All Outputs (3)

A generalizable and open-source algorithm for real-life monitoring of tremor in Parkinson’s disease (2025)
Journal Article
Timmermans, N. A., Terranova, R., Soriano, D. C., Cagnan, H., Raykov, Y. P., Bucur, I. G., Bloem, B. R., Helmich, R. C., & Evers, L. J. W. (2025). A generalizable and open-source algorithm for real-life monitoring of tremor in Parkinson’s disease. npj Parkinson's Disease, 11, Article 205. https://doi.org/10.1038/s41531-025-01056-2

Wearable sensors can objectively and continuously monitor daily-life tremor in Parkinson’s Disease (PD). We developed an open-source algorithm for real-life monitoring of PD tremor which achieves generalizable performance across different wrist-worn... Read More about A generalizable and open-source algorithm for real-life monitoring of tremor in Parkinson’s disease.

Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait (2025)
Journal Article
Post, E., Van Laarhoven, T., Raykov, Y. P., Little, M. A., Nonnekes, J., Heskes, T. M., Bloem, B. R., & Evers, L. J. (2025). Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait. Journal of NeuroEngineering and Rehabilitation, 22(1), Article 37. https://doi.org/10.1186/s12984-025-01578-z

Background: Accurately measuring hypokinetic arm swing during free-living gait in Parkinson’s disease (PD) is challenging due to other concurrent arm activities. We developed a method to isolate gait segments without these arm activities. Methods: Wr... Read More about Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait.

Principled Machine Learning (2022)
Journal Article
Raykov, Y. P., & Saad, D. (2022). Principled Machine Learning. IEEE Journal of Selected Topics in Quantum Electronics, 28(4), Article 0200419. https://doi.org/10.1109/JSTQE.2022.3186798

We introduce the underlying concepts which give rise to some of the commonly used machine learning methods, excluding deep-learning machines and neural networks. We point to their advantages, limitations and potential use in various areas of photonic... Read More about Principled Machine Learning.