A Wearable AR-based BCI for Robot Control in ADHD Treatment: Preliminary Evaluation of Adherence to Therapy

A wearable, single-channel Brain-Computer Interface (BCI) based on Augmented Reality (AR) and Steady-State Visually Evoked Potentials (SSVEPs) for robot control is proposed as an innovative therapy for robot-based Attention Deficit Hyperactivity Disorder (ADHD) rehabilitation of children. The system manages to overcome the challenges regarding immersivity and wearability, providing a direct path between human brain and social robots, already successfully employed for ADHD treatment. Through the proposed system, even without training, the user can drive a robot, in real-time, by brain signals. A preliminary evaluation of the children adherence to the therapy was conducted as a case study on 18 subjects, at an accredited rehabilitation center. After investigating the children acceptance of the proposed system, different tasks were assigned to the volunteers aiming to observe their level of involvement. The experimental activity showed encouraging results, where almost all the participants were satisfied with the experience and keen to repeat it again in the future

Evaluation of the Effectiveness of a Wearable, {AR}-based {BCI} for Robot Control in {ADHD} Treatment

A highly wearable, single-channel Brain-Computer Interface based on Augmented Reality and Steady-State Visually Evoked Potentials is proposed as a therapy for Attention Deficit Hyperactivity Disorder (ADHD) rehabilitation of children. Through the proposed system, the user can drive a social robot, in real-time, by simply looking at the flickering icons rendered on the Augmented Reality (AR) smart glasses. The social robot is already successfully employed for ADHD treatment. After a preliminary evaluation of the children adherence to the therapy (involving 18 subjects), a one-month therapy was conducted on 7 participants. During the tests, different tasks were assigned to the children depending on their level of involvement. The obtained results, based on the Italian Battery for ADHD, highlight that for all the participants, an improvement in the various tests proposed could be observed, even with a low number of sessions

A Wearable SSVEP BCI for AR-based, Real-time Monitoring Applications

A real-time monitoring system based on Augmented Reality (AR) and highly wearable Brain-Computer Interface (BCI) for hands-free visualization of patient's health in Operating Room (OR) is proposed. The system is designed to allow the anesthetist to monitor hands-free and in real-time the patient's vital signs collected from the electromedical equipment available in OR. After the analysis of the requirements in a typical Health 4.0 scenario, the conceptual design, implementation and experimental validation of the proposed system are described in detail. The effectiveness of the proposed AR-BCI-based real-time monitoring system was demonstrated through an experimental activity was carried out at the University Hospital Federico II (Naples, Italy), using operating room equipment

Broadband Power Line Communication in Railway Traction Lines: A Survey

Power line communication (PLC) is a technology that exploits existing electrical transmission and distribution networks as guiding structures for electromagnetic signal propagation. This facilitates low-rate data transmission for signaling and control operations. As the demand in terms of data rate has greatly increased in the last years, the attention paid to broadband PLC (BPLC) has also greatly increased. This concept also extended to railways as broadband traction power line communication (BTPLC), aiming to offer railway operators an alternative data network in areas where other technologies are lacking. However, BTPLC implementation faces challenges due to varying operating scenarios like urban, rural, and galleries. Hence, ensuring coverage and service continuity demands the suitable characterization of the communication channel. In this regard, the scientific literature, which is an indicator of the body of knowledge related to BTPLC systems, is definitely poor if compared to that addressed to BPLC systems installed on the electrical transmission and distribution network. The relative papers dealing with BTPLC systems and focusing on the characterization of the communication channel show some theoretical approaches and, rarely, measurements guidelines and experimental results. In addition, to the best of the author's knowledge, there are no surveys that comprehensively address these aspects. To compensate for this lack of information, a survey of the state of the art concerning BTPLC systems and the measurement methods that assist their installation, assessment, and maintenance is presented. The primary goal is to provide the interested readers with a thorough understanding of the matter and identify the current research gaps, in order to drive future research towards the most significant issues

Performance and Usability Evaluation of an Extended Reality Platform to Monitor Patient’s Health during Surgical Procedures

An extended-reality (XR) platform for real-time monitoring of patients' health during surgical procedures is proposed. The proposed system provides real-time access to a comprehensive set of patients' information, which are made promptly available to the surgical team in the operating room (OR). In particular, the XR platform supports the medical staff by automatically acquiring the patient's vitals from the operating room instrumentation and displaying them in real-time directly on an XR headset. Furthermore, information regarding the patient clinical record is also shown upon request. Finally, the XR-based monitoring platform also allows displaying in XR the video stream coming directly from the endoscope. The innovative aspect of the proposed XR-based monitoring platform lies in the comprehensiveness of the available information, in its modularity and flexibility (in terms of adaption to different sources of data), ease of use, and most importantly, in a reliable communication, which are critical requirements for the healthcare field. To validate the proposed system, experimental tests were conducted using instrumentation typically available in the operating room (i.e., a respiratory ventilator, a patient monitor for intensive care, and an endoscope). The overall results showed (i) an accuracy of the data communication greater than 99 %, along with (ii) an average time response below ms, and (iii) satisfying feedback from the SUS questionnaires filled out by the physicians after intensive use

Soft Transducer for Patient’s Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection

This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In particular, first, the soft transducer measures hypertension-related vitals (heart rate, oxygen saturation and systolic/diastolic pressure) and sends the data to a remote database (which can be easily consulted both by the patient and the physician). In addition to this, a dedicated deep learning algorithm, based on a Long-Short-Term-Memory Autoencoder, was designed, implemented and tested for providing an alert when the patient’s vitals exceed certain thresholds, which are automatically personalized for the specific patient. Furthermore, a mobile application (EcO2u) was developed to manage the entire data flow and facilitate the data fruition; this application also implements an innovative face-detection algorithm that ensures the identity of the patient. The robustness of the proposed soft transducer was validated experimentally on five individuals, who used the system for 30 days. The experimental results demonstrated an accuracy in anomaly detection greater than 93%, with a true positive rate of more than 94

Malus pumila Mill. cv Annurca apple extract might be therapeutically useful against oxidative stress and patterned hair loss

: Patterned hair loss (PHL) or androgenetic alopecia is a condition affecting about 50% of people worldwide. Several pharmacological medications have been developed over the years, but few studies have investigated their effectiveness. Therefore, new, safer and more effective strategies are required. Recent investigations showed that Annurca apple extract application could induce keratin production and promote hair growth thanks to the high amount of procyanidin B2 contained in. Hence, this study aimed to investigate the role of an Annurca apple extract in preventing PHL by testing it on human follicle dermal papilla cells (HFDPCs) for the first time. Treatment of HFDPCs with Annurca apple extract counteracted intracellular reactive oxygen species accumulation by increasing the activity of antioxidant enzymes such as superoxide dismutase 2 and catalase. Furthermore, treatment with Annurca apple extract increased β-catenin and fibroblast growth factor 2, which are involved in hair growth stimulation. These data suggest that Annurca apple extract may be a potential therapeutically useful nutraceutical product for preventing or treating hair loss by reducing oxidative stress and inducing the expression of hair growth-related factors

Assessment of congenital coronary artery fistulas by transesophageal color Doppler echocardiography

PURPOSE: Coronary angiography is the gold standard for imaging the coronary tree, but the relation of coronary artery fistulas to other structures, and their origin and course, may not be apparent. We evaluated the ability of multiplane color Doppler transesophageal echocardiography to identify coronary fistulas. PATIENTS AND METHODS: Twenty-one patients with angiographically confirmed coronary artery fistulas were investigated by transesophageal echocardiography in four Italian hospitals between January 1997 and May 2001. RESULTS: Transesophageal echocardiography correctly diagnosed fistulous connection in all 21 patients. This included 6 patients with connections from the left circumflex artery (into the right chambers of the heart in 5 patients, and into the left ventricle in 1 patient), 10 patients with a fistula arising from the left anterior descending artery or left main coronary artery (with drainage into the right ventricle or main pulmonary artery), and 5 patients with a fistula from the right coronary artery (with drainage sites in the lateral aspect of the right ventricle, the low posterior right atrium, or the superior vena cava). In 4 of the 21 patients, angiography did not identify the precise site of a fistula into the coronary sinus or right ventricle. CONCLUSION: Color Doppler transesophageal echocardiography is useful in the diagnosis and in the precise localization of coronary artery fistulas

Adoption of Machine Learning Techniques to Enhance Classification Performance in Reactive Brain-Computer Interfaces

This paper proposes the adoption of an innovative algorithm to enhance the performance of highly wearable, reactive Brain-Computer Interfaces (BCIs), which exploit the Steady-State Visually Evoked Potential (SSVEP) paradigm. In particular, a combined time-domain/frequency-domain processing is performed in order to reduce the number of features of the brain signals acquired. Successively, these features are classified by means of an Artificial Neural Network (ANN) with a learnable activation function. In this way, the user intention can be translated into commands for external devices. The proposed algorithm was initially tested on a benchmark data set, composed by 35 subjects and 40 simultaneous flickering stimuli, obtaining performance comparable with the state of the art. Successively, the algorithm was also applied to a data set realized with highly wearable BCI equipment. In particular, (i) Augmented Reality (AR) smart glasses were used to generate the flickering stimuli necessary to the SSVEPs elicitation, and (ii) a single-channel EEG acquisition was conducted for each volunteer. The obtained results showed that the proposed strategy provides a significant enhancement in SSVEPs classification with respect to other state-of-the-art algorithms. This can contribute to improve reliability and usability of brain computer interfaces, thus favoring the adoption of this technology also in daily-life applications