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Resistance Training Exercise Program for Intervention to Enhance Gait Function in Elderly Chronically Ill Patients: Multivariate Multiscale Entropy for Center of Pressure Signal Analysis

机译:抗性培训锻炼计划,以增强老年慢性病患者的步态功能:压力信号分析中心的多变量多尺度熵

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摘要

Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI), based on multiscale entropy (MSE) algorithm, has been applied in recent studies to show a person’s adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE) was advanced algorithm used to calculate the complexity index (CI) values of the center of pressure (COP) data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age,67.56±10.70years) with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE) algorithm to identify the sense of balance in the elderly.
机译:跌倒是不可预测的事故,所产生的伤害可能在老年人身上严重,特别是那些患有慢性病的人。建议通过减少临床血压来预防和治疗高血压和其他慢性疾病。基于多尺度熵(MSE)算法的“复杂性指数”(CI)已经应用于最近的研究,以显示人对内在和外部扰动的适应性,并且广泛使用的姿势摇摆或稳定性。多变量多体熵(MMSE)是先进的算法,用于计算压力中心(COP)数据的复杂性索引(CI)值。在这项研究中,我们应用了MSE&MMSE,分析了24名老年人,慢性病患者的步态功能(44%的女性; 56%男性;平均年龄,67.56±10.70年),具有心血管疾病,糖尿病或骨质疏松症。经过12周的培训计划后,姿势稳定性测量显示出显着改善。我们的结果表明抵抗训练的有益效果,可用于改善老年人的姿势稳定性,并表示MMSE算法计算COP数据的CI优于多尺度熵(MSE)算法,以识别平衡感老年。

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