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    Measuring and Remote Monitoring of Vital Signs

    , M.Sc. Thesis Sharif University of Technology Mozaffari, Ali (Author) ; Atarodi, Mojtaba (Supervisor)
    Abstract
    With the increasing number of elderly people as a proportion of the total population in the world and the aging of the world's population, the need for medical care has increased. On the one hand, most of the elderly population have chronic diseases such as diabetes, hypertension, etc., which do not require hospitalization in healthcare centers, but they need to monitor their health status. Given the progress of technology, the measurement of vital body signals has been made possible with non-invasive methods. In this thesis, an attempt has been made to provide a wearable and portable solution for the measurement, monitoring, and collection of vital signals based on the Internet of Things... 

    Non-invasive and Continuous Blood Pressure Measurement Using Pulse Transit Time without Cuff Requirement

    , M.Sc. Thesis Sharif University of Technology Esmaili Dastjerdi, Amir Hossein (Author) ; Shabany, Mahdi (Supervisor)
    Abstract
    This thesis addresses cuff-less blood pressure (BP) estimation, for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimation with the aid of the processing of vital signals. Both with and without calibration per person approaches for BP estimation are considered. A data acquisition hardware is designed for high-resolution sampling of phonocardiogram (PCG), Photoplethysmogram (PPG) and electrocardiogram (ECG). Using these signals, pulse transit time (PTT) and pulse arrival time (PAT) indexes, which would be used for BP estimation with calibration, are extracted. For the BP estimator model using the calibration, A nonlinear model based on PTT or PAT, via modeling the vessels... 

    ECG denoising using parameters of ECG dynamical model as the states of an extended Kalman filter

    , Article 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, 23 August 2007 through 26 August 2007 ; 2007 , Pages 2548-2551 ; 05891019 (ISSN) ; 1424407885 (ISBN); 9781424407880 (ISBN) Sayadi, O ; Sameni, R ; Shamsollahi, M. B ; Sharif University of Technology
    2007
    Abstract
    In this paper an efficient Altering procedure based on the Extended Kalman Filter (EKF) has been proposed. The method is based on a modified nonlinear dynamic model, previously introduced for the generation of synthetic ECG signals. We have suggested simple dynamics as the governing equations for the model parameters. Since we have not any observation for these new state variables, they are considered as hidden states. Quantitative evaluation of the proposed algorithm on the MIT-BIH signals shows that an average SNR improvement of 12 dB is achieved for a signal of -5 dB. The results show improved output SNRs compared to the EKF outputs in the absence of these new dynamics. © 2007 IEEE  

    Heart Motion Measurement and Prediction for Robotic Assisted Beating Heart Surgery

    , Ph.D. Dissertation Sharif University of Technology Mansouri, Saeed (Author) ; Farahmand, Farzam (Supervisor) ; Vossoughi, Gholamreza (Supervisor)
    Abstract
    An essential requirement for performing robotic assisted surgery on a freely beating heart is a prediction algorithm which can estimate the future heart trajectory with a high accuracy in a long horizon. The main objective of this research was measurement and prediction of the heart motion for robotic assisted beating heart surgery. In this study, first the feasibility of a stereo infrared tracking system for measuring the free beating heart motion was investigated by experiments on a heart motion simulator. Simulator experiments revealed a high tracking accuracy when the capturing times were synchronized and the tracker pointed at the target from an appropriate distance.Then, the heart... 

    A comprehensive multimodality heart motion prediction algorithm for robotic-assisted beating heart surgery

    , Article International Journal of Medical Robotics and Computer Assisted Surgery ; Volume 15, Issue 2 , 2019 ; 14785951 (ISSN) Mansouri, S ; Farahmand, F ; Vossoughi, G ; Alizadeh Ghavidel, A ; Sharif University of Technology
    John Wiley and Sons Ltd  2019
    Abstract
    Background: An essential requirement for performing robotic-assisted surgery on a freely beating heart is a prediction algorithm that can estimate the future heart trajectory. Method: Heart motion, respiratory volume (RV) and electrocardiogram (ECG) signal were measured from two dogs during thoracotomy surgery. A comprehensive multimodality prediction algorithm was developed based on the multivariate autoregressive model to incorporate the heart trajectory and cardiorespiratory data with multiple inherent measurement rates explicitly. Results: Experimental results indicated strong relationships between the dominant frequencies of heart motion with RV and ECG. The prediction algorithm...