Performance evaluation of motion capture systems for respiratory function assessment

Motion capture (MoCap) is the process of recording the movement of objects or people. Currently, within a large number of MoCap technologies, the most affordable and accurate analysis of the musculoskeletal system can be performed by using systems based on the tracking of markers positioned on specific body landmarks. Scientific literature outlines a validation issue for results from the same subject examined by different laboratories: to ensure a correct diagnosis, standard methods are required for the evaluation of the performances of measurement systems so that values and uncertainties of kinematics and dynamics quantities can be evaluated with repeatability and reproducibility. No established procedure based on metrological tools have been developed for a fast, in-situ evaluation of MoCap systems for small movement detection and breathing assessment purposes. Moreover, no volumetric platform have been developed to test performances of MoCap system in the calculation of volumes and volume changes, neither in static and dynamic conditions. So, the developing of a method for calibration assessment and measurement uncertainty evaluation of MoCap system applied to the movement as well as mechanical ventilation analysis should be useful to propose a new procedure to establish a standard for quality for mechanical measurements performed in movement analysis laboratories. Moreover, the exploration of alternative solutions for analysis of breathing with optical technologies is needed. The application of MoCap technology to extend the potentiality of currently available instruments to better understand the biomechanics of breathing in healthy subjects, pathological ones and in new populations like elite athletes, during exercise at the different level of effort and with dysfunctional breathing symptoms could be interesting to improve the knowledge of human physiology. Despite some attempts have been proposed, an easy-to-use software for the analysis of breathing values and kinematical parameters should improve the use of that tools by clinicians and researchers in general. The proposed procedure and software will be available for care centres of movement analysis and mechanical ventilation analysis as well as institutions where MoCap systems are used. To overcome some limitations of MoCap systems in some scenarios and in the environments in which the collection of a large number of markers are complicated for a prolonged time (i.e., sports activities), wearable textiles may be used to collect vital signs, breathing parameters and biomechanics in general. In the last years, the growing interest in smart textiles for medical applications is driven by the aim to increase the mobility of subjects who need a continuous monitoring of physiological parameters. Smart textiles can embed one or more sensors to monitor various mechanical, thermal and chemical parameters (e.g., strain, temperature, displacement, oxygen blood saturation). The lung volume and breathing temporal parameters (i.e., breathing rate, inspiratory/expiratory times and ratio) can be obtained by means of devices that measure flowrate at the mouth (i.e., portable pneumotachometers, flow sensors), requiring the use of a facemask. However, no information about the biomechanics of the breathing can be obtained. Since the chest and the abdomen show movements related to the alternation of inspiration and expiration, temporal and kinematical parameters of the breathing can be potentially evaluated by registering these movements. Wearables based upon the strain evaluation can be potentially employed at this scope. Within the large numbers of technologies can be adopted, during the last decades, the use of fiber optic-based sensors (FOSs) has been gaining acceptance in the development of systems to monitor respiration. Literature shows a lack of investigation in the placement of the sensors, as well as a limited number of trials aiming at validating the measurements performed by the smart textiles. The specific aims of this Thesis dissertation are: 1. Design, development, and test of a mechatronic platform for in-situ test of MoCap systems; 2. Test of marker-based systems for movement analysis in the range of small movements with the developed platform; 3. Design, development, and test of methods to ensure accurate measurements of breathing volumes and features from tridimensional coordinates collected by MoCap systems, in a range of application; 4. Design, development, and test of a wearable solution to collect breathing parameters, and the relative algorithms to extract breathing features. This Thesis is structured in five chapters briefly described below to report the background, methodology and experimental results in accordance to the specific aims. Chapter I presents an in-depth analysis of the characteristics of MoCap system used in the musculo-skeletal system evaluation. By the analysis of the literature, the optoelectronic plethysmography seems to be a promising technology for the investigation not only of breathing parameters (as temporal parameters and lung volumes) but also of the biomechanics of breathing. The biomechanics of the chest wall during exercise can highlight breathing strategy and pathologies impossible to be detected with flow-based traditional technologies (i.e. spirometry). Moreover, there is the need of an instrument for the fast volume calibration for MoCap as well as for the assessment of the performance among the time of MoCap used in the field of breathing assessment. A the end of the Chapter a brief summary of wearable solutions for breathing monitoring have been also presented, highlighting the major limitations of available systems have been used in this promising field. Chapter II will be devoted to the description of the design, metrological evaluation, and test on a motion laboratory of a fully programmable mechatronic platform. This platform (two versions of the platform will be described) allows delivering known displacement and volume to MoCap system. Its metrological characterization will be described as well as the motion control strategy adopted to optimize its performances. The results of a calibration of one MoCap performed by the use of the platform will be also reported and discussed. In the third chapter, the description of all the methods used to compute volumes from tridimensional coordinates will be described and reviewed. Then, three new methods will be described and the performances of these methods will be discussed against a spirometry data collected on healthy subjects. Moreover, a paragraph is completely devoted to new approaches in the evaluation of breathing in sports science including the description of an ad-hoc developed software for the breathing analysis. Lastly, the comparison between full and reduced markers protocols in the breathing volumes and kinematics evaluation will be presented as well as the result of the application of MoCap system and the developed software in the non-invasive investigation of kinematics and breathing volumes in the dysfunctional breather. The fourth chapter will be devoted to the wearable technologies for the respiratory monitoring. The first section will describe the actual technologies based on the optical fibers used in this field; in the next sections different design of a smart textile design and made to measure vital signs will be described and its performances in the measure of breathing rate, temporal features, volume and compartmental volumes as well as heart rate in harsh environments will be described. Lastly, the fifth chapter will summarize the main findings of this dissertation as well as the limitations and areas of future development and application of the methods proposed in this research.