Low-cost inkjet-printed nanostructured biosensor based on CRISPR/Cas12a system for pathogen detection.

The escalating global incidence of infectious diseases caused by pathogenic bacteria, especially in developing countries, emphasises the urgent need for rapid and portable pathogen detection devices. This study introduces a sensitive and specific electrochemical biosensing platform utilising cost-effective electrodes fabricated by inkjet-printing gold and silver nanoparticles on a plastic substrate. The biosensor exploits the CRISPR/Cas12a system for detecting a specific DNA sequence selected from the genome of the target pathogen. Upon detection, the trans-activity of Cas12a/gRNA is triggered, leading to the cleavage of rationally designed single-strand DNA reporters (linear and hairpin) labelled with methylene blue (ssDNA-MB) and bound to the electrode surface. In principle, this sensing mechanism can be adapted to any bacterium by choosing a proper guide RNA to target a specific sequence of its DNA. The biosensor's performance was assessed for two representative pathogens (a Gram-negative, Escherichia coli, and a Gram-positive, Staphylococcus aureus), and results obtained with inkjet-printed gold electrodes were compared with those obtained by commercial screen-printed gold electrodes. Our results show that the use of inkjet-printed nanostructured gold electrodes, which provide a large surface area, in combination with the use of hairpin reporters containing a poly-T loop can increase the sensitivity of the assay corresponding to a signal variation of 86%. DNA targets amplified from various clinically isolated bacteria, have been tested and demonstrate the potential of the proposed platform for point-of-need applications.

Inkjet-printed fully customizable and low-cost electrodes matrix for gesture recognition.

The use of surface electromyography (sEMG) is rapidly spreading, from robotic prostheses and muscle computer interfaces to rehabilitation devices controlled by residual muscular activities. In this context, sEMG-based gesture recognition plays an enabling role in controlling prosthetics and devices in real-life settings. Our work aimed at developing a low-cost, print-and-play platform to acquire and analyse sEMG signals that can be arranged in a fully customized way, depending on the application and the users' needs. We produced 8-channel sEMG matrices to measure the muscular activity of the forearm using innovative nanoparticle-based inks to print the sensors embedded into each matrix using a commercial inkjet printer. Then, we acquired the multi-channel sEMG data from 12 participants while repeatedly performing twelve standard finger movements (six extensions and six flexions). Our results showed that inkjet printing-based sEMG signals ensured significant similarity values across repetitions in every participant, a large enough difference between movements (dissimilarity index above 0.2), and an overall classification accuracy of 93-95% for flexion and extension, respectively.

Design and Construction of a Bilateral Haptic System for the Remote Assessment of the Stiffness and Range of Motion of the Hand.

The use of haptic devices in the rehabilitation of impaired limbs has become rather popular, given the proven effectiveness in promoting recovery. In a standard framework, such devices are used in rehabilitation centers, where patients interact with virtual tasks, presented on a screen. To track their sessions, kinematic/dynamic parameters or performance scores are recorded. However, as Internet access is now available at almost every home and in order to reduce the hospitalization time of the patient, the idea of doing rehabilitation at home is gaining wide consent. Medical care programs can be synchronized with the home rehabilitation device; patient data can be sent to the central server that could redirect to the therapist laptop (tele-healthcare). The controversial issue is that the recorded data do not actually represent the clinical conditions of the patients according to the medical assessment scales, forcing them to frequently undergo clinical tests at the hospital. To respond to this demand, we propose the use of a bilateral master/slave haptic system that could allow the clinician, who interacts with the master, to assess remotely and in real time the clinical conditions of the patient that uses the home rehabilitation device as the slave. In this paper, we describe a proof of concept to highlight the main issues of such an application, limited to one degree of freedom, and to the measure of the stiffness and range of motion of the hand.

Robotic upper limb rehabilitation after acute stroke by NeReBot: evaluation of treatment costs.

Stroke is the first cause of disability. Several robotic devices have been developed for stroke rehabilitation. Robot therapy by NeReBot is demonstrated to be an effective tool for the treatment of poststroke paretic upper limbs, able to improve the activities of daily living of stroke survivors when used both as additional treatment and in partial substitution of conventional rehabilitation therapy in the acute and subacute phases poststroke. This study presents the evaluation of the costs related to delivering such therapy, in comparison with conventional rehabilitation treatment. By comparing several NeReBot treatment protocols, made of different combinations of robotic and nonrobotic exercises, we show that robotic technology can be a valuable and economically sustainable aid in the management of poststroke patient rehabilitation.

Cost of disorders of the brain in Italy.

The aim of this study was to estimate the cost of "brain" disorders in Italy. Country-specific prevalence and health-economic data on addiction, affective, anxiety and psychotic disorders, tumours, dementia, epilepsy, migraine/other headaches, multiple sclerosis, Parkinson's disease, stroke and head trauma were reviewed. Direct medical/non-medical and indirect costs were computed. Population-based samples and national or regional registries were used. The Italian population expected with a brain disorder was 12.4 million in 2004. The highest cost per case was for tumours and multiple sclerosis; the lowest was for anxiety disorders and migraine. Dementia (8.6 billion euros), psychotic and affective disorders (18.7 billion euros), migraine (3.5 billion euros) and stroke (3.4 billion euros) represented the highest total costs. Direct medical costs were predominant for psychiatric and neurosurgical disorders, direct non-medical costs for dementia, and indirect costs for neurological disorders. The total cost of brain disorders in Italy was 40.8 billion euros, 3% of the gross national product, and 706 euros per Italian citizen/year. This figure is however likely to be underestimated as it is based on retrospective methodology and samples of brain disorders, and does not include intangible costs.