Abstract
There are several pathologies attacking the central nervous system and diverse therapies for each specific disease. These therapies seek as far as possible to minimize or offset the consequences caused by these types of pathologies and disorders in the patient. Therefore, comprehensive neurological care has been performed by neurorehabilitation therapies, to improve the patients’ life quality and facilitating their performance in society. One way to know how the neurorehabilitation therapies contribute to help patients is by measuring changes in their brain activity by means of electroencephalograms (EEG). EEG data-processing applications have been used in neuroscience research to be highly computing- and data-intensive. Our proposal is an integrated system of Electroencephalographic, Electrocardiographic, Bioacoustic, and Digital Image Acquisition Analysis to provide neuroscience experts with tools to estimate the efficiency of a great variety of therapies. The three main axes of this proposal are: parallel or distributed capture, filtering and adaptation of biomedical signals, and synchronization in real epochs of sampling. Thus, the present proposal underlies a general system, whose main objective is to be a wireless benchmark in the field. In this way, this proposal could acquire and give some analysis tools for biomedical signals used for measuring brain interactions when it is stimulated by an external system during therapies, for example. Therefore, this system supports extreme environmental conditions, when necessary, which broadens the spectrum of its applications. In addition, in this proposal sensors could be added or eliminated depending on the needs of the research, generating a wide range of configuration limited by the number of CPU cores, i.e., the more biosensors, the more CPU cores will be required. To validate the proposed integrated system, it is used in a Dolphin-Assisted Therapy in patients with Infantile Cerebral Palsy and Obsessive–Compulsive Disorder, as well as with a neurotypical one. Event synchronization of sample periods helped isolate the same therapy stimulus and allowed it to be analyzed by tools such as the Power Spectrum or the Fractal Geometry.
Highlights
Performing complex algorithms in less time demands a very high processing capacity, raising drastically the operating frequency, which is unfeasible due to the current limitations of processors such as the size of the transistors, the dissipation of the heat generated or a higher cost [1,2,3].Sensors 2020, 20, 6991; doi:10.3390/s20236991 www.mdpi.com/journal/sensorsTo deal with this very high processing demand, it is more appropriate to resort to multiprocessing, since it uses different processors where the workload is divided, it does not increase the working frequency of a processor
In this work the brain activity of both living beings is monitored during a Dolphin-Assisted Therapy, fulfilling the objective of achieving a measurement of brain activity
All the resources of the Intel i5 4570 microprocessor are configured as follows: the index i has a value with the total available workers and by means of a switch instruction it evaluates in an orderly way the access and the number of the CPU-Core, as follows: We summarize the proposed General Algorithm of this system by means of Figure 14, due to the huge amount of code developed, which is divided into many functions and subroutines
Summary
To deal with this very high processing demand, it is more appropriate to resort to multiprocessing, since it uses different processors where the workload is divided, it does not increase the working frequency of a processor. Derived from parallel-computing systems are distributed computing systems, which in the same way to distribute the processing among different computers, but instead of sharing memory, each computer has an individual one, sharing only the processed information [4]. Computers can be managed in different ways classified mainly as client–server or peer-to-peer architecture. In a client–server architecture, a computer will function as the head of the system or hub node NM and the other computers will be the hosts or secondary nodes
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