Publications

In nature, lightweight and low-powered insects are ideal model systems to study motion perception strategies. Understanding the underlying characteristics and functionality of insects’ visual systems is not only attractive to neural system modellers but also critical in providing effective solutions to future robotics. This paper presents a novel modelling of dynamic vision system inspired by Drosophila physiology for mimicking fast motion tracking and a closed-loop behavioural response to fixation. The proposed model was realised on the embedded system in an autonomous micro robot which has limited computational resources. A monocular camera was applied as the only motion sensing modality. Systematic experiments including open-loop and closed-loop bio-robotic tests validated the proposed visual fixation model: the robot showed motion tracking and fixation behaviours similarly to insects; the image processing frequency can maintain 25 45Hz. Arena tests also demonstrated a successful following behaviour aroused by fixation in navigation.

The efficient use and transport of byproduct gypsum to be used as a secondary raw material implies its conditioning in a suitable physical form. Most frequently demands are to supply a concentrated suspension, which is sufficiently fluid and stable to be pumped and stored in tanks. The preparation of a fluid concentrated gypsum slurry is a demanding task, since particle anisotropy and surface interactions prevent the attainment of high solid loadings. In this paper we present the testing of different families of dispersants, and discuss the modifications of the surface interactions exerted by each, in terms of surface potential and macroscopic rheological properties. We show that by appropriately choosing the dispersing system it is possible to prepare pumpable concentrated slurries with a solid content approaching 80% by weight. Star-shaped polymers are shown to enable the preparation of highly concentrated suspensions, which exhibit good rheological properties and retain stability both under rest and at the highest shear rates, thus being adapted to be stored in tanks, and to be transferred by pumping. These dispersing agents do not induce electrostatic repulsion among the particles, ζ-potential being nearly zero. Steric repulsion is responsible for the dispersion, and even at the highest concentration the suspension does not show jamming and thickening.

This paper presents a physiological monitoring system for assistive robots using a thermal camera. It is based on the detection of subtle changes in temperature observed on different parts of the face. First, we segment and estimate these face regions on thermal images. Then, by applying Fourier analysis on temperature data, we estimate respiration and heartbeat rate. This physiological monitoring system has been integrated in an assistive robot for elderly people at home, as part of the ENRICHME project. Its performance has been evaluated on a new thermal dataset for physiological monitoring, which is made publicly available for researchpurposes.

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, contrary to the popular trend of focusing mostly on the machine learning aspects of MI BCI training, a comprehensive mutual learning methodology that reinstates the three learning pillars (at the machine, subject, and application level) as equally significant could lead to a BCI–user symbiotic system able to succeed in real-world scenarios such as the Cybathlon event. Two severely impaired participants with chronic spinal cord injury (SCI), were trained following our mutual learning approach to control their avatar in a virtual BCI race game. The competition outcomes substantiate the effectiveness of this type of training. Most importantly, the present study is one among very few to provide multifaceted evidence on the efficacy of subject learning during BCI training. Learning correlates could be derived at all levels of the interface—application, BCI output, and electroencephalography (EEG) neuroimaging—with two end-users, sufficiently longitudinal evaluation, and, importantly, under real-world and even adverse conditions.

Objective: To evaluate the effectiveness of reinforced feedback in virtual environment (RFVE) treatment combined with conventional rehabilitation (CR) in comparison with CR alone, and to study whether changes are related to stroke etiology (ie, ischemic, hemorrhagic). Design: Randomized controlled trial. Setting: Hospital facility for intensive rehabilitation. Participants: Patients (N=136) within 1 year from onset of a single stroke (ischemic: n=78, hemorrhagic: n=58). Interventions: The experimental treatment was based on the combination of RFVE with CR, whereas control treatment was based on the same amount of CR. Both treatments lasted 2 hours daily, 5d/wk, for 4 weeks. Main Outcome Measures: Fugl-Meyer upper extremity scale (F-M UE) (primary outcome), FIM, National Institutes of Health Stroke Scale (NIHSS), and Edmonton Symptom Assessment Scale (ESAS) (secondary outcomes). Kinematic parameters of requested movements included duration (time), mean linear velocity (speed), and number of submovements (peak) (secondary outcomes). Results: Patients were randomized in 2 groups (RFVE with CR: n=68, CR: n=68) and stratified by stroke etiology (ischemic or hemorrhagic). Both groups improved after treatment, but the experimental group had better results than the control group (Mann-Whitney U test) for F-M UE (P<.001), FIM (P<.001), NIHSS (P≤.014), ESAS (P≤.022), time (P<.001), speed (P<.001), and peak (P<.001). Stroke etiology did not have significant effects on patient outcomes. Conclusions: The RFVE therapy combined with CR treatment promotes better outcomes for upper limb than the same amount of CR, regardless of stroke etiology.

Background: Dystroglycanopathy (α-DG) is a relatively common, clinically and genetically heterogeneous category of congenital forms of muscular dystrophy (CMD) and limb-girdle muscular dystrophy (LGMD) associated with hypoglycosylated α-dystroglycan. To date, mutations in at least 19 genes have been associated with α-DG. One of them, GMPPB, encoding the guanosine-diphosphate-mannose (GDP-mannose) pyrophosphorylase B protein, has recently been associated with a wide clinical spectrum ranging from severe Walker-Warburg syndrome to pseudo-metabolic myopathy and even congenital myasthenic syndromes. We re-sequenced the full set of known disease genes in 73 Italian patients with evidence of either reduced or nearly absent α-dystroglycan to assess genotype-phenotype correlations in this cohort. We used innovative bioinformatic tools to calculate the effects of all described GMPPB mutations on protein function and attempted to correlate them with phenotypic expressions. Results: We identified 13 additional cases from 12 families and defined seven novel mutations. Patients displayed variable phenotypes including less typical pictures, ranging from asymptomatic hyperCKemia, to arthrogryposis and congenital clubfoot at birth, and also showed neurodevelopmental comorbidities, such as seizures and ataxic gait, as well as autism-spectrum disorder, which is seldom described in clinical reports of dystroglycanopathies. We also demonstrated that few mutations recur in the Italian GMPPB-mutated population and that alterations of protein stability are the main effects of GMPPB missense variants. Conclusion: This work adds to the data on genotype-phenotype correlations in α-DG and offers new bionformatic tools to provide the conceptual framework needed to understand the complexity of these disorders.

Aims: Pompe disease is an autosomal recessive lysosomal storage disorder resulting from deficiency of acid α-glucosidase (GAA) enzyme. Histopathological hallmarks in skeletal muscle tissue are fibre vacuolization and autophagy. Since 2006, enzyme replacement therapy (ERT) is the only approved treatment with human recombinant GAA alglucosidase alfa. We designed a study to examine ERT-related skeletal muscle changes in 18 modestly to moderately affected late onset Pompe disease (LOPD) patients along with the relationship between morphological/biochemical changes and clinical outcomes. Treatment duration was short-to-long term. Methods: We examined muscle biopsies from 18 LOPD patients at both histopathological and biochemical level. All patients underwent two muscle biopsies, before and after ERT administration respectively. The study is partially retrospective because the first biopsies were taken before the study was designed, whereas the second biopsy was always performed after at least 6 months of ERT administration. Results: After ERT, 15 out of 18 patients showed improved 6-min walking test (6MWT; P = 0.0007) and most of them achieved respiratory stabilization. Pretreatment muscle biopsies disclosed marked histopathological variability, ranging from an almost normal pattern to a severe vacuolar myopathy. After treatment, we detected morphological improvement in 15 patients and worsening in three patients. Post-ERT GAA enzymatic activity was mildly increased compared with pretreatment levels in all patients. Protein levels of the mature enzyme increased in 14 of the 18 patients (mean increase = +35%; P < 0.05). Additional studies demonstrated an improved autophagic flux after ERT in some patients. Conclusions: ERT positively modified skeletal muscle pathology as well as motor and respiratory outcomes in the majority of LOPD patients.

The presence of major depressive symptoms is usually considered a negative long-term prognostic factor after an acute myocardial infarction (AMI); however, most of the supporting research was conducted before the era of immediate reperfusion by percutaneous coronary intervention. The aims of this study are to evaluate if depression still retains long-term prognostic significance in our era of immediate coronary reperfusion, and to study possible correlations with clinical parameters of physical performance. In 184 patients with recent ST-elevated AMI (STEMI), treated by immediate reperfusion, moderate or severe depressive symptoms (evaluated by Beck Depression Inventory version I) were present in 10 % of cases. Physical performance was evaluated by two 6-min walk tests and by a symptom-limited cardiopulmonary exercise test: somatic/affective (but not cognitive/affective) symptoms of depression and perceived quality of life (evaluated by the EuroQoL questionnaire) are worse in patients with lower levels of physical performance. Follow-up was performed after a median of 29 months by means of telephone interviews; 32 major adverse cardiovascular events (MACE) occurred. The presence of three vessels disease and low left ventricle ejection fraction are correlated with a greater incidence of MACE; only somatic/affective (but not cognitive/affective) symptoms of depression correlate with long-term outcomes. In patients with recent STEMI treated by immediate reperfusion, somatic/affective but not cognitive/affective symptoms of depression show prognostic value on long-term MACE. Depression symptoms are not predictors “per se” of adverse prognosis, but seem to express an underlying worse cardiac efficiency, clinically reflected by poorer physical performance.

Automated recognition of Activities of Daily Living allows to identify possible health problems and apply corrective strategies in Ambient Assisted Living (AAL). Activities of Daily Living analysis can provide very useful information for elder care and long-term care services. This paper presents an automated RGB-D video analysis system that recognises human ADLs activities, related to classical daily actions. The main goal is to predict the probability of an analysed subject action. Thus, abnormal behaviour can be detected. The activity detection and recognition is performed using an affordable RGB-D camera. Human activities, despite their unstructured nature, tend to have a natural hierarchical structure; for instance, generally making a coffee involves a three-step process of turning on the coffee machine, putting sugar in cup and opening the fridge for milk. Action sequence recognition is then handled using a discriminative Hidden Markov Model (HMM). RADiaL, a dataset with RGB-D images and 3D position of each person for training as well as evaluating the HMM, has been built and made publicly available.