Tamburini, Paola
  
(2018)
Use of non-linear metrics for the characterization of human motion: methodological constraints and functional interpretation, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. 
 Dottorato di ricerca in 
Ingegneria biomedica, elettrica e dei sistemi, 30 Ciclo. DOI 10.6092/unibo/amsdottorato/8288.
  
 
  
  
        
        
        
  
  
  
  
  
  
  
    
  
    
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      Abstract
      This PhD Thesis analysed the numerous and various metrics proposed for the quantification of motor stability in human motion analysis.
Human motion analysis points to provide quantitative measures for the objective characterization of specific motion patterns, such as gait, aiming to support evidence based clinical decision. 
In recent years, the significant interest in finding effective methods for the quantification and prediction of fall risk in elderly subjects led to a proliferation of novel metrics.
The majority of them originates from the theory of dynamical systems and has been used in robotics. Thus, they have been applied to gait analysis data, assuming similar interpretability in terms of motor control, resulting in a large amount of published studies, often leading to not conclusive and sometimes contrasting results. This can be related to the lack of a methodological reference for the appropriate experimental assessment and implementation of these metrics (e.g. target variables, number of strides, sampling frequency, implementation parameters) and of a clear functional correlate, establishing the relationship between the metrics and their possible clinical interpretation.
Aiming to assess gait stability as an expression of motor control, both intrinsic properties of the human body and their relationship with the specific movement pattern must be taken into account. To this purpose, non-linear metrics were analysed (i.e. Lyapunov Exponent, Recurrence Quantification Analysis, Harmonic Ratio, and Multiscale Sample Entropy) describing different aspects of gait pattern related to the motor control system.
The aim of this PhD dissertation was to improve the understanding of these non-linear metrics, providing evidence for the definition of methodological references for their experimental assessment, implementation, and possible clinical interpretation in specific conditions.
	Even though not exhaustive, the results provide an essential set of basic knowledge for the definition of a reference for the reliable use and interpretation of these non-linear metrics.
     
    
      Abstract
      This PhD Thesis analysed the numerous and various metrics proposed for the quantification of motor stability in human motion analysis.
Human motion analysis points to provide quantitative measures for the objective characterization of specific motion patterns, such as gait, aiming to support evidence based clinical decision. 
In recent years, the significant interest in finding effective methods for the quantification and prediction of fall risk in elderly subjects led to a proliferation of novel metrics.
The majority of them originates from the theory of dynamical systems and has been used in robotics. Thus, they have been applied to gait analysis data, assuming similar interpretability in terms of motor control, resulting in a large amount of published studies, often leading to not conclusive and sometimes contrasting results. This can be related to the lack of a methodological reference for the appropriate experimental assessment and implementation of these metrics (e.g. target variables, number of strides, sampling frequency, implementation parameters) and of a clear functional correlate, establishing the relationship between the metrics and their possible clinical interpretation.
Aiming to assess gait stability as an expression of motor control, both intrinsic properties of the human body and their relationship with the specific movement pattern must be taken into account. To this purpose, non-linear metrics were analysed (i.e. Lyapunov Exponent, Recurrence Quantification Analysis, Harmonic Ratio, and Multiscale Sample Entropy) describing different aspects of gait pattern related to the motor control system.
The aim of this PhD dissertation was to improve the understanding of these non-linear metrics, providing evidence for the definition of methodological references for their experimental assessment, implementation, and possible clinical interpretation in specific conditions.
	Even though not exhaustive, the results provide an essential set of basic knowledge for the definition of a reference for the reliable use and interpretation of these non-linear metrics.
     
  
  
    
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Tamburini, Paola
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          30
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Gait analysis, non-linear indexes, motor control, methodology, functional interpretation
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.6092/unibo/amsdottorato/8288
          
        
      
        
          Data di discussione
          4 Maggio 2018
          
        
      
      URI
      
      
     
   
  
    Altri metadati
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Tamburini, Paola
          
        
      
        
          Supervisore
          
          
        
      
        
          Co-supervisore
          
          
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          30
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Gait analysis, non-linear indexes, motor control, methodology, functional interpretation
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.6092/unibo/amsdottorato/8288
          
        
      
        
          Data di discussione
          4 Maggio 2018
          
        
      
      URI
      
      
     
   
  
  
  
  
  
    
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