ETD system

Electronic theses and dissertations repository

 

Tesi etd-09222019-124941


Thesis type
Tesi di laurea magistrale
Author
ALBANA, SONIA
email address
sonia.albana@gmail.com
URN
etd-09222019-124941
Title
Pathological gait event detection for application with a lower limb exoskeleton: Design and development of an optimized wavelet-based strategy using Genetic Algorithms
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
BIONICS ENGINEERING
Commissione
relatore Prof. Vitiello, Nicola
relatore Prof.ssa Crea, Simona
tutor Dott. Conti, Roberto
Parole chiave
  • Gait Event Detection
  • Exoskeleton
  • Wavelet Transform
  • Genetic Algorithm
Data inizio appello
11/10/2019;
Consultabilità
secretata d'ufficio
Data di rilascio
11/10/2022
Riassunto analitico
Over the last decade, the employment of robotic exoskeletons in rehabilitation and gait assistance has considerably grown due to their capability to enhance mobility in individuals affected by lower limb impairments. This work provides a methodology for detecting heel strike (HS) timing from hip joint angle signal. The main aim is to enable, in an Active Pelvis Orthosis (APO), the quantitative assessment of the pathological gait, allowing to improve the assistive process and to evaluate the device effectiveness in terms of rehabilitative action. The proposed solution consists of a strategy based on wavelet analysis and is driven by a nature-inspired optimization process. An algorithm performs the Discrete Wavelet Transform, allowing to identify the HS occurrence from the frequency content of the hip joint angle acquired by the sensory system of the APO. Furthermore a Genetic Algorithm is implemented in order to select the optimal wavelet algorithm parameters, guaranteeing an accurate and robust event detection as the gait patterns change. The design and development of the strategy are presented along with its experimental validation with transfemoral amputees performing ground level walking at preferred speeds. The method is benchmarked against the gait event detector currently implemented in the control strategy of the APO.
File