Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean–atmosphere coupled processes make the region’s climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air–sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air–sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.Universidad de Costa Rca/[805-B7-507]/UCR/Costa RicaCRYOPERU/[144-2015]//PerúUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

Toward higher-performance bionic limbs for wider clinical use

Funding Information: We were supported by the Academy of Finland (I.V.), Austrian Federal Ministry of Science (A.S. and O.C.A.), Bertarelli Foundation (S.M.), the European Union (A.S., D.F., K.-P.H., O.C.A., R.B. and S.M.), the European Research Council (A.S., D.F. and O.C.A.), German Federal Ministry of Education and Research BMBF (K.-P.H. and T.S.), the German National Research Foundation (T.S.), the Royal British Legion (A.M.J.B.), the Swedish Innovation Agency (VINNOVA) (R.B.), the Swedish Research Council (R.B.), the Swiss National Competence Center in Research (NCCR) in Robotics (S.M.), US Department of Defense (R.B. and H.H.), US Department of Veterans Affairs (D.T.), US Department of Veterans Affairs Rehabilitation Research and Development Service (R.F.ff.W.), US National Institute on Disability, Independent Living and Rehabilitation Research (H.H. and T.K.), US National Institutes of Health (D.T., H.H., L.J.H. and R.F.ff.W.), US National Institute on Neurological Disorders and Stroke (R.F.ff.W.), USNational Institute on Bioimaging and Bioengineering (R.F.ff.W.) and US National Science Foundation (H.H.). Publisher Copyright: © 2021, Springer Nature Limited.Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.Peer reviewe