Adaptive and Wireless Recordings of Electrophysiological Signals during Concurrent Magnetic Resonance Imaging
A Single-Scan Inhomogeneity-Tolerant NMR Method for High-Resolution 2D J-Resolved Spectroscopy
2D homonuclear J-resolved NMR spectroscopy has been widely applied to molecular conformational elucidation, metabolite analysis and in vivo study. However, conventional 2D J-resolved experiments generally suffer from two intrinsic issues, namely long acquisition duration and magnetic field inhomogeneity. Herein, a general single-scan NMR method, SGEN-J, is proposed to address aforementioned two crucial issues, thus applicable to rapidly detecting biological tissues with intrinsic susceptibility variations and abundant metabolites. Experiments of SGEN-J on various chemical and biological samples were performed to demonstrate its feasibility and effectiveness for molecular structure elucidation, biomedical study, even potential in vivo study.
Micro-coil Design Influences the Spatial Extent of Responses to Intracortical Magnetic Stimulation
Magnetic stimulation from micro-coils has the potential to improve the spatial resolution of cortical stimulation by selectively activating pyramidal neurons while avoiding passing axons. Here, we explored how micro-coil design influences the effectiveness and selectivity with which neurons are activated. Computational modeling and physiological experiments revealed that the use of a sharp bend at the coil tip (V-shaped) enhanced coil selectivity; an additional bend provided even higher selectivity. The use of a second loop enhanced coil strength. Our results suggest that further optimization of coil design may help to enhance both the strength and selectivity of future coil designs.
A Machine Learning Shock Decision Algorithm for use during Piston-driven Chest Compressions
Cardiopulmonary resuscitation (CPR) therapy provides oxygen to the vital organs during cardiac arrest. An accurate heart rhythm analysis during piston-driven mechanical chest compressions would avoid interruptions in CPR therapy. We developed a rhythm analysis algorithm that combines adaptive filtering to remove compression artifacts from the electrocardiogram, multiresolution stationary wavelet transform (SWT) analysis for feature extraction, and a gaussian support vector machine (SVM) classifier for the shock/no-shock decision. Our results show that the heart rhythm can be accurately diagnosed during mechanical compressions, avoiding interruptions in CPR that compromise perfusion of the vital organs.
In vivo Visualization of Vasculature in Adult Zebrafish by using High-Frequency Ultrafast Ultrasound Imaging
Zebrafish has recently become a crucial animal model for studying human diseases. However, when a zebrafish matures completely, its body loses transparency, making conventional optical imaging techniques difficult for visualizing the vessels. In the present study, high-frequency (40-MHz) micro-Doppler imaging (HFμDI) based on ultrafast ultrasound imaging was proposed for adult zebrafish dorsal vascular mapping in vivo. Blood flow signals were extracted using an eigen-based clutter filter. Blood vessels were clearly observed in 2D and 3D HFμDI. The minimal diameter of vessel can be detected was 36 μm. The maximum flow velocity range was approximately 3–4 mm/s on the dorsal vessels.
Wearable Devices for Precision Medicine and Health State Monitoring
Wearable technologies will play an important role in advancing precision medicine by enabling measurement of clinically-relevant parameters that define an individual’s health state. The lifestyle and fitness markets have provided the driving force for the development of a broad range of wearable technologies that can be adapted for use in healthcare. Here we review existing technologies currently used for measurement of the four primary vital signs along with other clinically-relevant parameters. We review the relevant physiology that defines the measurement needs, and evaluate the different methods of signal transduction and measurement modalities for use in healthcare.
Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects
By combining medical imaging data (CT and MRI) with respiratory computer simulations, we create a powerful tool to correlate structure and function abnormalities in asthma subjects. Segmental volume defect percentages (SVDP) measured from hyperpolarized 3He MRI and CT images are used to define resistance-based boundary conditions for the gas flow models. Subjects with central airway remodeling had larger airway resistances, conducting airway pressure gradients, and secondary flow motion compared to the healthy subjects.