Banca de DEFESA: ANA PAULA MENDONÇA FERNANDES

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : ANA PAULA MENDONÇA FERNANDES
DATE: 13/02/2025
TIME: 09:00
LOCAL: presencial
TITLE:

Development and validation of a system for analysis neuromuscular and functional physical performance for people with Amyotrophic Lateral Sclerosis 

KEY WORDS:

Surface electromyography; accelerometer; Lateral Sclerosis Amyotrophic; Signal processing.

PAGES: 85
BIG AREA: Ciências da Saúde
AREA: Fisioterapia e Terapia Ocupacional
SUMMARY:

Amyotrophic Lateral Sclerosis (ALS) is a rare, neurodegenerative,
progressive, and severe disease that aggressively impacts the
functionality and quality of life of affected individuals. Characterized by
the degeneration of upper motor neurons (UMN) and lower motor
neurons (LMN), ALS can result in complete motor paralysis. The disease
imposes significant burdens on economic, social, emotional, and
familial aspects, creating substantial challenges for patients and
caregivers alike. Its rapid and variable progression adds complexity to
both diagnosis and personalized care.
The analysis of surface electromyography (SEMG) signals and
accelerometry (ACC) is crucial for early diagnosis and therapeutic
planning. However, the high cost of movement analysis devices and the
difficulty in classifying neuromuscular patterns limit access to this
technology, particularly in public health systems such as the Brazilian
Unified Health System (SUS).
This project aims to develop and validate a low-cost, accessible system
capable of collecting, processing, and analyzing SEMG and ACC signals
in real time. The system is designed to assist in diagnosis, exercise
prescription, and the precise monitoring of disease progression.
Currently, the project is at Technology Readiness Level 6, with critical
functions demonstrated in a relevant environment, leveraging
accessible technologies and innovative data analysis methods.
The system validation included steps such as bench tests and pilot
studies with four healthy individuals, where both the developed device
and the real-time processing code were validated. The data collected for
device validation were analyzed using statistical tests, including the
intraclass correlation coefficient (ICC), Bland-Altman analysis, and
energy ratio, with results demonstrating high consistency, agreement,
and correspondence between methods. For real-time code validation,
the raw and processed signals from the device were evaluated using
Pearson correlation, linear regression, and the SPM1D test. The results
indicated a strong linear correlation (r > 0.96), no statistically significant
differences (p > 0.05), and regression coefficients close to 1, with high
determination coefficients (R2 > 0.92).This study introduces an
innovative and accessible methodology that integrates advanced
monitoring and data analysis technologies, such as EMG and ACC, to
support diagnosis, monitor disease progression, and establish
personalized therapeutic goals for individuals with ALS. By reducing
costs for public health systems and providing valuable data for clinical
research, this low-cost approach has the potential to improve
accessibility. Its precision in neuromuscular signal analysis allows for
early diagnosis, continuous monitoring, and effective, personalized
therapeutic management across different levels of healthcare.

 

COMMITTEE MEMBERS:
Presidente - 2179208 - ANA RAQUEL RODRIGUES LINDQUIST
Interna - 2374822 - FABRICIA AZEVEDO DA COSTA CAVALCANTI
Externo à Instituição - FELIPE RICARDO DOS SANTOS FERNANDES