基于温度监测的糖尿病足预防性智能鞋袜研究进展

doi:10.13475/j.fzxb.20230103002

纺织学报 ›› 2024, Vol. 45 ›› Issue (07): 240-247.doi: 10.13475/j.fzxb.20230103002

基于温度监测的糖尿病足预防性智能鞋袜研究进展

施楚¹, 李俊¹^,²(), 王云仪¹^,²

1.东华大学服装与艺术设计学院, 上海 200051
2.东华大学现代服装设计与技术教育部重点实验室, 上海 200051

收稿日期:2023-01-18 修回日期:2023-08-01 出版日期:2024-07-15 发布日期:2024-07-15
通讯作者: 李俊(1970—),男,教授,博士。主要研究方向为功能防护服装及其舒适性。E-mail:lijun@dhu.edu.cn。
作者简介:施楚(1997—),女,博士生。主要研究方向为服装舒适性与功能。
基金资助:
中央高校基本科研业务费专项基金项目(2232023G-08);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(21130750100)

Research progress on smart footwear for monitoring temperature in diabetic foot

SHI Chu¹, LI Jun¹^,²(), WANG Yunyi¹^,²

1. College of Fashion and Design, Donghua University, Shanghai 200051, China
2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China

Received:2023-01-18 Revised:2023-08-01 Published:2024-07-15 Online:2024-07-15

摘要/Abstract

摘要：

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。

关键词: 糖尿病足, 皮肤温度, 温度传感器, 智能可穿戴, 鞋袜, 风险预测

Abstract:

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.

Key words: diabetic foot, skin temperature, temperature sensor, smart wearable product, footwear, risk prediction

中图分类号:

TS943.77

施楚, 李俊, 王云仪. 基于温度监测的糖尿病足预防性智能鞋袜研究进展[J]. 纺织学报, 2024, 45(07): 240-247.

SHI Chu, LI Jun, WANG Yunyi. Research progress on smart footwear for monitoring temperature in diabetic foot[J]. Journal of Textile Research, 2024, 45(07): 240-247.

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链接本文: http://www.fzxb.org.cn/CN/10.13475/j.fzxb.20230103002

http://www.fzxb.org.cn/CN/Y2024/V45/I07/240

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参考文献 46

[1]	张会峰, 许樟荣, 冉兴无. 糖尿病足的相关定义和标准[J]. 中华糖尿病杂志, 2020, 12(6): 363-368.
	ZHANG Huifeng, XU Zhangrong, RANG Xingwu. Definition and standards of diabetic foot[J]. Chinese Journal of Diabetes Mellitus, 2020, 12(6): 363-368.
[2]	中华医学会糖尿病学分会,中华医学会感染病学分会, 中华医学会组织修复与再生分会. 中国糖尿病足防治指南(2019版)(Ⅴ)[J]. 中华糖尿病杂志, 2019, 11(6): 92-108.
	Chinese Diabetes Society,Chinese Society of Infectious Diseases, Chinese Society for Tissue Repair and Regeneration. Chinese guideline on prevention and management of diabetic foot (2019 edition)(V)[J]. Chinese Journal of Diabetes Mellitus, 2019, 11(6): 92-108.
[3]	李欣仪, 罗文静, 赵楠, 等. 糖尿病患者合并足部皮肤问题现状及其影响因素[J]. 解放军护理杂志, 2020, 37(10): 5-9.
	LI Xinyi, LUO Wenjing, ZHAO Nan, et al. The status quo and influence factors of foot skin problems among patients with diabetes[J]. Nursing Journal of Chinese People's Liberation Army, 2020, 37(10): 5-9.
[4]	罗颖琪, 李炳辉, 许樟荣, 等. 国际糖尿病足工作组:糖尿病足溃疡预防指南——《国际糖尿病足工作组:糖尿病足防治国际指南(2019)》的一部分[J]. 感染、炎症、修复, 2019, 20(3): 140-157.
	LUO Yingqi, LI Binghui, XU Zhangrong, et al. International working group on the diabetic foot guideline on the prevention of foot ulcers in persons with diabetes: part of the 2019 IWGDF guidelines on the prevention and management of diabetic foot disease[J]. Infection,Inflammation,Repair, 2019, 20(3): 140-157.
[5]	李欣仪, 周秋红, 赵楠, 等. 糖尿病患者足部风险筛查现状及影响因素研究[J]. 护理学杂志, 2021, 36(9): 33-36.
	LI Xinyi, ZHOU Qiuhong, ZHAO Nan, et al. Foot risk screening and its influencing factors among patients with diabetes[J]. Journal of Nursing Science, 2021, 36(9): 33-36.
[6]	MONTEIRO-SOARES M, BOYKO E J, RIBEIRO J, et al. Predictive factors for diabetic foot ulceration: a systematic review: predictive factors for diabetic foot ulceration[J]. Diabetes/Metabolism Research and Reviews, 2012, 28(7): 574-600.
[7]	HAYASHI A, SHICHIRI M. Use of noncontact infrared skin thermometer for peripheral arterial disease screening in patients with and without diabetes[J]. Angiology, 2020, 71(7): 650-657. doi: 10.1177/0003319720920162 pmid: 32319312
[8]	NETTEN J J, RASPOVIC A, LAVERY L A, et al. Prevention of foot ulcers in the at-risk patient with diabetes: a systematic review[J]. Diabetes/Metabolism Research and Reviews, 2020. DOI:10.1002/dmrr.2701.
[9]	HOUGHTON V J, BOWER V M, CHANT D C. Is an increase in skin temperature predictive of neuropathic foot ulceration in people with diabetes? a systematic review and meta-analysis[J]. Journal of Foot and Ankle Research, 2013, 6(1): 31. doi: 10.1186/1757-1146-6-31 pmid: 23919736
[10]	黄悦, 汪清, 陈丹, 等. 足部皮肤温度与糖尿病足溃疡风险相关性的meta分析[J]. 实用预防医学, 2022, 29(9): 1059-1063.
	HUANG Yue, WANG Qing, CHEN Dan, et al. Meta-analysis on correlation between foot skin temperature and the risk of diabetic foot ulcers[J]. Practical Preventive Medicine, 2022, 29(9): 1059-1063.
[11]	MOULAEI K, MALEK M, SHEIKHTAHERI A. A smart wearable device for monitoring and self-management of diabetic foot: a proof of concept study[J]. International Journal of Medical Informatics, 2021. DOI: 10.1016/j.ijmedinf.2020.104343.
[12]	NOVICE T, VEMURI C, GILBERT C, et al. Do patients with diabetes mellitus want wearable technology to prevent diabetic foot ulcers?[J]. Journal of Diabetes Science and Technology, 2019, 13(4): 799-800. doi: 10.1177/1932296819851776 pmid: 31113260
[13]	MACDONALD E M, PERRIN B M, KINGSLEY M I C. Factors influencing Australian podiatrists' behavioural intentions to adopt a smart insole into clinical practice: a mixed methods study[J]. Journal of Foot and Ankle Research, 2020, 13(1): 28. doi: 10.1186/s13047-020-00396-x pmid: 32487234
[14]	CHAN A W, MACFARLANE I A, BOWSHER D R. Contact thermography of painful diabetic neuropathic foot[J]. Diabetes Care, 1991, 14(10): 918-922. pmid: 1773693
[15]	SUN P C, JAO S H E, CHENG C K. Assessing foot temperature using infrared thermography[J]. Foot & Ankle International, 2005, 26(10): 847-853.
[16]	ASTASIO-PICADO A, ESCAMILLA MARTÍNEZ E, MARTÍNEZ NOVA A, et al. Thermal map of the diabetic foot using infrared thermography[J]. Infrared Physics & Technology, 2018, 93: 59-62.
[17]	BAGAVATHIAPPAN S, PHILIP J, JAYAKUMAR T, et al. Correlation between plantar foot temperature and diabetic neuropathy: a case study by using an infrared thermal imaging technique[J]. Journal of Diabetes Science and Technology, 2010, 4(6): 1386-1392. doi: 10.1177/193229681000400613 pmid: 21129334
[18]	GATT A, CASSAR K, FALZON O, et al. The identification of higher forefoot temperatures associated with peripheral arterial disease in type 2 diabetes mellitus as detected by thermography[J]. Primary Care Diabetes, 2018, 12(4): 312-318. doi: S1751-9918(18)30002-0 pmid: 29396205
[19]	YAVUZ M, ERSEN A, HARTOS J, et al. Temperature as a causative factor in diabetic foot ulcers: a call to revisit ulceration pathomechanics[J]. Journal of the American Podiatric Medical Association, 2019, 109(5): 345-350. doi: 10.7547/17-131 pmid: 30427732
[20]	HERNANDEZ-CONTRERAS D A, PEREGRINA-BARRETO H, RANGEL-MAGDALENO J de J, et al. Plantar thermogram database for the study of diabetic foot complications[J]. IEEE Access, 2019, 7: 161296-161307.
[21]	HERNANDEZ-CONTRERAS D, PEREGRINA-BARRETO H, RANGEL-MAGDALENO J, et al. Narrative review: diabetic foot and infrared thermography[J]. Infrared Physics & Technology, 2016, 78: 105-117.
[22]	VAN NETTEN J J, VAN BAAL J G, LIU C, et al. Infrared thermal imaging for automated detection of diabetic foot complications[J]. Journal of Diabetes Science and Technology, 2013, 7(5): 1122-1129. doi: 10.1177/193229681300700504 pmid: 24124937
[23]	VAN NETTEN J J, PRIJS M, VAN BAAL J G, et al. Diagnostic values for skin temperature assessment to detect diabetes-related foot complications[J]. Diabetes Technology & Therapeutics, 2014, 16(11): 714-721.
[24]	ARMSTRONG D G, HOLTZ-NEIDERER K, WENDEL C, et al. Skin temperature monitoring reduces the risk for diabetic foot ulceration in high-risk patients[J]. The American Journal of Medicine, 2007, 120(12): 1042-1046.
[25]	WIJLENS A M, HOLLOWAY S, BUS S A, et al. An explorative study on the validity of various definitions of a 2.2 ℃ temperature threshold as warning signal for impending diabetic foot ulceration: Exploring the validity of various definitions of a 2.2 ℃ temperature threshold[J]. International Wound Journal, 2017, 14(6): 1346-1351.
[26]	MING A, WALTER I, ALHAJJAR A, et al. Study protocol for a randomized controlled trial to test for preventive effects of diabetic foot ulceration by telemedicine that includes sensor-equipped insoles combined with photo documentation[J]. Trials, 2019, 20(1): 521.
[27]	FRYKBERG R G, GORDON I L, REYZELMAN A M, et al. Feasibility and efficacy of a smart mat technology to predict development of diabetic plantar ulcers[J]. Diabetes Care, 2017, 40(7): 973-980. doi: 10.2337/dc16-2294 pmid: 28465454
[28]	GATT A, FALZON O, CASSAR K, et al. Establishing differences in thermographic patterns between the various complications in diabetic foot disease[J]. International Journal of Endocrinology, 2018. DOI: 10.1155/2018/ 9808295.
[29]	LAVERY L A, PETERSEN B J, LINDERS D R, et al. Unilateral remote temperature monitoring to predict future ulceration for the diabetic foot in remission[J]. BMJ Open Diabetes Research and Care, 2019, 7(1): e000696.
[30]	NIEMANN U, SPILIOPOULOU M, MALANOWSKI J, et al. Plantar temperatures in stance position: a comparative study with healthy volunteers and diabetes patients diagnosed with sensoric neuropathy[J]. EBioMedicine, 2020.DOI: /10.1016/j.ebiom.2020.102712.
[31]	BEACH C, COOPER G, WEIGHTMAN A, et al. Monitoring of dynamic plantar foot temperatures in diabetes with personalised 3D-printed wearables[J]. Sensors, 2021, 21(5): 1717.
[32]	REDDY P N, COOPER G, WEIGHTMAN A, et al. Walking cadence affects rate of plantar foot temperature change but not final temperature in younger and older adults[J]. Gait & Posture, 2017, 52: 272-279.
[33]	REDDY P N, COOPER G, WEIGHTMAN A, et al. An in-shoe temperature measurement system for studying diabetic foot ulceration etiology: preliminary results with healthy participants[J]. Procedia CIRP, 2016, 49: 153-156.
[34]	YAVUZ M, BREM R W, DAVIS B L, et al. Temperature as a predictive tool for plantar triaxial loading[J]. Journal of Biomechanics, 2014, 47(15): 3767-3770. doi: 10.1016/j.jbiomech.2014.09.028 pmid: 25446272
[35]	REYZELMAN A M, KOELEWYN K, MURPHY M, et al. Continuous temperature-monitoring socks for home use in patients with diabetes: observational study[J]. Journal of Medical Internet Research, 2018. DOI: 10.2196/12460.
[36]	NAJAFI B, MOHSENI H, GREWAL G S, et al. An optical-fiber-based smart textile (smart socks) to manage biomechanical risk factors associated with diabetic foot amputation[J]. Journal of Diabetes Science and Technology, 2017, 11(4): 668-677. doi: 10.1177/1932296817709022 pmid: 28513212
[37]	TORREBLANCA GONZÁLEZ J, GÓMEZ-MARTÍN B, HERNÁNDEZ ENCINAS A, et al. The use of infrared thermography to develop and assess a wearable sock and monitor foot temperature in diabetic subjects[J]. Sensors, 2021, 21(5): 1821.
[38]	李肖悦. 基于糖尿病足溃疡的智能监测袜设计与性能分析[D]. 杭州: 浙江理工大学, 2022:42-66.
	LI Xiaoyue. Design and performance analysis of intelligent monitoring socks based on diabetic foot ulcers[D]. Hangzhou: Zhejiang Sci-Tech University, 2022:42-66.
[39]	DE PASCALI C, FRANCIOSO L, GIAMPETRUZZI L, et al. Modeling, fabrication and integration of wearable smart sensors in a monitoring platform for diabetic patients[J]. Sensors, 2021, 21(5): 1847.
[40]	RESCIO G, LEONE A, FRANCIOSO L, et al. Fully integrated smart insole for diabetic foot[C]// LEONE A, CAROPPOA, RESCIOG, et al. Ambient Assisted Living. Cham: Springer International Publishing, 2019: 221-228.
[41]	MURILLO F L, LEIJA L, VERA A. A foot temperature measuring system for diabetic patients[C]// 2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). Campeche Mexico: IEEE, 2014:1-4.
[42]	NAJAFI B, REEVES N D, ARMSTRONG D G. Leveraging smart technologies to improve the management of diabetic foot ulcers and extend ulcer‐free days in remission[J]. Diabetes-Metabolism Research and Reviews, 2020.DOI: 10.1002/dmrr.3239.
[43]	YANO T, OKAMOTO Y, HIRO M, et al. Relationship between skin temperature and skin blood flow in the fingers of healthy adults during cold vasodilation[J]. Journal of the Autonomic Nervous System, 1995, 1(56): 536-541.
[44]	COATES J, CHIPPERFIELD A, CLOUGH G. Wearable multimodal skin sensing for the diabetic foot[J]. Electronics, 2016, 5(4): 45-58.
[45]	谭哲煜, 赵楠, 戴薇薇, 等. 糖尿病足溃疡预防的未来:从分级医疗向个体化医疗的模式转变[J]. 中华糖尿病杂志, 2021, 13(5): 457-461.
	TAN Zheyu, ZHAO Nan, DAI Weiwei, et al. The future of diabetic foot ulcer prevention: the shift from hierarchical medical care to individualized medical care[J]. Chinese Journal of Diabetes, 2021, 13(5): 457-461.
[46]	GOLLEDGE J, FERNANDO M, LAZZARINI P, et al. The potential role of sensors, wearables and telehealth in the remote management of diabetes-related foot disease[J]. Sensors, 2020. DOI:10.3390/s20164527.

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载体	传感器			参考文献
载体	类型	单侧数量/个	位置	参考文献
袜	微型温度传感器	6	大拇趾、第1跖骨头、第3跖骨头、第3跖骨头、足底中心、足跟	[35]
袜	光纤温度压力传感器	5	大拇趾、第1跖骨头、第5跖骨头、足底中心、足跟	[36]
袜	运动传感器	1	大拇趾上方	[36]
袜	热敏电阻温度传感器	5	大拇趾、第1跖骨头、第5跖骨头、足弓内侧、足跟	[37]
袜	柔性温度传感器	1	前足掌内侧	[38]
鞋垫	温度传感器	6	大拇趾、第1跖骨头、第3跖骨头、第5跖骨头、足弓外侧、足跟	[26]
鞋垫	温湿度传感器	1	足底中心	[11]
鞋垫	压力传感器	4	大拇趾、第1跖骨头、第4跖骨头、足跟	[11]
鞋垫	温度、压力、葡萄糖传感器	8	大拇趾、第1跖骨头、第2跖骨头、第3第4跖骨头中间、第4第5跖骨头中间、足弓外侧、足跟左、足跟右	[39-40]
鞋垫	温度传感器	4	大拇趾、第1跖骨头、足弓外侧、足跟	[41]
鞋垫	铂电阻温度传感器	4	大拇趾、第1跖骨头、第5跖骨头、足跟	[31]

基于温度监测的糖尿病足预防性智能鞋袜研究进展

Research progress on smart footwear for monitoring temperature in diabetic foot

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