Microenvironment temperature prediction between body and seat interface using autoregressive data-driven model.

There is a need to develop a greater understanding of temperature at the skin-seat interface during prolonged seating from the perspectives of both industrial design (comfort/discomfort) and medical care (skin ulcer formation). Here we test the concept of predicting temperature at the seat surface and skin interface during prolonged sitting (such as required from wheelchair users). As caregivers are usually busy, such a method would give them warning ahead of a problem. This paper describes a data-driven model capable of predicting thermal changes and thus having the potential to provide an early warning (15- to 25-min ahead prediction) of an impending temperature that may increase the risk for potential skin damages for those subject to enforced sitting and who have little or no sensory feedback from this area. Initially, the oscillations of the original signal are suppressed using the reconstruction strategy of empirical mode decomposition (EMD). Consequentially, the autoregressive data-driven model can be used to predict future thermal trends based on a shorter period of acquisition, which reduces the possibility of introducing human errors and artefacts associated with longer duration "enforced" sitting by volunteers. In this study, the method had a maximum predictive error of <0.4 °C when used to predict the temperature at the seat and skin interface 15 min ahead, but required 45 min data prior to give this accuracy. Although the 45 min front loading of data appears large (in proportion to the 15 min prediction), a relative strength derives from the fact that the same algorithm could be used on the other 4 sitting datasets created by the same individual, suggesting that the period of 45 min required to train the algorithm is transferable to other data from the same individual. This approach might be developed (along with incorporation of other measures such as movement and humidity) into a system that can give caregivers prior warning to help avoid exacerbating the skin disorders of patients who suffer from low body insensitivity and disability requiring them to be immobile in seats for prolonged periods.

[1]  P. Dabnichki,et al.  Skin temperature distribution and thermoregulatory response during prolonged seating , 2013 .

[2]  N. Zaproudina,et al.  High scrotal temperatures and chairs in the pathophysiology of poor semen quality. , 2005, Pathophysiology : the official journal of the International Society for Pathophysiology.

[3]  Mike Kolich,et al.  A conceptual framework proposed to formalize the scientific investigation of automobile seat comfort. , 2008, Applied ergonomics.

[4]  Mark J. Buller,et al.  Individualized Short-Term Core Temperature Prediction in Humans Using Biomathematical Models , 2008, IEEE Transactions on Biomedical Engineering.

[5]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[6]  Shinichi Watanabe,et al.  Thermal evaluation of a chair with fans as an individually controlled system , 2009 .

[7]  Zhuofu Liu,et al.  Studying thermal characteristics of seating materials by recording temperature from 3 positions at the seat-subject interface. , 2011, Journal of tissue viability.

[8]  Tonny Karlsmark,et al.  Evaluation of four non‐invasive methods for examination and characterization of pressure ulcers , 2008, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[9]  P W McCarthy,et al.  Assessment of humidity and temperature sensors and their application to seating , 2009, Journal of medical engineering & technology.

[10]  Jenny Wall,et al.  Preventing pressure ulcers among wheelchair users: preliminary comments on the development of a self-administered risk assessment tool. , 2003, Journal of tissue viability.

[11]  Amit Gefen,et al.  How do microclimate factors affect the risk for superficial pressure ulcers: a mathematical modeling study. , 2011, Journal of tissue viability.

[12]  P. Black,et al.  Causation of Large-Amplitude Coastal Seiches on the Caribbean Coast of Puerto Rico , 1990 .

[13]  W. Hanke,et al.  Effects of occupational exposure - is there a link between exposure based on an occupational questionnaire and semen quality? , 2014, Systems biology in reproductive medicine.

[14]  Norden E. Huang,et al.  The Ages of Large Amplitude Coastal Seiches on the Caribbean Coast of Puerto Rico , 2000 .

[15]  Masanori Shukuya,et al.  Adaptive comfort from the viewpoint of human body exergy consumption , 2012 .

[16]  N. Vuillerme,et al.  TexiCare: an innovative embedded device for pressure ulcer prevention. Preliminary results with a paraplegic volunteer. , 2013, Journal of tissue viability.

[17]  M. Ferrarin,et al.  Analysis of thermal properties of wheelchair cushions with thermography , 2006, Medical and Biological Engineering and Computing.

[18]  Meimei Liu,et al.  Noise Removal Applied to a Temperature Signal from Body and Seat Contact Surface Based on the EMD Method , 2013 .

[19]  Md. Khademul Islam Molla,et al.  Analysis of Temperature Change under Global Warming Impact using Empirical Mode Decomposition , 2007 .

[20]  Tülin Gündüz Cengiz,et al.  An on-the-road experiment into the thermal comfort of car seats. , 2007, Applied ergonomics.

[21]  N. Huang,et al.  A study of the characteristics of white noise using the empirical mode decomposition method , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[22]  Amit Gefen,et al.  An air-cell-based cushion for pressure ulcer protection remarkably reduces tissue stresses in the seated buttocks with respect to foams: finite element studies. , 2014, Journal of tissue viability.

[23]  Michael Clark,et al.  Seating and pressure ulcers: clinical practice guideline. , 2009, Journal of tissue viability.

[24]  Satoru Takada,et al.  Re-evaluation of Stolwijk's 25-node human thermal model under thermal-transient conditions: Prediction of skin temperature in low-activity conditions , 2009 .

[25]  Edward Arens,et al.  Indoor Environmental Quality ( IEQ ) Title A model of human physiology and comfort for assessing complex thermal environments , 2001 .

[26]  Mohamed B. Gadi A new computer program for the prediction and analysis of human thermal comfort , 2000 .