Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes

Healthcare Technology Letters

article

Neha Mathur¹  Ivan Glesk¹  Arjan Buis² 

[1] Department of Electronic and Electrical Engineering, University of Strathclyde;Department of Biomedical Engineering, University of Strathclyde

关键词: biothermics;    prosthetics;    skin;    thermal time constant;    skin temperature predictive modelling;    lower limb prostheses;    Gaussian processes;    body-device interface;    tissue health;    heat dissipation;    hard socket;    residual limb temperature;    perspiration;   

DOI  :  10.1049/htl.2015.0023

学科分类：肠胃与肝脏病学

来源: Wiley

【 摘 要 】

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm – Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable.

【 授权许可】

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