首页|基于温度监测的糖尿病足预防性智能鞋袜研究进展

基于温度监测的糖尿病足预防性智能鞋袜研究进展

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为尽早发现、及时干预糖尿病患者足部疾病的发展,提高糖尿病足预防性智能产品预测能力的敏感度和特异度,基于文献回顾,对比了不同类型糖尿病患者与健康人群的足底温度特征差异,分析了糖尿病足的温度预测指标的提取和阈值设置,发现单、双侧足部温度及足部应变温度均能用于预防糖尿病足疾病的发生,但以双足对称点的温差 2.2℃作为糖尿病足疾病预测阈值应用最广.讨论了基于糖尿病足温度监测需求的智能测温鞋袜产品的设计开发,发现智能袜的研发程度比智能鞋更为成熟,不同产品间温度传感器的数量和放置区域存在差异,其中大拇趾底、第1 跖骨头、第5 跖骨头和足跟这4 个区域具有高度一致性.未来研究可针对不同风险程度的糖尿病足进行温度分级,结合压力、湿度等其他指标建立多指标风险预测模型,并综合鞋和袜进行系统性多功能研发.
Research progress on smart footwear for monitoring temperature in diabetic foot
Significance The diabetic foot is a serious chronic complications in diabetic patients and is characterized by high rates of disability,death,and recurrence.50%of diabetic foot ulcers and amputations can be avoided through early screening,but only 15.7%of diabetic patients are screened regularly.Studies have shown that monitoring the skin temperature of diabetic patients'feet helps to detect foot abnormalities,and reduce the risk of primary and secondary diabetic foot.Currently,smart footwear for monitoring foot temperature in the diabetic foot has developed,such as Siren Diabetic Socks and SmartSox Socks.However,the willingness of patients for wearing diabetic footwear is low,and medical professionals suggest that there is still a lack of strong evidence for the diagnostic value of such products.Therefore,a comprehensive and scientific analysis of smart footwear for monitoring temperature in the diabetic foot can help improve the systematic understanding of these products among diabetic patients and related researchers,increase the popularity and usage rate,and provide theoretical references for future research.Progress In order to systematically and objectively understand the mechanism and product efficacy of smart footwear for monitoring foot temperature,the differences in plantar temperature characteristics between different types of diabetic patients and healthy people were compared.Thermograms from the healthy people showed a symmetrical butterfly pattern with the medial arches showing the highest temperatures,while in diabetics,due to inflammation caused by neuropathy,abnormal thermoregulation,and local ischemia caused by peripheral arterial disease,the foot temperature is often higher than that of healthy feet,and the distribution is irregular,with higher temperatures in areas at high risk of ulceration.In order to fully extract the predictive value of temperature,there mainly exist three types of index extraction methods,i.e.,thermal symmetry of foot,in dependent limb regional temperature difference,and temperature stress analysis.A 2.2℃difference between contralateral spots is the most widely used as the predictive threshold of diabetic foot disease,and the predictive sensitivity and specificity are often improved by continuous duration-assisted analysis.Recently,smart footwear targeting foot temperature monitoring has been developed.The Optical-Fiber-Based Smart Sock has the advantages of multi-index monitoring,comfortable and reusable.However,there are still differences in the number of temperature sensors and monitoring areas between products.The main monitoring areas are heel,medial midfoot,first metatarsal head,fifth metatarsal head,and first toe.Conclusion and Prospect The effectiveness of using temperature monitoring to prevent diabetic foot has been unanimously recognized by researchers.It is clinically meaningful to use the temperature difference of 2.2℃between contralateral spots as the prediction threshold for diabetic foot.Nontheless,the individual baseline temperature differences should be taken into consideration,assisted with other indicators such as the duration of temperature difference and pressure,so as to improve the predictive sensitivity and specificity of smart footwear.In the future,the risk level can be identified based on the foot temperature values and distribution patterns of diabetic patients under different activity intensities based on big data,and other indicators such as pressure,shear stress,toe range of motion,humidity,pH,and sweat-based glucose level can be studied in depth to predict the potential value of diabetic foot risk,explore the relationship between the indicators,and dissect the diabetic foot development risk mechanism together with skin temperature.In addition,machine learning can be used to optimize early warning algorithms,automatically calculating and updating the typical foot temperature pattern individualized.Finally,the overall system of shoes and socks needs to be comprehensively explored regarding the care and prevention of diabetic foot.

diabetic footskin temperaturetemperature sensorsmart wearable productfootwearrisk prediction

施楚、李俊、王云仪

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东华大学服装与艺术设计学院,上海 200051

东华大学现代服装设计与技术教育部重点实验室,上海 200051

糖尿病足 皮肤温度 温度传感器 智能可穿戴 鞋袜 风险预测

中央高校基本科研业务费专项基金项目上海市科学技术委员会"科技创新行动计划""一带一路"国际合作项目

2232023G-0821130750100

2024

纺织学报
中国纺织工程学会

纺织学报

CSTPCD北大核心
影响因子:0.699
ISSN:0253-9721
年,卷(期):2024.45(7)