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The aim of this study was to identify a method for staging hepatic fibrosis using a non-invasive, rapid and inexpensive technique based on ultrasound morphologic hepatic features. A total of 215 patients with different liver diseases underwent B-mode (2-D brightness mode) ultrasonography, vibration-controlled transient elastography, 2-D shear wave elastography and measurement of the controlled attenuation parameter with transient elastography. B-Mode images of the anterior margin of the left lobe were obtained and processed with automatic Genoa Line Quantification (GLQ) software based on a neural network for staging liver fibrosis. The accuracy of GLQ was 90.6% during model training and 78.9% in 38 different patients with concordant elastometric measures. Receiver operating characteristic curve analysis of GLQ performance using vibration-controlled transient elastography as a reference yielded areas under the curves of 0.851 for F ≥ F1, 0.793 for F ≥ F2, 0.784 for F ≥ F3 and 0.789 for F ≥ F4. GLQ has the potential to be a rapid, easy-to-perform and tolerable method in the staging of liver fibrosis.

Image segmentation partitions a digital image into regions of interest, by taking into account the information content and local properties of homogeneity and topological connectivity. The evaluation of segmentation quality is usually based on supervised ground-truth images, which are provided by experts and used for comparison with segmented images. Indeed, intra-rater and inter-rater reliability affect the accuracy of such reference information. In addition to subjectivity, the skill of the experts and their knowledge could lead to bias. To achieve an objective performance measure, an automatic method for unsupervised evaluation of volume segmentation is proposed, which aims at finding a repetitive and user-independent evaluation of segmented results. The proposed approach leverages on the integration of volume- and boundary-based analysis. The quality of the segmentation is estimated on the basis of gradient properties, measured in the volume and focused on the voxels of the border. The segmentation is evaluated through a simple fuzzy index based on the resulting gradient. The experimental phase is conducted on a set of Magnetic Resonance volumes of the wrist district.

In this paper, a study on the use of ICT support to help therapists and Systemic Sclerosis (SSc) patients in the recovery phase is described. The ReMoVES platform is conceived in the field of assistive computing technologies and delivers engaging exergames to be performed in conjunction with traditional rehabilitation both at home and at clinical centers, thus enabling the continuity of care. The present work refers to the implementation and integration in the ReMoVES platform of standard hand rehabilitative exercises for SSc that typically involves repetitive movements. Data related to game sessions are collected and analyzed for assessing the patients’ conditions.

Internet of Things (IoT) solutions are a concrete answer to many needs in the healthcare framework since they enable remote support for patients and foster continuity of care. Currently, frail elderly people are among end users who most need and would benefit from IoT solutions from both a social and a healthcare point of view. Indeed, IoT technologies can provide a set of services to monitor the healthcare of the elderly or support them in order to reduce the risk of injuries, and preserve their motor and cognitive abilities. The main feature of IoT solutions for the elderly population is ease of use. Indeed, to fully exploit the potential of an IoT solution, patients should be able to autonomously deal with it. The remote-monitoring validation engineering system (ReMoVES) described here is an IoT solution that caters to the specific needs of frail elderly individuals. Its architecture was designed for use at rehabilitation centers and at patients’ homes. The system is user-friendly and comfortably usable by persons who are not familiar with technology. In addition, exergames enhance patient engagement in order to curb therapy abandonment. Along with the technical presentation of the solution, a real-life scenario application is described referring to sit-to-stand activity.

Cultural heritage preservation is a crucial topic for our society. When dealing with fine art, color is a primary feature that encompasses much information related to the artwork’s conservation status and to the pigments’ composition. As an alternative to more sophisticated devices, the analysis and identification of color pigments may be addressed via a digital camera, i.e., a non-invasive, inexpensive, and portable tool for studying large surfaces. In the present study, we propose a new supervised approach to camera characterization based on clustered data in order to address the homoscedasticity of the acquired data. The experimental phase is conducted on a real pictorial dataset, where pigments are grouped according to their chromatic or chemical properties. The results show that such a procedure leads to better characterization with respect to state-of-the-art methods. In addition, the present study introduces a method to deal with organic pigments in a quantitative visual approach.

Visuospatial neglect (VN) frequently occurs in Posterior Cortical Atrophy (PCA) and requires specific rehabilitation. In this single-case study, we investigated the efficacy of a computer-assisted cognitive training (CCT) alone or coupled with multiple sessions of anodal transcranial direct-current stimulation (A-tDCS) over the right posterior parietal cortex in improving left VN symptoms in a patient with PCA. The digital ReMoVES platform was used for both VN assessment and training. We found a significant improvement after CCT combined with A-tDCS within the limits of a single-case, our results suggest, for the first time, the usefulness of this combined approach in a neurodegenerative disorder.

Digital solutions for unilateral spatial neglect (USN) assessment and treatment are nowadays of great interest, because of both the possibility of combining them with other rehabilitation practices, and the easy-to-understand data and indicators they collect. The ReMoVES platform, developed in DITEN laboratories, is conceived in the Assistive Technologies framework and provides motor and cognitive exergames and activities to be performed in conjunction with traditional rehabilitation. In this work, two case-studies, related to the USN rehabilitation, are presented. The combination of cognitive therapy, delivered by the ReMoVES platform, and transcranial direct-current stimulation (tDCS) technique was used as rehabilitation treatment for both the patients. Data collected at the beginning or at the end of the rehabilitation process, or also during the treatment sessions, are shown and discussed in this paper. This work is a preliminary part of a wider one, that will be conducted involving many different rehabilitation centers, aimed at proving the validity of such an approach to USN treatments.

Nowadays, the tools for remote monitoring and training analysis are a matter of deep interest in the field of telerehabilitation. In this study we present a method for the automated evaluation of performance in exergames for motor rehabilitation that can be performed by the patient, even autonomously in a domestic environment, with Microsoft Kinect and Leap Motion. The proposed method is based on a machine learning approach utilizing the Support Vector Machine (SVM). It uses a radial basis function kernel that deals with a two-class classification problem. The performance outcomes for one of the 10 exergames developed by our team are provided as a case study. After a crucial phase consisting of hyperparameter optimization, the SVM algorithm proved to be able to distinguish the "Good" class from the "Other" class with an accuracy of 0.80.

Chocolate is a food product that is loved by many because of its desirable qualities. These qualities include a shiny gloss on the surface, snap when the chocolate is broken, and a smooth texture that becomes apparent only when the chocolate melts in the mouth. Aim of this paper is the application of a 2-step quality assessment to fine chocolate products, e.g. the well-known Italian “Cremino”, distributed worldwide. The first step consists in monitoring the temperature fluctuation during the distribution from the production plant to the point of demand, usually a candy shop. The second step deals with the simulation of the monitored shipment in a temperature and humidity controlled system. The simulation of the physical and environmental conditions generated during the real shipment is followed by chemical analysis and sensitive analysis conducted separately on non-stressed products (the so-called “time zero products”) and stressed products. The effects of temperature are evaluated by comparing stressed and time zero products belonging to the same production batch. The analyses are repeated after 6 months in order to evaluate the effects due to time and shelf-life erosion. The obtained results demonstrate the importance and criticality of packaging and containment solutions to face unexpected temperature variations during the logistic journey to the final consumer.