目的 观察基于双重任务的步行情景模拟训练对脑卒中患者的影响。方法 选取2021年10月-2022年12月红河州第三人民医院收治的64例脑卒中患者为研究对象,随机分为治疗组和对照组,各32例。对照组给予常规康复训练及步行情景模拟训练治疗,治...目的 观察基于双重任务的步行情景模拟训练对脑卒中患者的影响。方法 选取2021年10月-2022年12月红河州第三人民医院收治的64例脑卒中患者为研究对象,随机分为治疗组和对照组,各32例。对照组给予常规康复训练及步行情景模拟训练治疗,治疗组给予常规康复训练及基于双重任务的步行情景模拟训练治疗,2组患者均治疗4周。采用单任务起立-步行测试(timed up and go test,TUG)及双任务TUG评估患者步行功能,采用Fugl-Meyer运动功能评定法(Fugl-Meyer assessment,FMA)下肢运动功能评定(FMA-lower limb,FMA-LL)评估患者下肢功能,采用Berg平衡量表(ber g balance scale,BBS)评估患者平衡功能,采用Barthle指数(barthel index,BI)评估患者日常生活能力。结果 治疗后,2组患者单任务TUG时间比较,差异无统计学意义(P>0.05)。治疗后,治疗组双任务TUG时间短于对照组(P<0.05)。治疗后,治疗组FMA-LL评分、BBS评分、BI评分均高于对照组(P<0.05)。结论 在常规康复治疗基础上联合双重任务的步行情景模拟训练能有效改善脑卒中患者的步行能力、下肢功能、平衡功能,提高患者日常生活能力。展开更多
The decentralized fuzzy inference method(DFIM)is employed as an optimization technique to reconstruct time-and space-dependent heat flux of two-dimensional(2D)participating medium.The forward coupled radiative and con...The decentralized fuzzy inference method(DFIM)is employed as an optimization technique to reconstruct time-and space-dependent heat flux of two-dimensional(2D)participating medium.The forward coupled radiative and conductive heat transfer problem is solved by a combination of finite volume method and discrete ordinate method.The reconstruction task is formulated as an inverse problem,and the DFIM is used to reconstruct the unknown heat flux.No prior information on the heat flux distribution is required for the inverse analysis.All retrieval results illustrate that the time-and spacedependent heat flux of participating medium can be exactly recovered by the DFIM.The present method is proved to be more efficient and accurate than other optimization techniques.The effects of heat flux form,initial guess,medium property,and measurement error on reconstruction results are investigated.Simulated results indicate that the DFIM is robust to reconstruct different kinds of heat fluxes even with noisy data.展开更多
文摘目的 观察基于双重任务的步行情景模拟训练对脑卒中患者的影响。方法 选取2021年10月-2022年12月红河州第三人民医院收治的64例脑卒中患者为研究对象,随机分为治疗组和对照组,各32例。对照组给予常规康复训练及步行情景模拟训练治疗,治疗组给予常规康复训练及基于双重任务的步行情景模拟训练治疗,2组患者均治疗4周。采用单任务起立-步行测试(timed up and go test,TUG)及双任务TUG评估患者步行功能,采用Fugl-Meyer运动功能评定法(Fugl-Meyer assessment,FMA)下肢运动功能评定(FMA-lower limb,FMA-LL)评估患者下肢功能,采用Berg平衡量表(ber g balance scale,BBS)评估患者平衡功能,采用Barthle指数(barthel index,BI)评估患者日常生活能力。结果 治疗后,2组患者单任务TUG时间比较,差异无统计学意义(P>0.05)。治疗后,治疗组双任务TUG时间短于对照组(P<0.05)。治疗后,治疗组FMA-LL评分、BBS评分、BI评分均高于对照组(P<0.05)。结论 在常规康复治疗基础上联合双重任务的步行情景模拟训练能有效改善脑卒中患者的步行能力、下肢功能、平衡功能,提高患者日常生活能力。
基金Project supported by the Natural Science Foundation of Chongqing(CSTC,Grant No.2019JCYJ-MSXMX0441).
文摘The decentralized fuzzy inference method(DFIM)is employed as an optimization technique to reconstruct time-and space-dependent heat flux of two-dimensional(2D)participating medium.The forward coupled radiative and conductive heat transfer problem is solved by a combination of finite volume method and discrete ordinate method.The reconstruction task is formulated as an inverse problem,and the DFIM is used to reconstruct the unknown heat flux.No prior information on the heat flux distribution is required for the inverse analysis.All retrieval results illustrate that the time-and spacedependent heat flux of participating medium can be exactly recovered by the DFIM.The present method is proved to be more efficient and accurate than other optimization techniques.The effects of heat flux form,initial guess,medium property,and measurement error on reconstruction results are investigated.Simulated results indicate that the DFIM is robust to reconstruct different kinds of heat fluxes even with noisy data.
