The nomination to Best Paper Award at the upcoming CIARP conference belongs to a team with IEETA signature. The team is composed by João Rodrigues (IST), Osvaldo Pacheco (IEETA), and Paulo Correia (IST). CIARP will be held in Coimbra this November 2023. The conference is focused on disruptive innovation on pattern recognition, computer vision, artificial […]
We are delighted to announce that the paper titled “Gesture Recognition for Communication Support in the Context of the Bedroom: Comparison of Two Wearable Solutions” has been awarded the prestigious “Best Paper Award” at the International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE). The paper, authored by Ana Patrícia […]
AltaiR is a newly developed C-based toolkit that revolutionizes large-scale genomic and proteomic data analysis. By using alignment-free methodologies, AltaiR can efficiently handle millions of sequences, making it especially valuable for studying viruses like SARS-CoV-2. With AltaiR, researchers can quickly filter out low-quality data, track how genomes evolve over time, and detect unique segments of […]
The integration of a collaborative VR framework that integrates serious games with varying levels of complexity allows to enhance motivation, engagement, and social interaction among stroke survivors. The system, developed by a IEETA team, enables healthcare professionals to monitor participants in real-time through a dedicated tool, allowing for dynamic adjustments and personalized VR experiences. This […]
Time series are data points collected at regularly spaced time intervals. Time series of counts are a special type of time series considering only non-negative integer values. An example is the daily number of hospital admissions, which can be zero or any other positive integer value. This type of data requires models that ensure the […]
Hand–eye calibration is critical for robotics, enabling precise coordination between cameras and robotic systems. Our work introduces a general approach that stands out for its versatility and accuracy: Key Highlights • Handles Multiple Setups: Simultaneously supports eye-on-hand and eye-to-base configurations, as well as multiple cameras. • Nonlinear Optimization: Uses a nonlinear least squares method guided […]
BoosToRaise is revolutionizing the workplace, co-created with giants like Bosch Thermotechnology, Ikea Industry, and Oli-Sistemas Sanitários. This platform inspires career ownership, fosters a learning-obsessed culture, and champions employee-driven innovation. What makes BoosToRaise a game-changer? 1. Career Self-Ownership: Empowering employees to steer their own careers using the Harada Method and Neuro-Linguistic Programming for sharp, actionable plans. […]
Restoring mobility in individuals with motor impairments is one of the most ambitious goals in neurorehabilitation. At the intersection of neuroscience, machine learning, and assistive robotics, we are developing Brain-Machine Interfaces (BMIs) that can decode motor intentions from brain signals (EEG), even when data is limited, noisy, or imbalanced. Here’s what makes this research innovative: […]
A privacy-aware framework for Random Forests & XGBoost in distributed settings, built for practitioners who need auditability, not black boxes. Most federated learning toolkits focus on deep nets and often overlook interpretability. If you work with regulated data (e.g. healthcare or finance), that’s a non-starter. This work delivers a federated, PySyft-based approach for tree models […]
Genomic research fundamentally requires three components. Researchers must be able to find relevant data, obtain lawful and ethical access to it, and perform computations close to where the data resides. The European Genomic Data Infrastructure (GDI) addresses these needs by connecting national nodes, allowing researchers to locate datasets easily, request secure access, and run analyses […]
In many real-world classification problems, datasets exhibit a skewed class distribution, known as class imbalance, where one class has significantly more samples than another. Machine learning models trained on imbalanced data tend to favor the class with more samples. This bias toward the majority class leads to poor classification performance on rare but important cases, […]
🏥 Identifying biomedical named entities from clinical narratives has a great interest in the scientific community due to its importance in treatment improvements, drug development research, and patient record analysis. 💪 Traditional approaches often focus on recognizing a single entity type (such as chemicals), yet recent advancements emphasize the necessity of addressing multi-class scenarios. 🧠 […]
Viruses play a crucial role in many conditions, from rare diseases and syndromes to certain cancers. Yet, most treatments focus on managing the consequences of these diseases, rather than addressing the root cause – often undetected viral infections. The tide is turning, and leading medical centers are now focusing on the viruses that reside within […]
Communication difficulties can profoundly impact a person’s overall quality of life. However, most existing communication support systems are not designed for use while lying in bed alone, leaving a gap in assistive technology. 🔹 Introducing a Communication Support Solution for the In-Bed Scenario In the scope of the APH-ALARM project, we developed a system specifically […]
