Synphne accelerated stroke rehabilitation system - data analytics and cloud computing
This final year project is targeted to help increase the independency of stroke patients by helping them cope with their daily routine. A detailed comparison of stroke subject’s test results gathered from NUH clinical assessment. It shows how 15 subjects fared in each test, starting from Week 0 to W...
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sg-ntu-dr.10356-683782023-03-04T19:23:23Z Synphne accelerated stroke rehabilitation system - data analytics and cloud computing Nor Aini Ayoub Heng Kok Hui, John Gerard School of Mechanical and Aerospace Engineering SynPhNe Pte Ltd DRNTU::Engineering This final year project is targeted to help increase the independency of stroke patients by helping them cope with their daily routine. A detailed comparison of stroke subject’s test results gathered from NUH clinical assessment. It shows how 15 subjects fared in each test, starting from Week 0 to Week 3 to Week 6. This is to show how much they have improved after going through the SynPhNe’s rehabilitation exercise in Week 2 and Week 4. Thereby, findings were first made by analyzing which statistical test is the most suitable for this project and thus using it together with R Studio as the running tool. All subjects showed improvement fortnightly for every test except for 4 subjects. They scored lower at Week 6 as compared to previous weeks for either Grip Strength or 9-Hole Peg test. Even when comparing the shown results from these 4 tests namely Grip Strength test, 9-hole Peg test, Action Research Arm test (ARAT) and Fugl-Meyer (FM) test, all subjects scored the least for Grip Strength and showed the least amount of improvement even after many weeks. The average score of each subject for the FM test is 0.59 and 0.76 for Week 0 and Week 6 respectively. As for the Grip Strength test, each subject only scored an average of 0.098 for Week 0 and 0.22 for Week 6. The number of subjects that scored almost full or full marks for the ARAT, improved from 2 to 6 for Week 0 to Week 6. However, the Grip Strength test result that scored almost full marks have only improved slightly from 0 to 1 subject. Hence, usage of statistical tests like T-test and Wilcoxon signed rank test has provided a better understanding of the results shown. Paired T-test was chosen because it is a before and after sample population with sample size lesser than 30. However, Wilcoxon paired test was also used because the data was not normally distributed. However, The T-test and Wilcoxon signed rank test results have shown that the 9-Hole Peg test result has no relation to SynPhNe’s rehabilitation exercise. It was an unexpected result, but it may be due to the method used to normalized the data. This will be explained in detail in the later part of this paper. Thus, by the end of this project, it justifies that stroke patients gained better independence after going through SynPhNe’s rehabilitation exercise. Bachelor of Engineering (Mechanical Engineering) 2016-05-25T08:10:30Z 2016-05-25T08:10:30Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68378 en Nanyang Technological University 58 p. application/pdf |
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DRNTU::Engineering Nor Aini Ayoub Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
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This final year project is targeted to help increase the independency of stroke patients by helping them cope with their daily routine. A detailed comparison of stroke subject’s test results gathered from NUH clinical assessment. It shows how 15 subjects fared in each test, starting from Week 0 to Week 3 to Week 6. This is to show how much they have improved after going through the SynPhNe’s rehabilitation exercise in Week 2 and Week 4. Thereby, findings were first made by analyzing which statistical test is the most suitable for this project and thus using it together with R Studio as the running tool. All subjects showed improvement fortnightly for every test except for 4 subjects. They scored lower at Week 6 as compared to previous weeks for either Grip Strength or 9-Hole Peg test. Even when comparing the shown results from these 4 tests namely Grip Strength test, 9-hole Peg test, Action Research Arm test (ARAT) and Fugl-Meyer (FM) test, all subjects scored the least for Grip Strength and showed the least amount of improvement even after many weeks. The average score of each subject for the FM test is 0.59 and 0.76 for Week 0 and Week 6 respectively. As for the Grip Strength test, each subject only scored an average of 0.098 for Week 0 and 0.22 for Week 6. The number of subjects that scored almost full or full marks for the ARAT, improved from 2 to 6 for Week 0 to Week 6. However, the Grip Strength test result that scored almost full marks have only improved slightly from 0 to 1 subject. Hence, usage of statistical tests like T-test and Wilcoxon signed rank test has provided a better understanding of the results shown. Paired T-test was chosen because it is a before and after sample population with sample size lesser than 30. However, Wilcoxon paired test was also used because the data was not normally distributed. However, The T-test and Wilcoxon signed rank test results have shown that the 9-Hole Peg test result has no relation to SynPhNe’s rehabilitation exercise. It was an unexpected result, but it may be due to the method used to normalized the data. This will be explained in detail in the later part of this paper. Thus, by the end of this project, it justifies that stroke patients gained better independence after going through SynPhNe’s rehabilitation exercise. |
author2 |
Heng Kok Hui, John Gerard |
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Heng Kok Hui, John Gerard Nor Aini Ayoub |
format |
Final Year Project |
author |
Nor Aini Ayoub |
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Nor Aini Ayoub |
title |
Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
title_short |
Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
title_full |
Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
title_fullStr |
Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
title_full_unstemmed |
Synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
title_sort |
synphne accelerated stroke rehabilitation system - data analytics and cloud computing |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68378 |
_version_ |
1759854894962966528 |