference. Radar signals were processed using a sleep/wake decision algorithm integrated with breathing signals and movement features.Results: The average recording time for the analysis was 13.0 (7.0–20.5) h across neonates. Compared with video analyses, the sleep/wake decision algorithm for neonates correctly classified 72.2% of sleep epochs and 80.6% of wake epochs and achieved a final Cohen's kappa coefficient of 0.49 (0.41–0.59) and an overall accuracy of 75.2%.Conclusions: IR-UWB radar can provide considerable accuracy regarding sleep/wake decisions in neonates, and although current performance is not yet sufficient, this study demonstrated the feasibility of its possible use in the NICU for the first time. This unobtrusive, non-contact radar technology is a promising method for monitoring sleep/wake states with vital signs in neonates.

Towards long term monitoring: Seizure detection with reduced electroencephalogram channels

Epilepsy is a prevalent condition characterised by recurrent, unpredictable seizures. The diagnosis of epilepsy is by surface electroencephalography (EEG), a time-consuming and uncomfortable process for patients. The diagnosis of seizures using EEG over a brief monitoring period has variable success, dependent on patient tolerance and seizure frequency. Further, the availability of hospital resources and hardware and software specifications inherently limit the capacity to perform long-term data collection whilst maintaining patient comfort. The application and maintenance of the standard number of electrodes restrict recording time to a maximum of approximately ten days. This limited monitoring period also results in limited data for machine learning models for seizure detection and classification. This work examines the literature on the impact of reduced electrodes on data accuracy and reliability in seizure detection. Here we present two electrode ranking models, demonstrating the decline in seizure detection performance associated with reducing electrodes. We assert the need for further research in electrode reduction to advance solutions toward portable, reliable devices that can simultaneously provide patient comfort, long-term monitoring and contribute to multi-modal patient care solutions.

Intracorporeal Cortical Telemetry as a Step to Automatic Closed-Loop EEG-Based CI Fitting: A Proof of Concept

Electrically evoked auditory potentials have been used to predict auditory thresholds in patients with a cochlear implant (CI). However, with exception of electrically evoked compound action potentials (eCAP), conventional extracorporeal EEG recording devices are still needed. Until now, built-in (intracorporeal) back-telemetry options are limited to eCAPs. Intracorporeal recording of auditory responses beyond the cochlea is still lacking. This study describes the feasibility of obtaining longer latency cortical responses by concatenating interleaved short recording time windows used for eCAP recordings. Extracochlear reference electrodes were dedicated to record cortical responses, while intracochlear electrodes were used for stimulation, enabling intracorporeal telemetry (i.e., without an EEG device) to assess higher cortical processing in CI recipients. Simultaneous extra- and intra-corporeal recordings showed that it is feasible to obtain intracorporeal slow vertex potentials with a CI similar to those obtained by conventional extracorporeal EEG recordings. Our data demonstrate a proof of concept of closed-loop intracorporeal auditory cortical response telemetry (ICT) with a cochlear implant device. This research breaks new ground for next generation CI devices to assess higher cortical neural processing based on acute or continuous EEG telemetry to enable individualized automatic and/or adaptive CI fitting with only a CI.

Home-Based Monitoring of Eating in Adolescents: A Pilot Study

Objectives: To investigate eating episodes in a group of adolescents in their home-setting using wearable electromyography (EMG) and camera, and to evaluate the agreement between the two devices. Approach: Fifteen adolescents (15.5 ± 1.3 years) had a smartphone-assisted wearable-EMG device attached to the jaw to assess chewing features over one evening. EMG outcomes included chewing pace, time, episode count, and mean power. An automated wearable-camera worn on the chest facing outwards recorded four images/minute. The agreement between the camera and the EMG device in detecting eating episodes was evaluated by calculating specificity, sensitivity, and accuracy. Main results: The features of eating episodes identified by EMG throughout the entire recording time were (mean (SD)); chewing pace 1.64 (0.20) Hz, time 10.5 (10.4) minutes, episodes count 56.8 (39.0), and power 32.1% (4.3). The EMG device identified 5.1 (1.8) eating episodes lasting 27:51 (16:14) minutes whereas the cameras indicated 2.4 (2.1) episodes totaling 14:49 (11:18) minutes, showing that the EMG-identified chewing episodes were not all detected by the camera. However, overall accuracy of eating episodes identified ranged from 0.8 to 0.92. Significance: The combination of wearable EMG and camera is a promising tool to investigate eating behaviors in research and clinical-settings.

Miniature Structured Illumination Microscope for in vivo 3D Imaging of Brain Structures with Optical Sectioning

We present a high-resolution miniature, light-weight fluorescence microscope with electrowetting lens and onboard CMOS for high resolution volumetric imaging and structured illumination for rejection of out-of-focus and scattered light. The miniature microscope (SIMscope3D) delivers structured light using a coherent fiber bundle to obtain optical sectioning with an axial resolution of 18 μm. Volumetric imaging of eGFP labeled cells in fixed mouse brain tissue at depths up to 220 μm is demonstrated. The functionality of SIMscope3D to provide background free 3D imaging is shown by recording time series of microglia dynamics in awake mice at depths up to 120 μm in the brain.

The Identification of Electrical Properties of Acupuncture Points for Asthma Diagnosis

The aim of this research is to identify the electrical potential profile on the acupoint betwen healthy people and the patient of asthma. The raw data has taken by recording the electrical potential profile on the acupoints: Feishu, Pishu, and Shenshu from 10 healthy women and the 10 women with asthma attain the age of 20-30 years old based on the second data observation at the Local Government Clinic Kalijudan, Surabaya. Potential profile of the organs were the electrical signals form. It was achieved by the result of electrical potential which was based time recording. Recording time was done for 180 second. The results couldn't be differentiated significantly, so it needs the other signals processing with FFT analyze method with cutting as the data frames. It was done every 5 second. Based on the result of analyzing the amplitude of each frequency group, the significant differences are on the acupoint Shenshu : 0-5 Hz with p= 0.001, on the acupoint Phishu 148-152 Hz with p= 0.010, on the acupoint Feishu for frequency 198-203 Hz with p= 0.004 and on the acuponit Phishu p=0.011, for frequency 348-352 Hz on the acupoint Feishu and Shenshu have both value is p= 0,004 and 398-402 Hz with p=0,009 on the acupoint Phishu. According to the preference, it was found that the electrical potential profile on the acupoints of the healthy people has lower amplitude than the people with asthma. Then, the analyze of electrical potential profile on the acupoints can be used for asthma diagnose.

Fast Image Reconstruction Technique for Parallel Phase-Shifting Digital Holography

For incoherent and coherent digital holography, the parallel phase-shifting technique has been used to reduce the number of exposures required for the phase-shifting technique which eliminates zero-order diffraction and conjugates image components. Although the parallel phase-shifting technique can decrease the hologram recording time, the image interpolations require additional calculation time. In this study, we propose a technique that reduces the calculation time for image interpolations; this technique is based on the convolution theorem. We experimentally verified the proposed technique and compared it with the conventional technique. The proposed technique is more effective for more precise interpolation algorithms because the calculation time does not depend on the size of interpolation kernels.