Visit our Scientific Research Area: a section dedicated to professionals in the field, where you can find official resources—official documents, publications, and advanced research—on the scientific research topics of the synbrAIn team.

Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review

Parkinson’s disease (PD) is a neurodegenerative disorder that produces both motor and non-motor complications, degrading the quality of life of PD patients. Over the past two decades, the use of wearable devices in combination with machine learning algorithms has provided promising methods for more objective and continuous monitoring of PD.

Continue ReadingDeep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review

Analyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Using additional training data is known to improve the results, especially for medical image 3D segmentation where there is a lack of training material and the model needs to generalize well from few available data.

Continue ReadingAnalyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Automated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Oral capillaroscopy is a critical and non-invasive technique used to evaluate microcirculation. Its ability to observe small vessels in vivo has generated significant interest in the field. Capillaroscopy serves as an essential tool for diagnosing and prognosing various pathologies, with anatomic–pathological lesions playing a crucial role in their progression.

Continue ReadingAutomated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Enhancing video game experience with playtime training and tailoring of virtual opponents: Using Deep Q-Network based Reinforcement Learning on a Multi-Agent Environment

When interacting with fictional environments, the users' sense of immersion can be broken when characters act in mechanical and predictable ways.

Continue ReadingEnhancing video game experience with playtime training and tailoring of virtual opponents: Using Deep Q-Network based Reinforcement Learning on a Multi-Agent Environment

Teeth Segmentation in Panoramic Dental X-ray Using Mask Regional Convolutional Neural Network

Accurate instance segmentation of teeth in panoramic dental X-rays is a challenging task due to variations in tooth morphology and overlapping regions. In this study, we propose a new algorithm, for instance, segmentation of the different teeth in panoramic dental X-rays.

Continue ReadingTeeth Segmentation in Panoramic Dental X-ray Using Mask Regional Convolutional Neural Network

Automatic Detection of Myotonia using a Sensory Glove with Resistive Flex Sensors and Machine Learning Techniques

This paper deals with the automatic detection of Myotonia from a task based on the sudden opening of the hand. Data have been gathered from 44 subjects, divided into 17 controls and 27 myotonic patients, by measuring a 2-point articulation of each finger thanks to a calibrated sensory glove equipped with a Resistive Flex Sensor (RFS).

Continue ReadingAutomatic Detection of Myotonia using a Sensory Glove with Resistive Flex Sensors and Machine Learning Techniques

Hallmarks of Parkinson’s disease progression determined by temporal evolution of speech attractors in the reconstructed phase-space

Parkinson’s disease (PD) is one of the most widespread neurodegenerative diseases worldwide, affected by a number of alterations, among which speech impairments that, interestingly, manifests up to 10 years before other major evidences (e.g. motor impairments).

Continue ReadingHallmarks of Parkinson’s disease progression determined by temporal evolution of speech attractors in the reconstructed phase-space

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