Quantifying cardiorespiratory thorax movement with motion capture and deconvolution

Unobtrusive sensing is a growing aspect in the field of biomedical engineering. While many modalities exist, a large fraction of methods ultimately relies on the analysis of thoracic movement. To quantify cardiorespiratory induced thorax movement with spatial resolution, an approach using high-performance motion capture, electrocardiography and deconvolution is presented. In three healthy adults, motion amplitudes are estimated that correspond to values reported in the literature. Moreover, two-dimensional mappings are created that exhibit physiological meaningful relationships. Finally, the analysis of waveform data obtained via deconvolution shows plausible pulse transit behavior

Режимы лазерного восстановления оксида графена

Обработка светом (фотолитография) хорошо зарекомендовала себя в твердотельной электронике и на данный момент играет важную роль в микроэлектронной промышленности. С данной точки зрения представляется научный интерес работы по возможностям модификации пленок ОГ для получения гибкой, биосовместимой и "зеленой" электроникиPhotolithography is a powerfull instrument for designing a solid state electronics. Today is plays an important role in the microelectronic industry. Scientific interest of this work is on the possibilities of modifications of the graphene oxide film to obtain flexibility, biocompatible and "green" electronic

Prediction of tumor deformation for Image Guided Radiation Therapy

Radiation therapy uses ionizing radiation to damage the DNA of cancerous cells. It is extensively used for curative and palliative treatment and constitutes more than 50% of all lung cancer treatment modalities. Precise knowledge of the shape and location of the tumor is mandatory for effective Intensity Modulated Radiation Therapy. The task of accurately targeting the tumor is especially challenging when the tumor's location and shape is influenced by respiratory motion (e.g. tumors on the lung, breast, etc.). In this work, we develop an image-processing technique that assists the radiation therapy planning process, by exploiting computed tomography images to estimate the shape and position of the tumor over the breathing cycle. To validate the proposed algorithm for Deformable Image Registration, benchmark datasets provided to the community by a research group at The University of Texas M. D. Anderson Cancer Center (http://www.dir-lab.com/) were used. Numerical evaluation illustrates that the proposed algorithm outperforms all algorithms tested on the benchmark dataset for a majority of the cases. To advance the field of on-line tumor tracking from rigid motion towards deformation, time-varying Fourier Descriptors were used to learn a deformation model. Combining these two techniques we further developed a Semi-Automated Contouring software and evaluated it with real patient data provided by the Roswell Park Cancer Institute

Quantification of Respiratory Sinus Arrhythmia with High-Framerate Electrical Impedance Tomography

Respiratory Sinus Arrhythmia, the variation in the heart rate synchronized with the breathing cycle, forms an interconnection between cardiac-related and respiratory-related signals. It can be used by itself for diagnostic purposes, or by exploiting the redundancies it creates, for example by extracting respiratory rate from an electrocardiogram (ECG). To perform quantitative analysis and patient specific modeling, however, simultaneous information about ventilation as well as cardiac activity needs to be recorded and analyzed. The recent advent of medically approved Electrical Impedance Tomography (EIT) devices capable of recording up to 50 frames per second facilitates the application of this technology. This paper presents the automated selection of a cardiac-related signal from EIT data and quantitative analysis of this signal. It is demonstrated that beat-to-beat intervals can be extracted with a median absolute error below 20 ms. A comparison between ECG and EIT data shows a variation in peak delay time that requires further analysis. Finally, the known coupling of heart rate variability and tidal volume can be shown and quantified using global impedance as a surrogate for tidal volume