The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes
The present investigation aims at measuring as well as predicting blood pressure (BP) levels using anthropometric indexes. A standardised systolic blood pressure, (STBP) and diastolic blood pressure (DSBP) coupled with anthropometric evaluations of Body Mass Index waist to hip ratio, waist to height...
| Main Authors: | , , , , , |
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| Format: | Book Chapter |
| Language: | English English |
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Springer
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/42606/1/The%20application%20of%20artificial%20neural%20networks%20in%20predicting.pdf http://umpir.ump.edu.my/id/eprint/42606/2/The%20application%20of%20artificial%20neural%20networks%20in%20predicting%20blood%20pressure%20levels%20of%20youth%20archers%20by%20means%20of%20anthropometric%20indexes_ABS.pdf |
| _version_ | 1817928189635198976 |
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| author | Musa, Rabiu Muazu Muhammad Zuhaili, Suhaimi P. P. Abdul Majeed, Anwar Mohamad Razali, Abdullah Siti Musliha, Mat-Rasid Mohd Hasnun Ariff, Hassan |
| author_facet | Musa, Rabiu Muazu Muhammad Zuhaili, Suhaimi P. P. Abdul Majeed, Anwar Mohamad Razali, Abdullah Siti Musliha, Mat-Rasid Mohd Hasnun Ariff, Hassan |
| author_sort | Musa, Rabiu Muazu |
| collection | UMP |
| description | The present investigation aims at measuring as well as predicting blood pressure (BP) levels using anthropometric indexes. A standardised systolic blood pressure, (STBP) and diastolic blood pressure (DSBP) coupled with anthropometric evaluations of Body Mass Index waist to hip ratio, waist to height ratio, body fat percentage, and calf circumference was carried out on 50 youth archers. A Backward Regression Analysis (BRA) was used to determine the anthropometrics indexes that could predict both the STBP and DSBP whilst two models, namely Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) were developed based on the most correlated anthropometry. The BRA identified calf circumference (CC) as the highest correlated predictor for both STBP and DSBP. The ANN model developed demonstrated a better prediction efficacy against the MLR with an R2 as well as the mean absolute percentage error values of 0.95, 0.95, 0.050 and 0.06 as compared to MLR 0.26, 0.25, 8.46, 6.56 in the prediction of both the STBP and DSBP, respectively. It is evident from the present study that the BP levels of youth archers could be reliably measured using only their CC index. |
| first_indexed | 2024-12-09T02:30:23Z |
| format | Book Chapter |
| id | UMPir42606 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-12-09T02:30:23Z |
| publishDate | 2020 |
| publisher | Springer |
| record_format | dspace |
| spelling | UMPir426062024-12-02T01:22:59Z http://umpir.ump.edu.my/id/eprint/42606/ The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes Musa, Rabiu Muazu Muhammad Zuhaili, Suhaimi P. P. Abdul Majeed, Anwar Mohamad Razali, Abdullah Siti Musliha, Mat-Rasid Mohd Hasnun Ariff, Hassan T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures The present investigation aims at measuring as well as predicting blood pressure (BP) levels using anthropometric indexes. A standardised systolic blood pressure, (STBP) and diastolic blood pressure (DSBP) coupled with anthropometric evaluations of Body Mass Index waist to hip ratio, waist to height ratio, body fat percentage, and calf circumference was carried out on 50 youth archers. A Backward Regression Analysis (BRA) was used to determine the anthropometrics indexes that could predict both the STBP and DSBP whilst two models, namely Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) were developed based on the most correlated anthropometry. The BRA identified calf circumference (CC) as the highest correlated predictor for both STBP and DSBP. The ANN model developed demonstrated a better prediction efficacy against the MLR with an R2 as well as the mean absolute percentage error values of 0.95, 0.95, 0.050 and 0.06 as compared to MLR 0.26, 0.25, 8.46, 6.56 in the prediction of both the STBP and DSBP, respectively. It is evident from the present study that the BP levels of youth archers could be reliably measured using only their CC index. Springer 2020 Book Chapter PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42606/1/The%20application%20of%20artificial%20neural%20networks%20in%20predicting.pdf pdf en http://umpir.ump.edu.my/id/eprint/42606/2/The%20application%20of%20artificial%20neural%20networks%20in%20predicting%20blood%20pressure%20levels%20of%20youth%20archers%20by%20means%20of%20anthropometric%20indexes_ABS.pdf Musa, Rabiu Muazu and Muhammad Zuhaili, Suhaimi and P. P. Abdul Majeed, Anwar and Mohamad Razali, Abdullah and Siti Musliha, Mat-Rasid and Mohd Hasnun Ariff, Hassan (2020) The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes. In: Lecture Notes in Bioengineering. Springer, Berlin, Germany, pp. 348-357. ISBN ISSN : 2195-271X https://doi.org/10.1007/978-981-15-3270-2_37 https://doi.org/10.1007/978-981-15-3270-2_37 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Musa, Rabiu Muazu Muhammad Zuhaili, Suhaimi P. P. Abdul Majeed, Anwar Mohamad Razali, Abdullah Siti Musliha, Mat-Rasid Mohd Hasnun Ariff, Hassan The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title | The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title_full | The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title_fullStr | The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title_full_unstemmed | The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title_short | The application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| title_sort | application of artificial neural networks in predicting blood pressure levels of youth archers by means of anthropometric indexes |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/42606/1/The%20application%20of%20artificial%20neural%20networks%20in%20predicting.pdf http://umpir.ump.edu.my/id/eprint/42606/2/The%20application%20of%20artificial%20neural%20networks%20in%20predicting%20blood%20pressure%20levels%20of%20youth%20archers%20by%20means%20of%20anthropometric%20indexes_ABS.pdf |
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