Multifunctional Neurodevice for Recognition of Electrophysiological Signals and Data Transmission in an Exoskeleton ConstructionNatalia Nikolaevna Shusharina1,*, Evgeny Anatolyevich Bogdanov1, Vitaliy Andreevich Petrov1, Ekaterina Vladimirovna Silina2 and Maksim Vladimirovich Patrushev1
- *Corresponding Author:
- Shusharina NN
Immanuel Kant Baltic Federal University (IKBFU)
14 Nevskogo Str., Kaliningrad 236041, Russia
E-mail: [email protected]
Received Date: Jun 6, 2016; Accepted Date: Jul 21, 2016; Published Date: Aug 27, 2016
Citation: Shusharina NN, Bogdanov EA, Petrov VA, Silina EV, Patrushev MV (2016) Multifunctional Neurodevice for Recognition of Electrophysiological Signals and Data Transmission in an Exoskeleton Construction. Biol Med (Aligarh) 8:331. doi:10.4172/0974-8369.1000331.
Copyright: © 2016 Shusharina et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The most important task of health care is the increasing of life expectancy and improving the quality of life of the population. Taking into consideration the high numbers of disability, it is very relevant to establish a high-precision neurodevice, allowing the integration of people with limited functional abilities into the society. This paper presents the provisional results of a research work, the main aim of which was to develop the multifunctional neurodevice with the ability to transfer data to an exoskeleton construction. In the first phase, we selected the optimal way for a neurodevice layout that would be capable to measure the electromyography (EMG), electroencephalography (EEG), electroocu- lography (EOG), photoplethysmography, body temperature for a long period of time, and also motor activity with the ability to send data to a remote practitioner in real time. The software was developed. Experiments were conducted; at the same time the final (residual) graphical results were compared with the commercially available devices. The experimental results showed a high accuracy of the signals of EEG, EMG, EOG, photoplethysmography, thermometry, and physical activity. In conclusion, with the participation of 10 healthy volunteers, the study of hybridization of EEG and EMG signals was carried out, and it showed a significant advantage in comparison with only one modal system. It is expected that a further work will allow us to formulate optimal technical solutions based on the present knowledge of human physiology. This would be the basis for creating a highly accurate and safe multifunction neurodevice and would be able to meet the medico-social needs and would help to reintegrate people with disabilities into society by connecting them to the robotic technique, to the exoskeletons.