A new approach for real-time center-of-pressure correction in pressure sensitive mats using feedforward neural networks

Domínguez Gimeno, Sergio (Universidad de Zaragoza) ; Igual Catalán, Raúl (Universidad de Zaragoza) ; Medrano Sánchez, Carlos (Universidad de Zaragoza) ; Plaza García, Inmaculada (Universidad de Zaragoza) ; Martínez Cesteros, Javier (Universidad de Zaragoza) ; Pasetti, Marco

Resumen: Center-of-pressure (CoP) is a good clinical indicator in balance tests and fall-risk assessment. It can be detected using pressure sensitive mats (PSMs), which are affordable. However, these can suffer from certain nonidealities, such as hysteresis and creep. These effects have been assessed in literature. However, proposed algorithms have low computation speed and are complex. In this work, a completely new approach based on feedforward neural networks (FFNNs) is proposed with the goal of correcting the CoP given by PSMs, allowing real-time correction. Its performance is compared in terms of error and computation times with a state-of-the-art model, which corrects for hysteresis and creep in the PSM. Results show that FFNN can correct for the CoP measurements, providing a good accuracy-speed balance.

Idioma: Inglés

DOI: 10.1109/LSENS.2025.3601010

Año: 2025

Publicado en: IEEE Sensors Letters 9, 9 (2025), 7004804 [4 pp.]
ISSN: 2475-1472

Financiación: info:eu-repo/grantAgreement/ES/DGA/T49-23R
Financiación: info:eu-repo/grantAgreement/ES/MCIN/PID2021-125091OB-I00
Financiación: info:eu-repo/grantAgreement/ES/MTDFP-INCIBE/C-2023-077

Tipo y forma: Article (Published version)

Área (Departamento): Área Tecnología Electrónica (Dpto. Ingeniería Electrón.Com.)
Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)