Evaluation of Functional Abilities in 0-6 Year Olds: an Analysis with the eEarlyCare Computer Application.

María Consuelo Sáiz-Manzanares,Álvar Arnaiz-González,Raúl Marticorena-Sánchez

doi:10.3390/ijerph17093315

María Consuelo Sáiz-Manzanares, Álvar Arnaiz-González + Show 1 more

Open Access

https://doi.org/10.3390/ijerph17093315

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Abstract

The application of Industry 4.0 to the field of Health Sciences facilitates precise diagnosis and therapy determination. In particular, its effectiveness has been proven in the development of personalized therapeutic intervention programs. The objectives of this study were (1) to develop a computer application that allows the recording of the observational assessment of users aged 0–6 years old with impairment in functional areas and (2) to assess the effectiveness of computer application. We worked with a sample of 22 users with different degrees of cognitive disability at ages 0–6. The eEarlyCare computer application was developed with the aim of allowing the recording of the results of an evaluation of functional abilities and the interpretation of the results by a comparison with "normal development". In addition, the Machine Learning techniques of supervised and unsupervised learning were applied. The most relevant functional areas were predicted. Furthermore, three clusters of functional development were found. These did not always correspond to the disability degree. These data were visualized with distance map techniques. The use of computer applications together with Machine Learning techniques was shown to facilitate accurate diagnosis and therapeutic intervention. Future studies will address research in other user cohorts and expand the functionality of their application to personalized therapeutic programs.

Highlights

Advances in technology within Industry 4.0, especially those related to the use of computer applications, allow the derivation of data to servers and to software that can be implemented for the technical analysis of data mining
In view of the above, the objectives of this work were (1) to develop a computer application that allows the recording of the observational assessment of users affected in areas of functional development from 0 to 6 years of age and (2) to test the computer application on users with functional ages of 0–6 years
With respect to the first objective (“to develop a computer application that allows the recording of the observational assessment of users affected in areas of functional development from 0 to 6 years of age”), the computer application eEarlyCare was developed

Summary

Introduction

Advances in technology within Industry 4.0, especially those related to the use of computer applications, allow the derivation of data to servers and to software that can be implemented for the technical analysis of data mining This has generated a revolution in different fields of knowledge. To achieve this, supervised and unsupervised learning Data Mining techniques are applied to facilitate prediction, discovery of behavioural patterns, classification, and grouping of users according to different characteristics that are not established a priori. This facilitates the detection of coincidences in assessed groups [4]. These aspects are very important, since they will help professionals with the development of differential diagnoses and the application of personalized therapeutic intervention programs [5]

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