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    Design and Development of a Mobility Recognition System in PD Patients for Tele-rehabilitation

    , M.Sc. Thesis Sharif University of Technology Mohammadi Nasrabadi, Amin (Author) ; Behzadipour, Saeed (Supervisor) ; Alibiglou, Laila (Co-Supervisor)
    Abstract
    Parkinson's disease is a neurodegenerative disorder that affects motor functions. Performing mobility exercises help patients slowing down the progression of the illness and improving symptoms of the disease. Assessment and evaluation of activities of mobility exercises are critical for any treatment program particularly in tele-rehabilitation system. The purpose of the current study is to design an affordable and accurate wearable device with inertial measurement units (IMUs) for mobility activity recognition in Parkinson’s patients. The optimum number and arrangement (i.e. configuration) were found to minimize the cost while maintaining a fair accuracy. The activity recognition was... 

    A Sensor-Based Approach to Sign Language Recognition Using Hidden Markov Model

    , M.Sc. Thesis Sharif University of Technology Bayatmanesh, Saeid (Author) ; Shamsollahi, Mohammad Bagher (Supervisor) ; Vossoughi, Gholamreza (Co-Advisor)
    Abstract
    Sign language is the first and most important communication way between hearing impaired community, but the biggest issue within them is simply that most of them can't effectively communicate with most hearing people. If sign language can be translated to text or speech automatically, deaf people will be able to communicate with all the others. Sign language contains more than six thousands signs, in which, deaf people make use of hands and sometimes facial expression to do that. So far, three main approaches have been used to recognize posture and position of hand: 1) vision-based: using images of 1-3 camera(s), based on image processing; 2) glove-based: using sensory glove(s) and motion... 

    An Automatic Persian Sign Language Recognition System Using Sensory Glove

    , M.Sc. Thesis Sharif University of Technology Habibipour, Kamyar (Author) ; Vossoughi, Gholamreza (Supervisor) ; Shamsollahi, Mohammad Bagher (Co-Advisor)
    Abstract
    Sign language is the main medium of communication for mute and deaf people. Unfortunately most hearing people do not understand this language. This fact causes communication difficulties for hearing impaired people and negatively affects their social life. This problem motivates researchers to develop speaking aids and helps deaf people to communicate with hearing people. Sign language includes concurrent combination of hand shapes, orientation and movements of the hands, arms or body, and facial expressions which make the character and word recognition a challenging task. Generally there are two fields of study in sign language recognition based on measuring devices: 1- camera based 2-... 

    Auv Parameter Estimation Using Sensor Data Fusion Methods Based on Nonlinear Filters

    , M.Sc. Thesis Sharif University of Technology Ghanipoor, Farhad (Author) ; Alasty, Aria (Supervisor) ; Salarieh, Hassan (Co-Supervisor)
    Abstract
    Nowadays, application of AUVs in marine missions is a crucial research field. To reach a fully automated underwater vehicle, it should suitably be designed, controlled, navigated and its fault is detected immediately. An Identified model of AUV is usable for all of these goals. Thus, in this project, parameters of an appropriate dynamic model of AUV is estimated using augmented state space method and TUKF.By investigating possibility of parameter estimation of 6-DOF model and sub models in different cases, a scenario for estimation of cruise, steering and diving sub model parameters of AUV, using output of DVL and Gyroscope is proposed. Furthermore, planar misalignment between DVL and IMU,... 

    Development of a Classifier for the Human Activity Recognition System of PD Patients Using Biomechanical Features of Motion

    , M.Sc. Thesis Sharif University of Technology Ejtehadi, Mehdi (Author) ; Behzadipour, Saeed (Supervisor)
    Abstract
    Parkinson’s disease (PD) is a neurodegenerative disorder and during the last few years considerable measures have been taken to rehabilitate its patients. To prevent the disorder from deteriorating and to control its progress, patients have to undergo some therapy sessions that incorporate some mobility exercises e.g. walking, sitting up and down, and etc. Since transporting the patients to the clinical centers is too burdensome, growing attention is drawn towards telerehabilitation. To this end, DMRCINT has developed a telerehab system for PD patients. This system is an intelligent classifier that uses features of linear acceleration and angular velocity signals to detect the activity that... 

    Development of a Human Activity Recognition System with an Adaptive Neuro-Fuzzy Post-Processing for the Lee Silverman Voice Treatment-BIG and Functional Activities

    , M.Sc. Thesis Sharif University of Technology Partovi, Ehsan (Author) ; Behzadipour, Saeed (Supervisor)
    Abstract
    Human Activity Recognition (HAR) has had tremendous improvements in the field of elderly monitoring and telerehabilitation. An anchor point for HAR systems in telerehabilitation is supervising rehabilitative excercises. For Parkinson’s disease (PD) patients, a group of rehabilitative activities, known as Lee Silverman Voice Treatment-BIG, or LSVT-BIG, have shown to be effective in improving motor performance. Similar to any rehabilitative measure, delivering these activities requires the supervision of an expert or clinician, so that the patient receives proper feedbacks. HAR systems can replace human experts. They can recognize activities and provide the user with proper feedback. HAR... 

    Design and Implementation of a Motion Analysis Algorithm based on Inertia-kinect Sensors for Step Length Estimation

    , M.Sc. Thesis Sharif University of Technology Abbasi, Javad (Author) ; Salarieh, Hassan (Supervisor) ; Alasty, Aria (Co-Supervisor)
    Abstract
    Motion capture is a process that movements of living organisms like human or objects are captured and the results are processed for the desired applications. This applications are in rehabilation, sports, film industry and etc. There are many techniques and instruments for motion capture that optical cameras are the most accurate ones. But this cameras are high cost and limited to labs. Some sensors like IMUs and recently, Kinect cameras have been considered by many researchers because these are low cost and easy to use. But problems like bias, accumulated error and occlusion make them to looking for improvments. Fusion algorithms are one of the best methods that help to use from each... 

    Toward calibration of low-precision MEMS IMU using a nonlinear model and TUKF

    , Article IEEE Sensors Journal ; Volume 20, Issue 8 , 2020 , Pages 4131-4138 Ghanipoor, F ; Hashemi, M ; Salarieh, H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    MEMS-IMUs have an extensive application in multifarious studies, as well as industrial and commercial areas. It is crucial to diminish their intrinsic errors in a suitable calibration procedure. In this paper, a novel calibration procedure was proposed for Inertial Measurement Units (IMUs) on a turntable. A general nonlinear model of the IMU output including the effects of bias, scale factor, misalignment, and lever arm was derived. Transformed Unscented Kalman Filter (TUKF) was utilized to perform the estimation of error parameters for gyroscopes and accelerometers. The calibration maneuvers were applied using a tri-axis turntable to create input signals. In addition, assuming the sensors... 

    Model identification of a Marine robot in presence of IMU-DVL misalignment using TUKF

    , Article Ocean Engineering ; Volume 206 , 2020 Ghanipoor, F ; Alasty, A ; Salarieh, H ; Hashemi, M ; Shahbazi, M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    In today's world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According... 

    Decoupled scalar approach for aircraft angular motion estimation using a gyro-free inertial measurement unit

    , Article Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME ; Volume 141, Issue 12 , 2019 ; 00220434 (ISSN) Dehghan Manshadi, A ; Saghafi, F ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2019
    Abstract
    In-flight aircraft angular motion estimation based on an all-accelerometers inertial measurement unit (IMU) is investigated in this study. The relative acceleration equation as the representative of a rigid-body kinematics is manipulated to present the state and measurement equations of the aircraft dynamics. A decoupled scalar form (DSF) of the system equations, as a free-singularity problem, is derived. Mathematical modeling and simulation of an aircraft dynamics, equipped with an all-accelerometers IMU, are employed to prepare measurement data. Taking into account the modeling of accelerometer error, the measurement data have been simulated as a real condition. Three extended Kalman... 

    How to synchronize and register an optical-inertial tracking system

    , Article Applied Mechanics and Materials ; Volume 332 , 2013 , Pages 130-136 ; 16609336 (ISSN) ; 9783037857335 (ISBN) Soroush, A ; Akbar, M ; Farahmand, F ; Sharif University of Technology
    2013
    Abstract
    Multi-sensor tracking is widely used for augmentation of tracking accuracy using data fusion. A basic requirement for such applications is the real time temporal synchronization and spatial registration of two sensory data. In this study a new method for time and space coordination of two tracking sensor measurements has been presented. For spatial registration we used a body coordinate system and then applied the effect of the level arm. The time synchronization was done based on least mean square (LMS) error method. This method was implemented to synchronize the position and orientation of an object using Inertial (1IMU) and Optical (Optotrak) tracking systems. The results of synchronized...