This paper presents a glove designed to assess the viability of communication between a deaf-blind user and his/her interlocutor through a vibrotactile device. This glove is part of the TactileCom system, where communication is bidirectional through a wireless link, so no contact is required between the interlocutors. Responsiveness is higher than with letter by letter wording. The learning of a small set of concepts is simpler and the amount learned can be increased at the user's convenience. The number of stimulated fingers, the keying frequencies and finger response were studied. Message identification rate was 97% for deaf-blind individuals and 81% for control subjects. Identification by single-finger stimulation was better than by multiple-finger stimulation. The interface proved suitable for communication with deaf-blind individuals and can also be used in other conditions, such as multilingual or noisy environments.
This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.
How to correctly measure the exposure of general public to extremely low-frequency (ELF) radiation is a key issue for ELF epidemiological studies. This paper proposes a measurement procedure to accurately assess the exposure of people to electric and magnetic field in the frequency band from 5 Hz to 100 kHz in buildings and their premises. As ELF radiation could be particularly harmful to children, the measurement procedure is focused on exposure to ELF in schools. Thus, the students' exposure to ELF fields can be assessed by correlating the ELF measurements to the hours of school activity. In this paper, the measurement protocol was applied to study the ELF exposure on students from García Quintana primary school in Valladolid, Spain. The campaign of measurements for ELF exposure assessment in this primary school was of great interest for the Regional Council of Public Health because of the social alarm generated by the presence of a significant number cancer cases in children.
Next generation of Internet of Things (IoT) services imposes stringent requirements to the future networks that current ones cannot fulfill. 5G is a technology born to give response to those requirements. However, the deployment of 5G is also accompanied by profound architectural changes in the network, including the introduction of technologies like multi-access edge computing (MEC), software defined networking (SDN), and network function virtualization (NFV). In particular, NFV poses diverse challenges like virtual network function (VNF) placement and chaining, also called VNF-mapping. In this paper, we present an algorithm that solves VNF-placement and chaining in a metro WDM optical network equipped with MEC resources. Therefore, it solves the VNF-mapping in conjunction with the virtual topology design of the underlying optical backhaul network. Moreover, a version of the method providing protection against node failures is also presented. A simulation study is presented to show the importance of designing the three problems jointly, in contrast to other proposals of the literature that do not take the design of the underlying network into consideration when solving that problem. Furthermore, this paper also shows the advantages of using collaboration between MEC nodes to solve the VNF-mapping problem and the advantage of using shared protection schemes. The new algorithm outperforms other proposals in terms of both service blocking ratio, and number of active CPUs (thus reducing energy consumption). Finally, the impact of deploying different physical topologies for the optical backhaul network is also presented.
DC-offset and DC-suppression are key parameters in bioelectric amplifiers. However, specific DC analyses are not often explained. Several factors influence the DC-budget: the programmable gain, the programmable cut-off frequencies for high pass filtering and, the low cut-off values and the capacitor blocking issues involved. A new intermediate stage is proposed to address the DC problem entirely. Two implementations were tested. The stage is composed of a programmable gain amplifier (PGA) with DC-rejection and low output offset. Cut-off frequencies are selectable and values from 0.016 to 31.83 Hz were tested, and the capacitor deblocking is embedded in the design. Hence, this PGA delivers most of the required gain with constant low output offset, notwithstanding the gain or cut-off frequency selected.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.