Programming of a system for the acquisition of images and thermographic data for the diabetic foot analysis

Bayareh, Rafael; Vera, A.; Leija, L.; Gutierrez, J.

doi:10.1109/iceee.2017.8108866

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…This method helps in detecting early diabetes using foot thermograph. [2] Data mining plays an important role in classification of medical images from large database system. Medical imaging system is one of the lead method used for health diagnosing by physicians.…”

Section: Related Workmentioning

confidence: 99%

Non Invasive Method of Diabetes Measurement using Teg Sensor via Foot Skin Temperature

Ganesan

2019

IJEAT

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Abstract: Diabetes is a type of metabolic dieses identified by unstable blood glucose level due to the defect in body to generate or use of insulin. Diabetes is created due to the defect in metabolism of converting the glucose to energy in blood. Hyperglycaemia is a stage were glucose value in the body is greater than 140 mg/dl which leads to type 1 diabetes for the patient. Type 1 diabetes is caused due to lack of generation of insulin in human blood and type 2 diabetes is caused due to resistance to insulin action which leads to several other diseases like foot ulcer and sever wounds in human foot or other parts of the body. Early diagnosing of diabetes disease plays an important task in improving the standard of healthy living. Traditional methods of identifying diabetes does not provides effective results and the results are not more reliable. Temperature based diabetes diagnosing model is defined using TEG sensor to analyse the heat changes in human foot.Imbalanced glucose level affects the performance of nerves system which leads to slower response for temperature change in the foot surface. TEG sensor is used to measure the heat transfer in foot by applying cold water over foot. The rate of temperature changes in foot represents the level of diabetes caused in the patient body. The signals from TEG sensor was collected and processed using signal analysis algorithm using MATLAB software.

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Section: Related Workmentioning

confidence: 99%

Non Invasive Method of Diabetes Measurement using Teg Sensor via Foot Skin Temperature

Ganesan

2019

IJEAT

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“…In addition, the typical sensitivity and responsiveness of micro-bolometers is inherently lower than photon detectors. Despite these limitations, the recently introduced miniature thermal core printed circuit board mounted micro-bolometer based cameras [15], costing as little as 300 USD, has prompted the present investigation into their applicability for LIT. The small format and low cost of the thermal core, in combination with the embedded actuators proposed in the paper, offer a new methodology for LIT with the potential for permanent deployment on a structure and a route to thermography based structural health monitoring.…”

Section: Introductionmentioning

confidence: 99%

Lock-in thermography using miniature infra-red cameras and integrated actuators for defect identification in composite materials

Ólafsson

Tighe

Boyd

et al. 2022

Optics & Laser Technology

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Detection of Diabetes Mellitus With Deep Learning and Data Augmentation Techniques on Foot Thermography

Anaya-Isaza

Zequera

2022

IEEE Access

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Programming of a system for the acquisition of images and thermographic data for the diabetic foot analysis

Cited by 5 publications

References 14 publications

Non Invasive Method of Diabetes Measurement using Teg Sensor via Foot Skin Temperature

Non Invasive Method of Diabetes Measurement using Teg Sensor via Foot Skin Temperature

Lock-in thermography using miniature infra-red cameras and integrated actuators for defect identification in composite materials

Detection of Diabetes Mellitus With Deep Learning and Data Augmentation Techniques on Foot Thermography

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