Faculdade

Eventos

Seminário do Programa de doutoramento em Engenharia Biomédica do aluno Duarte Miguel dos Santos Nunes Folgado "Analyzing 3D Human Movement using Inertial Sensors: Lessons Learned Working with the Manufacturing Industry"

Ter, 17 janeiro 2023, 16:00 - 17:00
Tipo de evento: 
Seminário
Organizador: 
Departamento de Física
Local do evento: 
Sala de Seminários Nº 213
Localização específica: 
Edifício I

"Analyzing 3D Human Movement using Inertial Sensors: Lessons Learned Working with the Manufacturing Industry"

Abstract: The incoming generation of Operators 4.0 is characterized by qualified operators who work with the support of machines, interact with collaborative robots and advanced systems, and use emerging technologies such as wearable devices and augmented and virtual reality. In line production environments, the movements and actions performed by operators are well-defined and intend to guarantee that workers abide by best practices in productivity and ergonomics. However, repetitive tasks constitute a risk factor for the onset of work-related musculoskeletal disorders and ultimately contribute to absenteeism. Wearables offer means for faster, more accurate, and ubiquitous digitalization of work study, promoting continuous awareness of the balance between productivity and ergonomics. This seminar presents ongoing research on how inertial sensors are being used to study human movement in industrial lines. More specifically, it outlines the hardware, motion tracking and analysis algorithms, laboratory validation studies, and lessons learned so far to make this technology readily and effectively applicable to real scenarios in manufacturing shop floors.

 

Short Biographical Note: Duarte Folgado received his MSc in Biomedical Engineering in 2015 from the NOVA School of Science and Technology. He is currently a PhD Candidate in Biomedical Engineering. Since 2015, he works as a Scientist with the Fraunhofer Portugal Research Center for Assistive Information and Communication Solutions (AICOS) on the Intelligent Systems team. His main research interests include signal processing, data mining, machine learning, and explainable artificial intelligence applied to time series.