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Measurement and modeling of hand grip strength and endurance of Malaysian female

机译:马来西亚女性握力和耐力的测量和建模

摘要

Gripping is an important physical activity in daily routine. The capability of muscular force during gripping can be evaluated in terms of Hand grip Strength (HGS) and Hand grip Endurance (HGE). There are two types of movements that are associated with HGE which are dynamic or repetitive (HGEd) and static (HGE5) movements. In the literature, there are many studies which have been performed to investigate the relationship between demographics and hand anthropometric dimensions factors with HGS. These factors have been used as predictive factor for rehabilitation and recovery. However there is lack of studies showing the relationship combined of demographics and hand anthropometric dimensions to HGE which are important factors in hand rehabilitation and recovery. The aim of this project is to develop predictive model of young female HGS and HGE based on the demographic and hand anthropometric collected. Thus, the specific objectives of this study are; (1) to develop a optimal grip size electronic hand grip strength measuring system that records and analyze the HGS and HGE time series signals, (2) to determine the correlation between demographic and hand anthropometric dimensions, and the HGS as well as HGE of young Malaysian female, and (3) to develop an intelligent predictive model of HGS and HGE. There are three assessments in evaluating the HGS, HOEd and HGEs: single- repetition, 20-repetition and 30-udseconds static hold. In addition 6 demographics and 9 hand anthropometrics data are recorded from each volunteer in order to investigate the correlationudbetween HGS, HGEd and HGEs and these data. By using all the associated data, the predictive model of HGS, HOEd and HGEs are developed using Adaptive Neuro Fuzzy Inference System (ANFIS) model. In this study 45 females of the age group 18 to 30 years were recruited. The assessment of grip strength and endurance was measured using the fabricated hand grip measuring device and followed the America Society of Hand Therapy (ASHT) protocols of seating to maintain the consistency of each volunteer's measurement. By comparing with similar study performed on western population, the results show that the female HGS in this study is much higher probably due to optimal grip size of the fabricated measuring device.udMeanwhile for HGEd and HGEs, these measurements are lower and it is found that the hand dominant was significantly stronger than non-hand dominant for HGS, HGEd and HGEs. In addition the HGS was correlated with weight, Body Mass Index (BMI), hand breadth across thumb, wrist thickness and wrist circumference. Meanwhile HGEd and HGEs were correlated with age and occupation but not correlated with any of the hand anthropometric dimensions. Non-parametric predictive model based on ANFIS is used to develop the predictive HGS and HE model. In developing predictive ANFIS modeling, the input selection was executed and the most significant inputs with respect toudHGS, HGEd and HGEs for both hands are obtained. In ANFIS model, there is small discrepancy between actual and predicted average output for training and checking datasets. Nevertheless, this study has shown that ANFIS can be potentially used as an effective predictive model with larger dataset.
机译:抓地力是日常生活中的重要体育锻炼。握力过程中的肌肉力量可根据握力强度(HGS)和握力耐力(HGE)进行评估。与HGE相关的运动有两种,即动态或重复(HGEd)和静态(HGE5)运动。在文献中,已经进行了许多研究以调查人口统计数据与手部人体测量尺寸因子与HGS的关系。这些因素已被用作康复和恢复的预测因素。但是,缺乏研究表明人口统计学和手部人体测量学尺寸与HGE的关系,这是手部康复和恢复的重要因素。该项目的目的是根据收集的人口统计数据和手部人体测量学,开发年轻女性HGS和HGE的预测模型。因此,这项研究的具体目标是: (1)开发最佳的握把大小电子握力测量系统,该系统记录并分析HGS和HGE时间序列信号;(2)确定人口统计学和手部人体测量学尺寸以及HGS和年轻人的HGE之间的相关性马来西亚女性,以及(3)建立HGS和HGE的智能预测模型。在评估HGS,HOEd和HGE时需要进行三种评估:单次重复,20次重复和30秒的静态保持。另外,每个志愿者记录了6个人口统计学数据和9个人体测量学数据,以研究HGS,HGEd和HGE与这些数据之间的相关性。通过使用所有相关数据,使用自适应神经模糊推理系统(ANFIS)模型开发了HGS,HOEd和HGE的预测模型。在这项研究中,招募了45位18至30岁的女性。握力和耐力的评估是使用预制的握力测量设备进行的,并遵循美国手部学会坐位(ASHT)协议以保持每个志愿者测量的一致性。通过与对西方人群进行的类似研究进行比较,结果表明,该研究中的女性HGS可能更高,这可能是由于所制造的测量设备的最佳握持尺寸所致。 ud同时,对于HGEd和HGE,这些测量值较低,并且发现HGS,HGEd和HGE的手优势明显强于非手优势。另外,HGS与体重,体重指数(BMI),拇指的手幅,手腕粗细和手腕周长相关。同时,HGEd和HGEs与年龄和职业相关,但与任何手部人体测量学尺寸均不相关。使用基于ANFIS的非参数预测模型来开发HGS和HE预测模型。在开发预测性ANFIS建模中,执行了输入选择,并获得了关于 udHGS,HGEd和HGE的两只手的最重要输入。在ANFIS模型中,用于训练和检查数据集的实际和预测平均输出之间存在很小的差异。然而,这项研究表明,ANFIS可以潜在地用作具有较大数据集的有效预测模型。

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    Nor Hadzfizah Mohd Radi;

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