Federated Learning;Cloud Computing;Healthcare Data Analysis;Smart Healthcare Applications

Publications

Smart textiles for health monitoring in industrial environments: a framework for wearable sensor integration

Publication . Vilarinho, Bruna Abreu; Vieira, Andre; Nunes-Pereira, João; Parente, João; Pires, Ivan Miguel Serrano ; Velez, Fernando J.

The occupational health and safety of workers in industrial plants are increasingly compromised through exposure to thermal, physical, and psychological stressors. Wearable sensors embedded in garments have been introduced as a promising technology for real-time, continuous health monitoring without compromising workers' mobility or comfort. This paper reviews recent literature on wearable sensor technologies embedded in textiles, with a focus on their applicability in industrial settings. The paper identifies the key physiological parameters commonly monitored (e.g., heart rate, skin temperature, respiratory rate, and skin conductance), the materials and sensor types used, as well as the methods of integration into garments. Based on the findings, a conceptual model for a smart textile monitoring system tailored to industrial workers is proposed. The aim is to support the development of ergonomic, accessible, unobtrusive, and effective solutions that promote occupational health and prevent work-related illnesses.

2025-07-24Text

Open access

Wearable sensors for stress monitoring in meniscus injury rehabilitation

Publication . Pires, Catarina de Sá Baio; Velez, Fernando J.; Coelho, Paulo Jorge Simões; Pataca, António Oseas; Pires, Ivan Miguel Serrano

Monitoring vital signs is essential in identifying physiological stress, particularly in rehabilitating meniscus injuries. Stress can compromise the effectiveness of physiotherapy, affecting recovery. This paper reviews monitoring technologies, such as those that consider heart rate and sweating sensors, and their application in remote patient monitoring. It highlights the importance of collecting real-time data to personalize treatments and optimize recovery and explores the challenges and benefits of this approach. Integrating these technologies can significantly improve therapeutic results, prevent stress, and improve patients' quality of life.

2025-07-25Text

Open access

Keywords

This project is at the forefront of combining cloud computing and federated learning to transform healthcare technologies. The healthcare industry is placing a greater and greater focus on data-driven decision-making. This project seeks to leverage big data while maintaining patient privacy and data security as top priorities. The project's fundamental idea is to use federated learning, a cutting-edge method for machine learning. With this technology, sensitive patient data can be shared throughout healthcare facilities to train algorithms collaboratively. Federated learning protects data privacy by learning from various data sources while allowing the development of strong, generalized models by maintaining the data localized. It is imperative in the healthcare industry, as diverse data sets significantly improve the precision and effectiveness of prediction models used in patient diagnosis and treatment. The project uses cloud and high-performance computing (HPC) technologies to support federated learning to handle, process, and evaluate extensive and intricate healthcare datasets. With cloud computing's scalability and flexibility, healthcare providers may access computational resources on demand, lowering costs and efficiency. HPC enables the swift handling of substantial data, which is crucial for instantaneous analysis and judgment in crucial healthcare situations with flexible and scalable machine learning models. By managing the inherent variety in healthcare data, these models help to improve therapy tailoring and patient care management. The project intends to change the healthcare environment by incorporating machine learning and sophisticated analytics to make it more preventive, personalized, and predictive. The project will revolutionize healthcare by providing cutting-edge technology solutions, representing a significant advancement in healthcare technology and a step toward a future in healthcare that is safer, more effective, and patient-centered., Engineering and technology

Funding agency

Fundação para a Ciência e a Tecnologia, I.P.

Funding programme

FCT_CPCA_2023_01

Funding Award Number

2023.10865.CPCA.A1