Information System databases for Neuropsychology Tests: case study in Boston Naming Test

Shinta Estri Wahyuningrum, A. Sulastri, Ridwan Sanjaya
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Abstract

In the field of psychology, determining the psychological condition of a person’s can be done using various types of tests. Neuropsychology test is a battery test that means every person should be taken 11 test in a moment. Each test has a different objective, as an example, The Boston Naming test is used to measure a person's ability in the language domain. The data stored for each data in the Boston Naming Test (BNT) is around 130 fields. Each test has different specific data. This makes the data grow rapidly and requires a database design that can accommodate this need.There are many approaches can be done to store the database such a relational database and NoSQL database. When the data are stored using relational methods and amount of data are large, there can be a lack of time in both processing and tracking. This article proposes a system to store the result of the neuropsychological test using the NoSQL database approach with sample data in subtest BNT.
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神经心理学测试的信息系统数据库:波士顿命名测试的案例研究
在心理学领域,可以通过各种类型的测试来确定一个人的心理状况。神经心理学测试是一个电池测试,意味着每个人都要在一瞬间做11个测试。每个测试都有不同的目标,例如,波士顿命名测试用于衡量一个人在语言领域的能力。波士顿命名测试(BNT)中为每个数据存储的数据大约有130个字段。每个测试都有不同的具体数据。这使得数据快速增长,需要能够满足这种需求的数据库设计。有许多方法可以用来存储数据库,如关系数据库和NoSQL数据库。当使用关系方法存储数据并且数据量很大时,处理和跟踪都可能缺乏时间。本文提出了一种基于NoSQL数据库的神经心理测试结果存储系统,并将样本数据存储在子测试BNT中。
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