Prediction of body physiological parameter changes after experiencing infinity walk: A prospective observational view

IF 3.4 Q2 Health Professions
Smart Health Pub Date : 2025-12-01 Epub Date: 2025-09-21 DOI:10.1016/j.smhl.2025.100609
K. Murugavalli , R. Ramalakshmi , G. Vishnuvarthanan , M. Pallikonda Rajasekaran
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引用次数: 0

Abstract

To develop a clinical prediction tool for estimating the changes in the body physiological parameters during six months for the people practicing infinity walk. Comparing the parameters of normal walk and infinity walk for recording progression and forecasting conversion in the physiological parameters. All eight subjects pursue a balanced diet as per the instructions delivered by dietitian. Four participants planned to practice the infinity walk, in the open or in a room, going from south to north and vice versa. Another four participants are advised to practice regular walking. All the individuals walked for 30 min in both morning and evening. Eight participants, comprising 4 men and 4 women. The participants, who included healthy individuals, people with diabetes, people with hypertension and those with both diabetes and hypertension, ranged in age from 30 to 60. The primary outcome is changes in weight, blood sugar level, blood pressure, and oxygen saturation when infinity walk is employed as a stimulus. In this prospective observational study, four of the subjects in each group are practicing the infinity walk, while the remaining four are walking normally for an hour each day (morning and evening). Physiological data are collected weekly once by clinician for analysis. Statistical analysis has been performed using linear regression and Wilcoxon Rank sum test in order to predict the changes in the physiological parameters in the future, when the subjects continuing the procedure for a long duration. In order to increase prediction accuracy, the Generalized Regression Neural Network (GRNN) and the Gaussian Process Regression (GPR) model are combined to create the GPR-GRNN. The statistical analysis states that the better changes in the body physiological parameters can be identified on the subject's performing infinity walk than the subjects practicing normal walk. Participants who perform infinite walking over regular walking show progressively better results. The findings of this study laid the groundwork for a reliable prediction of improvements in body physiological parameters over a period of time when infinite walking is practiced. Also, the results can assist in justifying the reason for the suggestion/preference given by the doctors/researchers to patients/common people to select infinity walk as an exercise.
无限行走后身体生理参数变化的预测:前瞻性观察观点
目的:开发一种临床预测工具,用于评估练习无限步行的人在六个月内身体生理参数的变化。比较正常行走和无限行走的参数,记录生理参数的进展和预测转换。所有8名受试者都按照营养师的指示追求均衡饮食。四名参与者计划在露天或房间里练习无限行走,从南到北,反之亦然。另外四名参与者被建议经常散步。所有受试者早晚各步行30分钟。8名参加者,包括4男4女。参与者包括健康人、糖尿病患者、高血压患者以及糖尿病和高血压兼有的人,年龄从30岁到60岁不等。当无限行走作为刺激时,主要结果是体重、血糖水平、血压和血氧饱和度的变化。在这项前瞻性观察研究中,每组四名受试者练习无限行走,而其余四名受试者每天(早晚)正常行走一小时。临床医生每周收集一次生理数据进行分析。采用线性回归和Wilcoxon秩和检验进行统计分析,以预测受试者在长时间持续治疗过程中生理参数的变化。为了提高预测精度,将广义回归神经网络(GRNN)与高斯过程回归(GPR)模型相结合,建立了GPR-GRNN模型。统计分析表明,与进行正常行走的受试者相比,进行无限行走的受试者可以识别出更好的身体生理参数变化。与定期步行相比,无限步行的参与者表现出越来越好的结果。这项研究的发现为在一段时间内练习无限步行时身体生理参数的改善奠定了可靠的预测基础。此外,研究结果可以帮助证明医生/研究人员建议/偏爱患者/普通人选择无限行走作为一种运动的原因。
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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来源期刊
Smart Health
Smart Health Computer Science-Computer Science Applications
CiteScore
6.50
自引率
0.00%
发文量
81
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