Abstract
Sleep is a mysterious shift in consciousness that bodies require every day. It is distinguished from wakefulness by a decreased ability to react to stimuli, but is more easily reversed than the state of hibernation. Sleep is vital for one’s health and well-being. Lacking of quality sleep decreases one’s functionality for the day and is detrimental to health in long term. Over the past 2 decades, actigraphy has emerged as one of the most popular methodologies to study and assess sleep–wake patterns. A lot of commercial devices have been manufactured based on this approach. However, these commercial devices do not really quantify and display the exact level of sleep quality. The same disadvantage happens for subjective assessment. This paper proposes a method using Fuzzy Logic (FL) which able to quantify the sleep quality. The FL system was developed through few vital steps: (i) Identifying the significant variables which affect the sleep quality, (ii) Determining the fuzzy set for each variable, (iii) Constructing the fuzzy rules through studying the relationship between each variable, (iv) Developing the inference system using Mamdani style. Four individuals were invited for carrying the experiments, developed FL system was used to measure their sleep quality and they were required to complete the sleep quality subjective assessments. Eventually, the results of using proposed method were compared to subjective assessment results for validation purpose.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. C.K., Ang UNSPECIFIED W.Y., Tey UNSPECIFIED P.L., Kiew UNSPECIFIED M., Fauzi UNSPECIFIED |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TJ Mechanical engineering and machinery > Mechanics applied to machinery. Dynamics |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering |
Journal or Publication Title: | Special Issue Engineering for Humanity Vol 2 |
UiTM Journal Collections: | UiTM Journal > Journal of Mechanical Engineering (JMechE) |
ISSN: | 18235514 |
Volume: | SI 4 |
Number: | 2 |
Page Range: | pp. 31-47 |
Keywords: | Sleep, Artificial intelligences, Fuzzy Logic, Actigraphy, Sleep Quality |
Date: | 2017 |
URI: | https://ir.uitm.edu.my/id/eprint/39031 |