Effect of footwear features on the gait muscle activity of young, middle - aged and older adults
In light of today’s society, Singapore is witnessing a surge of her senior population expedited by the low birth rates, the post-war baby boomers and the lengthened life expectancy of the modern population. As we age, our muscle mass and strength start to decline, increasing the vulnerability of suf...
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Format: | Final Year Project |
Language: | English |
Published: |
2015
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Online Access: | http://hdl.handle.net/10356/63990 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | In light of today’s society, Singapore is witnessing a surge of her senior population expedited by the low birth rates, the post-war baby boomers and the lengthened life expectancy of the modern population. As we age, our muscle mass and strength start to decline, increasing the vulnerability of suffering from age-related muscle loss disorder, for instance, sarcopenia, which is the gradual and degenerative loss of muscles mass prevalent in the elderly people. Notwithstanding the age, research has shown that performing regular exercises, such as taking frequent walks, can help to minimize the associated condition. Various footwear features can play an essential role in shaping the way we walk and have different effects on our gait cycles. Therefore, the purpose of this project is to identify and compare the different footwear to explore how the different features can affect the lower extremity muscles of middle and older adults in the gait cycle. From the results, we aim to explore and to determine different optimal features that will help reduce the deterioration of the leg muscle health among the middle and older adults. Three different age groups of subjects were tested; young (20-30 years old), middle-aged (40-60 years old) and older adults (60+ years old). Ten lower extremity muscles were studied and the effects of footwear during the different phases of the gait cycle were analyzed. These muscles activities were recorded using the wireless surface electromygraphy (SEMG) system and further analysed by MEGAWINTM software. |
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