Banca de QUALIFICAÇÃO: LEDYCNARF JANUÁRIO DE HOLANDA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : LEDYCNARF JANUÁRIO DE HOLANDA
DATE: 23/02/2021
TIME: 08:30
LOCAL: Vídeo Conferência
TITLE:

Machine Learning as Control Strategy for Upper Limb Orthosis for People with Amyotrophic Lateral Sclerosis

KEY WORDS:

Orthosis; Motor function; Machine Learning; Amyotrophic lateral sclerosis.

PAGES: 106
BIG AREA: Ciências da Saúde
AREA: Fisioterapia e Terapia Ocupacional
SUMMARY:

Machine Learning Algorithms (AM) have become allies in the development of more accurate and 
precise tools for rehabilitation. In this perspective, new orthoses are being developed to assist in 
rehabilitation to favor autonomy, functionality and self-care. With technological evolution, it was 
possible to add sensors capable of capturing biological signals, such as surface electromyography 
(EMGs) and inertial measurement units (UMIs), in order to analyze the movement of the body 
segment in real time. However, there is a variability in the characteristics of the biological signal, 
especially in people with Amyotrophic Lateral Sclerosis (ALS), whose symptoms are quite
 heterogeneous. Therefore, there is a need for new systems capable of identifying these different
 movement patterns, using AM algorithms. In view of the importance of moving the upper limb (MS)
 for handling objects, performing routine activities and functional independence. Thus, the aim is to
 implement AM algorithm in orthosis of MS and analyze its viability in people with ALS. This orthosis will
 be able to capture the signal from EMGs and UMIs, and classify physiological and pathological
 movement patterns, through AM algorithms, allowing the monitoring and adjustment of movement
 in real time, in order to favor a good motor performance for people with ALS.

BANKING MEMBERS:
Presidente - 2179208 - ANA RAQUEL RODRIGUES LINDQUIST
Interna - 1081828 - CATARINA DE OLIVEIRA SOUSA
Externo à Instituição - ABNER CARDOSO RODRIGUES NETO