Optical biosensing is being actively investigated for minimally-invasive monitoring of key biomarkers both $in~ vitro$ and $in~ vivo$ . However, typical benchtop instruments are not portable and are not well suited to high-throughput, real-time analysis. This paper presents a versatile multichannel instrument for measurement of emission intensity and lifetime values arising from luminescent biosensor materials. A detailed design description of the opto-electronic hardware as well as the control software is provided, elaborating a flexible, user-configurable system that may be customized or duplicated for a wide range of applications. This article presents experimental measurements that prove the $in~ vitro$ and $in ~vivo$ functionality of the system. Such tools may be adopted for many research and development purposes, including evaluation of new biosensor materials, and may also serve as prototypes for future miniaturized handheld or wearable devices.

Rapid in vitro evaluation of sensors and biosensors in conditions replicating in vivo physiological environments is desirable for improved preclinical evaluation. A two-part testing system with buffer exchange and simultaneous control of temperature, gas, and soluble analyte was developed. The system includes programmable incubators, peristaltic pumps, and gas and buffer metering subsystems. A reusable flow cell with windows for optical interrogation was developed to house multiple biosensor samples within the testing system where all of them can be examined simultaneously. The verification of the system environmental outputs indicates the accuracy within absolute errors of $1.59 ~\mu \text{M}$ for oxygen and 5.5 mg/dL for glucose, and relative standard deviations of oxygen and glucose of 2.01% and 2.16%, respectively, at steady state, making it well suited for in vitro evaluation of biosensors. The evaluation of the system with model phosphorescence oxygen and glucose biosensors demonstrates the system’s capabilities in replicating several relevant parameters of the in vivo environment. This system, and future iterations of it, can increase the rate and throughput for testing biosensors, accelerating translation from the benchtop to the bedside in the future.

This paper presents a real-time functional decomposition adaptive algorithm for the optimal sampling of the interferometric signal in Swept-Source Optical Coherence Tomography imaging systems, which completely eliminates the input signal dependent nonlinearities that are problematic in current state-of-the-art OCT realizations that use interpolation and resampling. The proposed adaptive calibration algorithm uses the Kalman approach to estimate the wavenumber index parameter ${k}$ from the Mach-Zender Interferometer signal which is then applied to an adaptive level crossing sampler to generate a sampling clock that ${k}$ -linearizes the data on real-time during the sampling process. Such a system implements an artifact-free realization of the technology removing the need for classical interpolation and resampling. The new real-time linearization scheme has the additional capability of increasing the imaging acquisition speed by 10X while providing robustness to noise, properties that are demonstrated through mathematical analysis and simulation results throughout the paper.

Embryo transfer (ET) and in vitro fertilization (IVF) are increasing in use by dairy producers as a means to breed their animals as these assisted reproductive techniques can optimize the genetics of the dairy breed or enable “beef on dairy” programs to increase the profitability of the dairy. Due to the advantages of ET and IVF, it is anticipated that their use will continue to increase despite the status of underwhelmingly low pregnancy outcomes. Pregnancy rates of bovine ET/IVF remain below 56%, with many dairy producers implementing beef on dairy programs reporting pregnancy to be lower than 23%. The inability to objectively evaluate embryo health prior to transfer into a recipient is a contributing factor to this problem as 20% of transferred embryos are inviable at the time of transfer and have little chance of establishing a pregnancy. The objective of this research was to evaluate bovine embryo real-time morphokinetic activity based on 30 s video recordings of day 7.5 morulas and correlate morphokinetic activity to developmental outcomes. Eighty-eight embryos were recorded in standard embryo culture conditions with an SMZ-1000 Stereo zoom microscope and TE-300 Nikon inverted microscope. The difference in the embryo’s morphokinetic activity was measured frame-by-frame and correlated to embryo hatching outcomes. It was found that embryos with lower morphokinetic activity demonstrated higher hatching rates and developmental outcomes, suggesting measurement of embryo morphokinetic activity is a noninvasive and non-subjective method to evaluate embryo competency prior to transfer and can be used to improve the reproductive efficiency and profitability of IVF/ET of dairy cattle.

In this paper, we present a real-time instantaneous phase estimation technique for the calibration of swept source optical coherence tomography (SS-OCT) systems. The proposed algorithm is able to accurately estimate both the amplitude and phase content of a swept source signal. The results are robust in the presence of substantial noise. Furthermore, the resulting phase profile is readily unwrapped, allowing for the generation of a k-linear sampling clock by means of a simple comparison step, which enables the SS-OCT system operator to determine the required number of points for accurate image reconstruction without the need for MZI path length modification. Our Simulations exhibit equivalent results with Hilbert transform based calibration techniques and low computational time rendering it suitable for real time applications.

This research design delves into a groundbreaking study that highlights the innovative use of wearables and deep reinforcement learning to enhance emotional well-being and manage stress. With a focus on leveraging wearable sensor technology, specifically the Empatica EmbracePlus device, the research unfolds at the intersection of emotional intelligence (EQ) augmentation, emotion recognition and intentional EQ practice. Leveraging the potential of wearables, participants were selected from the Master of Engineering Technical Management (METM) program at Texas A&M University, based on their involvement in studies related to emotional intelligence and management. The objective is to investigate personalized strategies for improving emotional well-being through three interconnected aims: a) exploring the relationship between emotional intelligence, stress management, and physiological indicators using wearable technology; b) evaluating the effectiveness of intentional EQ practices in improving emotional well-being and reducing stress; and c) utilizing machine learning to optimize the impact of intentional practices on overall well-being. This approach underscores the potential of wearables to illuminate the physiological responses accompanying mindfulness practices, offering fresh insights into the dynamic relationship between emotional intelligence, stress management, and intentional well-being enhancement.