Classification Analysis Of Sleep Quality On The Active Performance
Sufficient sleep is an important aspect to maintain active for daily activities. Good sleep quality essentially helps our brain to concentrate, store memory and stay active for physical activities. Most of the previous studies on sleeping analysis focused on the factors affecting sleeping patt...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2019
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| Online Access: | http://eprints.usm.my/58277/ http://eprints.usm.my/58277/1/Classification%20Analysis%20Of%20Sleep%20Quality%20On%20The%20Active%20Performance.pdf |
| _version_ | 1848883855873802240 |
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| author | Tan, Hann Woei |
| author_facet | Tan, Hann Woei |
| author_sort | Tan, Hann Woei |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Sufficient sleep is an important aspect to maintain active for daily activities.
Good sleep quality essentially helps our brain to concentrate, store memory and stay
active for physical activities. Most of the previous studies on sleeping analysis focused
on the factors affecting sleeping patterns instead of the sleep quality effecting on daily
performances. Therefore, this study is conducted to (i) determine the significant factors
affecting the sleep qualities, (ii) classify sleeping quality patterns and (iii) investigate
the relationship between sleeping patterns and active performances. This research
project involved an experimental and a survey study on the sleeping qualities for active
performances during the daytime. Data analysis was performed based on data mining
approach using the Waikato Environment for Knowledge Analysis (WEKA) software.
There were 20 voluntary participants which are the students of University Sains
Malaysia Engineering Campus. Two Android sleep tracking apps: PrimeNap and
Runtastic were applied to measure the sleeping patterns. The data was then compiled
on Google Form along with the active performance survey questionnaires, the
classification of the data into three classes show accuracies ranged from 63.2-92.8% on
both PrimeNap and Runtastic respectively. The data is further analysed in the
knowledge discovery process and the total sleep period, sleep cycle and REM sleep
period were identified as the three most significant attributes corresponding to
determine the sleep quality. However, the sleeping quality could not describe the
conditions of daily active performances. |
| first_indexed | 2025-11-15T18:57:27Z |
| format | Monograph |
| id | usm-58277 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:57:27Z |
| publishDate | 2019 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-582772023-04-28T09:53:21Z http://eprints.usm.my/58277/ Classification Analysis Of Sleep Quality On The Active Performance Tan, Hann Woei T Technology T351-385 Mechanical drawing. Engineering graphics Sufficient sleep is an important aspect to maintain active for daily activities. Good sleep quality essentially helps our brain to concentrate, store memory and stay active for physical activities. Most of the previous studies on sleeping analysis focused on the factors affecting sleeping patterns instead of the sleep quality effecting on daily performances. Therefore, this study is conducted to (i) determine the significant factors affecting the sleep qualities, (ii) classify sleeping quality patterns and (iii) investigate the relationship between sleeping patterns and active performances. This research project involved an experimental and a survey study on the sleeping qualities for active performances during the daytime. Data analysis was performed based on data mining approach using the Waikato Environment for Knowledge Analysis (WEKA) software. There were 20 voluntary participants which are the students of University Sains Malaysia Engineering Campus. Two Android sleep tracking apps: PrimeNap and Runtastic were applied to measure the sleeping patterns. The data was then compiled on Google Form along with the active performance survey questionnaires, the classification of the data into three classes show accuracies ranged from 63.2-92.8% on both PrimeNap and Runtastic respectively. The data is further analysed in the knowledge discovery process and the total sleep period, sleep cycle and REM sleep period were identified as the three most significant attributes corresponding to determine the sleep quality. However, the sleeping quality could not describe the conditions of daily active performances. Universiti Sains Malaysia 2019-05-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/58277/1/Classification%20Analysis%20Of%20Sleep%20Quality%20On%20The%20Active%20Performance.pdf Tan, Hann Woei (2019) Classification Analysis Of Sleep Quality On The Active Performance. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Mekanik. (Submitted) |
| spellingShingle | T Technology T351-385 Mechanical drawing. Engineering graphics Tan, Hann Woei Classification Analysis Of Sleep Quality On The Active Performance |
| title | Classification Analysis Of Sleep Quality On The Active Performance |
| title_full | Classification Analysis Of Sleep Quality On The Active Performance |
| title_fullStr | Classification Analysis Of Sleep Quality On The Active Performance |
| title_full_unstemmed | Classification Analysis Of Sleep Quality On The Active Performance |
| title_short | Classification Analysis Of Sleep Quality On The Active Performance |
| title_sort | classification analysis of sleep quality on the active performance |
| topic | T Technology T351-385 Mechanical drawing. Engineering graphics |
| url | http://eprints.usm.my/58277/ http://eprints.usm.my/58277/1/Classification%20Analysis%20Of%20Sleep%20Quality%20On%20The%20Active%20Performance.pdf |