Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

Muraccini, Marco (2020) Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria biomedica, elettrica e dei sistemi, 32 Ciclo.
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Abstract

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Muraccini, Marco
Supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
movement analysis, wearable sensors, magnetometer calibration, Earth’s magnetic field mapping, kinematic analysis
URN:NBN
Data di discussione
27 Marzo 2020
URI

Altri metadati

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