scholarly journals Assistive Technology for Risks Affecting Elderly People in Outdoor Environment

Author(s):  
Rami Yared ◽  
Bessam Abdulrazak
Author(s):  
Zhenhua Zheng ◽  
Junling Gao ◽  
Ye Yang

Gender difference in the health of elderly people has become an important perspective to consider when studying their health. However, the gender differences in terms of “environment–behavior–health” from the social ecology perspective remain unknown. On the basis of survey data from Shanghai, China, including 2839 samples, this study explored the gender differences of outdoor environment–behavior–activity ability in elderly people from two aspects of the mean value of variables and the path relationship, utilizing the structural equation model analysis method combined with social ecology theory. The results showed that, at the level of the mean of variables, the elderly males had significantly higher mean values than the females in terms of individual behaviors, but had significantly lower values in terms of social behaviors. At the level of path relationships, there were similarities in that the health of elderly males was more likely to be affected by individual factors, whereas that of the females was more effected by social factors. Through the great positive effect of the high-level social behaviors, the health of the elderly females was progressively promoted. The study provided some useful insights for future research, aiming at promoting gender-sensitive urban design.


2017 ◽  
Vol 13 (06) ◽  
pp. 58 ◽  
Author(s):  
Thittaporn Ganokratanaa ◽  
Suree Pumrin

The relationship between humans and computers is called human computer interaction (HCI). HCI is a major research topic in the area of assistive technology. In the field of medical assistive technology specifically, a hand gesture is considered a suitable method to convey information. It can help elderly people, who are unable to walk or speak, communicate with caregivers whenever they need help. This paper proposes a system to recognize the hand gestures of elderly people using an inexpensive Raspberry Pi. A vision-based algorithm is developed to detect and classify dynamic hand gestures in real time on the Raspberry Pi embedded platform. There are three main procedures; contour detection, convex extraction, and rule-based classification. The system can detect six different gestures on both hands in various orientations. The experiment showed good results in detecting and classifying their meanings as lingual descriptions.


2006 ◽  
Vol 18 (Supplement) ◽  
pp. 45-45
Author(s):  
Shigenobu Suzuki ◽  
Yoshiaki Takagai ◽  
Akira Kakimoto ◽  
Yukio Sekiguchi

Author(s):  
Eliane de Sousa Leite ◽  
Tatiane Peixoto Rodrigues ◽  
Maria do Carmo Andrade Duarte de Farias ◽  
Maria Adelaide Silva Paredes Moreira ◽  
Greicy Kelly Gouveia Dias Bittencourt ◽  
...  

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