Bradykinesia Detection System Using IoT Based Health Care System for Parkinson’s Disease Patient

S. F. Desyansah, M. N. Mohammed, S. Al-Zubaidi, Halim Syamsudin, Ibrahim Abdullah, E. Yusuf
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引用次数: 2

Abstract

Parkinson’s disease (PD) is affecting around 1.47% of people aged 60 years or older and considered as a second most common movement disorder. It is resulted due to a reduction in the dopamine level. One of the PD characteristics is smallness and slowness of executed movement, called Bradykinesia. This study aims to develop an early detection system based on frequencies measurement of movement and the interpretation result would be analyzed with quantitative method using validity, coefficient determinant and ANOVA test. The data retrieve measurement frequencies. There are variables that will be analyzed the value from x,y,z axis and the value of frequency. As the results of the analysis of the validity test, this study uses the Pearson correlation test with a p-value of 0.538, Sig. (2-tailed) of 0.006, where the value interpreted that there was a reasonably strong correlation between the two variables with a significance level of 0.01 or 1%. An according to the value of adjusted R square is 79.7% the dependent variable represented the independent variable, whereas 20.3% is influenced by other parameter that not employed in this study. Also, the degree of freedom in ANOVA test is 3 with 25 numbers of samples.
基于物联网的帕金森病患者运动迟缓检测系统
帕金森病(PD)影响了大约1.47%的60岁或以上的人,被认为是第二大常见的运动障碍。这是由于多巴胺水平降低造成的。PD的特征之一是执行运动的小而慢,称为运动迟缓。本研究旨在开发一套基于运动频率测量的早期检测系统,并利用效度、行列式系数和方差分析等定量方法对判读结果进行分析。数据检索测量频率。需要分析的变量有x,y,z轴的值和频率的值。作为效度检验的分析结果,本研究使用Pearson相关检验,p值为0.538,Sig(双尾)为0.006,该值解释两个变量之间存在相当强的相关性,显著性水平为0.01或1%。根据调整后的R方值,有79.7%的因变量代表自变量,20.3%的因变量受到本研究未采用的其他参数的影响。ANOVA检验的自由度为3,样本个数为25。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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