Preliminary Study on Comfortableness of Motorized Wheelchair Cushion_Journal of Biomedical Engineering

Authors：

 WANGShuyi , SUNChangying , WANGBingcao

School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;

Corresponding author：

WANGShuyi, Email: wangshuyi2001@sina.com

Keywords：

temperature and humidity; adjustment time; comfort degree; mathematical model

DOI：

10.7507/1001-5515.20160054

Video：

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This paper aims to explore the thermal feelings of different cover materials effect on wheelchair cushion comfortableness, and to build a mathematical model for motorized wheelchair cushion comfortableness. By measuring temperature and humidity between the contact face of motorized wheelchair cushion and human body as well as the setting posture adjustment time while cushion cover materials are nylon cloth, leather, fishnets cloth. At the same time, each volunteer took a questionnaire about the comfort of different cushion cover materials. Results showed that fishnets cloth was most comfortable, leather was worst, while nylon cloth was in between the two. The experimental objective data were consistent with the subjective data. We built a back propagation (BP) neural network mathematical model for motorized wheelchair cushion comfortableness. This study will provide objective reference to motorized wheelchair for the designers and users.

Citation： WANGShuyi, SUNChangying, WANGBingcao. Preliminary Study on Comfortableness of Motorized Wheelchair Cushion. Journal of Biomedical Engineering, 2016, 33(2): 320-324. doi: 10.7507/1001-5515.20160054 Copy

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10.	张方方, 张莲, 刘贺.基于神经网络的室内环境热舒适度融合算法[J].重庆工学院学报(自然科学), 2009, 23(10):114-118.
11.	嵇赟喆, 涂光备, 王晓杰.人工神经网络在热舒适实验研究中的应用[J].天津大学学报, 2004, 37(4):331-335.
12.	ATTHAJARIYAKUL S, LEEHAKPREEDA T. Neural computing thermal comfort index for HVAC systems[J].Energy Conversion and Management, 2005, 46(15):2553-2565.
13.	LIU W W, LIAN Z W, ZHAO B. A neural network evaluation model for individual thermal comfort[J].Energy and Buildings, 2007, 39(10):1115-1122.
14.	FRANCESCO C, MARIA L G, GIANFRANCO R, et al. The control of indoor thermal comfort conditions:introducing a fuzzy adaptive controller[J].Energy and Buildings, 2004, 36(2):97-102.
15.	张川燕, 王子介.基于BP神经网络的热舒适性指标计算[J].南京师范大学学报工程技术版, 2009, 9(1):44-48.

1. 鲁涛, 原魁, 朱海兵.智能轮椅研究现状及发展趋势[J].机器人技术与应用, 2008, 3(2):1-3.
2. 周敏.温觉特性与坐姿体压分布的实验研究[D].南京:南京林业大学, 2007.
3. 高嫚.压疮与体位关系的研究进展[J].中国实用护理杂志, 2008, 24(2):59-61.
4. 刘卓夫, 罗中明, VINCENZO C, 等.人体-座椅接触面测量参数的研究初探[J].仪表技术与传感器, 2011, 1(1):92-94.
5. 夏岚, 李文琳, 刘文金.基于人机工程学的客车椅设计方法研究[J].中南林业科技大学学报, 2010, 30(5):184-188.
6. 杨海波, 姜红梅, 王欣.基于人机工程学的健康办公椅设计研究[J].设计, 2012, 8(2):24-25.
7. 秦美超, 轮椅舒适性评价体系研究[D].大连:大连交通大学, 2012.
8. MCCARTHY P W, LIU Z, HEUSCH D. Assessment of humidity and temperature sensors and their application to seating[J].J Med EngTchnol, 2009, 33(6):449-453.
9. 刘卓夫, 李恩会, 李俊夫, 等.座椅热舒适性客观评价温度模型构建[J].人类工效学, 2012, 18(1):62-65.
10. 张方方, 张莲, 刘贺.基于神经网络的室内环境热舒适度融合算法[J].重庆工学院学报(自然科学), 2009, 23(10):114-118.
11. 嵇赟喆, 涂光备, 王晓杰.人工神经网络在热舒适实验研究中的应用[J].天津大学学报, 2004, 37(4):331-335.
12. ATTHAJARIYAKUL S, LEEHAKPREEDA T. Neural computing thermal comfort index for HVAC systems[J].Energy Conversion and Management, 2005, 46(15):2553-2565.
13. LIU W W, LIAN Z W, ZHAO B. A neural network evaluation model for individual thermal comfort[J].Energy and Buildings, 2007, 39(10):1115-1122.
14. FRANCESCO C, MARIA L G, GIANFRANCO R, et al. The control of indoor thermal comfort conditions:introducing a fuzzy adaptive controller[J].Energy and Buildings, 2004, 36(2):97-102.
15. 张川燕, 王子介.基于BP神经网络的热舒适性指标计算[J].南京师范大学学报工程技术版, 2009, 9(1):44-48.

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