S
Sabrina Iarlori
Researcher at Marche Polytechnic University
Publications - 35
Citations - 553
Sabrina Iarlori is an academic researcher from Marche Polytechnic University. The author has contributed to research in topics: Robot & Wheelchair. The author has an hindex of 11, co-authored 30 publications receiving 387 citations.
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Journal ArticleDOI
Electric Motor Fault Detection and Diagnosis by Kernel Density Estimation and Kullback–Leibler Divergence Based on Stator Current Measurements
TL;DR: This paper deals with the problem of fault detection and diagnosis of induction motor based on motor current signature analysis with Kernel density estimation (KDE) and Kullback-Leibler divergence used as an index to identify the dissimilarity between two probability distributions.
Journal ArticleDOI
The KIMORE Dataset: KInematic Assessment of MOvement and Clinical Scores for Remote Monitoring of Physical REhabilitation
Marianna Capecci,Maria Gabriella Ceravolo,Francesco Ferracuti,Sabrina Iarlori,Andrea Monteriù,Luca Romeo,Federica Verdini +6 more
TL;DR: The KIMORE dataset merges a large heterogeneous population of 78 subjects, divided into 2 groups with 44 healthy subjects and 34 with motor dysfunctions, and provides the most clinically-relevant features and the clinical score for each exercise.
Proceedings ArticleDOI
Accuracy evaluation of the Kinect v2 sensor during dynamic movements in a rehabilitation scenario
Marianna Capecci,M. G. Ceravolo,Francesco Ferracuti,Sabrina Iarlori,Sauro Longhi,Luca Romeo,S. N. Russi,Federica Verdini +7 more
TL;DR: In this work, joint positions and angles represent clinical features, chosen by medical staff, used to evaluate the subject's movements, and provide salient information for evaluating the reliability of Kinect v2 sensor for dynamic postures.
Journal ArticleDOI
A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment.
Marianna Capecci,M. G. Ceravolo,Francesco Ferracuti,Sabrina Iarlori,Ville Kyrki,Andrea Monteriù,Luca Romeo,Federica Verdini +7 more
TL;DR: The study supports the use of HSMMs to assess motor performance providing a quantitative feedback to physiotherapist and patients and its correlation better with the physician's score than DTW.
Journal ArticleDOI
Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review.
Nibras Abo Alzahab,Luca Apollonio,Angelo Di Iorio,Muaaz Alshalak,Sabrina Iarlori,Francesco Ferracuti,Andrea Monteriù,Camillo Porcaro +7 more
TL;DR: In this paper, the authors proposed a review on hybrid deep learning-based brain-computer interface (BCI) systems, starting from seminal studies published between 2015 and 2020, extracting trends and highlighting relevant aspects to the topic.