Performance analysis of different fall detecting algorithms with different combinations of sensors.
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.
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Brac University
2021
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| Acesso em linha: | http://hdl.handle.net/10361/14794 |
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10361-147942021-07-13T21:01:19Z Performance analysis of different fall detecting algorithms with different combinations of sensors. Jhalak, Rashed Mahmood Tonni, Fariya Rahman Ibrahim, Ishaq Ibne Rabbi, MD. Fazle Bhuian, Mohammed Belal Hossain Department of Electrical and Electronic Engineering, Brac University Algorithm Accelerometer Gyroscope Magnetometer Threshold Performance Analysis This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 59-63). Fall is one of the major reasons for the death of elderly people. Fall detection systems with different sensors based on different algorithms are now quite well admired. In this paper we analyzed the performance of different algorithms that can be used to detect fall. We used four different types of machine learning algorithms for this project. At first, we have created our own data with accelerometer and gyroscope separately and simultaneously. Then we used this data on each algorithm and found the accuracy rate. After that we added Magnetometer and compared the new result with the previous results and the threshold difference among these algorithms. Our final result is which algorithm has the highest rate to detect fall comparing all the sensors individually and all together and we found SVM algorithm with using accelerometer and gyroscope together gives the highest accuracy of about 97%. Rashed Mahmood Jhalak Fariya Rahman Tonni Ishaq Ibne Ibrahim MD. Fazle Rabbi B. Electrical and Electronic Engineering 2021-07-13T15:36:59Z 2021-07-13T15:36:59Z 2021 2021-01 Thesis ID: 16121040 ID: 16121030 ID: 16121028 ID: 16321119 http://hdl.handle.net/10361/14794 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 63 Pages application/pdf Brac University |
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Brac University |
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Institutional Repository |
| language |
en_US |
| topic |
Algorithm Accelerometer Gyroscope Magnetometer Threshold Performance Analysis |
| spellingShingle |
Algorithm Accelerometer Gyroscope Magnetometer Threshold Performance Analysis Jhalak, Rashed Mahmood Tonni, Fariya Rahman Ibrahim, Ishaq Ibne Rabbi, MD. Fazle Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021. |
| author2 |
Bhuian, Mohammed Belal Hossain |
| author_facet |
Bhuian, Mohammed Belal Hossain Jhalak, Rashed Mahmood Tonni, Fariya Rahman Ibrahim, Ishaq Ibne Rabbi, MD. Fazle |
| format |
Thesis |
| author |
Jhalak, Rashed Mahmood Tonni, Fariya Rahman Ibrahim, Ishaq Ibne Rabbi, MD. Fazle |
| author_sort |
Jhalak, Rashed Mahmood |
| title |
Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| title_short |
Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| title_full |
Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| title_fullStr |
Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| title_full_unstemmed |
Performance analysis of different fall detecting algorithms with different combinations of sensors. |
| title_sort |
performance analysis of different fall detecting algorithms with different combinations of sensors. |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14794 |
| work_keys_str_mv |
AT jhalakrashedmahmood performanceanalysisofdifferentfalldetectingalgorithmswithdifferentcombinationsofsensors AT tonnifariyarahman performanceanalysisofdifferentfalldetectingalgorithmswithdifferentcombinationsofsensors AT ibrahimishaqibne performanceanalysisofdifferentfalldetectingalgorithmswithdifferentcombinationsofsensors AT rabbimdfazle performanceanalysisofdifferentfalldetectingalgorithmswithdifferentcombinationsofsensors |
| _version_ |
1814306923789418496 |