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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±10.70 years) 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:瀑布是不可预知的事故,造成的伤害可以在老年人严重,特别是那些患有慢性疾病。建议经常锻炼减少临床血压,预防和治疗高血压等慢性疾病。在“复杂性指数”(CI)的基础上,多尺度熵(MSE)算法,在最近的研究中得到了应用,显示一个人的适应征和外部扰动和重心晃动或稳定性的广泛使用的措施。多元多尺度熵(MMSE)是用于计算复杂度指数(CI)压力(COP)数据的中心的值先进算法。在这项研究中,我们采用了MSE和MMSE分析的24老人,慢性病患者(44%为女性,平均年龄,67.56±10.70年; 56%为男性)步态与任何心血管疾病,糖尿病,骨质疏松症或。一项为期12周的训练计划后,姿势稳定性的测量表明显著的改善。我们的结果表明的阻力训练,这可用于改善在老年人姿势稳定性,并表示MMSE算法将COP数据的计算CI分别优于多尺度熵(MSE)算法以识别所述平衡感的有益效果老年。

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