• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.32-38
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• 2002

This paper describes a development of a portable physical activity monitoring system using two accelerometers to quantify physical activity. The system hardware consists of two piezoresistive accelerometers, amplifiers with gain of 30, lowpass filters with cut-off frequency of 15Hz, offset control circuits, one-chip microcontroller and flash memory card. In order to evaluate the performance of the system we acquired 3 channel data at 32 sample/sec from body-fixed accelerometers in chest and right upper leg. And then the acquired data were processed by MatLab on personal computer. We tried to distinguish not only fundamental actions which are steady-state activities such as standing, sitting, and lying but also dynamic activities with walking, up a stairway, down a stairway, and running. Five subjects participated the evaluation process which compare the video data with the measured data. As a result, the activity classification rate of 90.6% on average was obtained. Overall results showed that the steady-state activities could be classified from the low component of 3-axis acceleration signal and dynamic activities could be distinguished from frequency analysis using wavelet transform and FFT. Finally, we could find that this system can be applied to acquire and analyze the static and dynamic physical activity data.

• Journal of the Korean Applied Science and Technology
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• v.38 no.3
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• pp.786-800
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• 2021

The subjects of this study were 463 people aged 65 and older in the senior welfare center in Seoul and Gyeonggi. The purpose of the study is to analyze the differences between physical fitness factors and cognitive functions, activities of daily living, instrumental activities of daily living, and psychological variables in the participation of the elderly in physical activities. Data ware analyzed by frequency analysis, reliability analysis, independent sample t-test and one-way ANOVA, and Pearson's correlation analysis, with SPSS 25.0 statistics program. The results of this study are as follows. First, there are statistically significant differences in physical fitness, cognitive function, activities of daily living, instrumental activities of daily living, and psychological factors such as depression and quality of life, depending on whether the elderly participate in physical activity. There were statistically significant differences in physical fitness, cognitive function, ADL, IADL, depression and quality of life, depending on the frequency of participation of older people in physical activity. A statistically significant difference in physical fitness appeared depending on the participation time of the elderly who participated in physical activity. Second, a study of the correlation between physical fitness and cognitive function, ADL, IADL, depression, and quality of life revealed a correlation for most factors. Based on these research results, it is necessary to develop a systematic arbitration strategy including physical activity for the successful aging of the elderly and the independent life of old age.