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Low-power laser therapy for carpal tunnel syndrome: effective optical power

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文摘 Low-power laser therapy has been used for the non-surgical treatment of mild to moderate carpal tunnel syndrome, although its efficacy has been a long-standing controversy. The laser parameters in low-power laser therapy are closely related to the laser effect on human tissue. To evaluate the efficacy of low-power laser therapy, laser parameters should be accurately measured and controlled, which has been ignored in previous clinical trials. Here, we report the measurement of the effective optical power of low-power laser therapy for carpal tunnel syndrome. By monitoring the backside reflection and scattering laser power from human skin at the wrist, the effective laser power can be inferred. Using clinical measurements from 30 cases, we found that the effective laser power differed significantly among cases, with the measured laser reflection coefficient ranging from 1.8% to 54%. The reflection coefficient for 36.7% of these 30 cases was in the range of 10–20%, but for 16.7% of cases, it was higher than 40%. Consequently, monitoring the effective optical power during laser irradiation is necessary for the laser therapy of carpal tunnel syndrome.
来源 Neural Regeneration Research ,2016,11(7):1180-1184 【核心库】
DOI 10.4103/1673-5374.187063
关键词 nerve regeneration ; peripheral nerve regeneration ; carpal tunnel syndrome ; laser therapy ; median nerve ; diode laser ; skin absorption ; skin reflection ; skin scattering ; laser power measurement ; laser therapy ; neural regeneration
地址

1. Department of Neurology, Tongji Hospital, Tongji University School of Medicine, Shanghai  

2. Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai  

3. Department of Rehabilitation Medicine, Tongji Hospital, Tongji University School of Medicine, Shanghai

语种 英文
文献类型 研究性论文
ISSN 1673-5374
学科 医药、卫生
基金 国家自然科学基金
文献收藏号 CSCD:5766890

参考文献 共 31 共2页

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引证文献 1

1 Bao Bingbo Brain remodeling after chronic median nerve compression in a rat model Neural Regeneration Research,2018,13(4):704-708
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