Mohd Shah, Muhammad Azraie (2022) Mathematical analysis of heart rate for driving fatigue using Box-Behnken design. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)
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Abstract
Driver distraction due to fatigue is recognized as one of the major factors of road crashes, leading in thousands of incidents and deaths each year. Fatigue drivers have potential for falling asleep at the wheel, misjudge speed and distance and impair reaction time and decision making, which can result in road accident. Therefore, the main purpose for this study is to develop and validate the regression models to relate the relationship between input process parameters which is driving speed, driving duration, body mass index (BMI), gender and type of road, and an output response which is heart rate that cause driving fatigue. Six qualified and healthy drivers were used as the experiment’s respondents: three male and three female. Pulse oximeter SMH-01 has been used in this research as the heart rate monitor. Design Expert 8.0.6 software was used for the regression analysis. The regression model was successfully developed and validated. The results indicate that actual heart rate data from the validation runs fall within the 95% prediction interval and the residual errors are ranging from 0.001% to 3.88%, which in absolute value is less than 10%. The significant parameters that influenced the heart rate were also identified. Heart rate was influenced by the driving speed, driving duration, BMI, gender, and type of road. The author believes that the development of psychophysical factor models for the driver fatigue problem among Malaysian using regression analysis is a new contribution to the body of knowledge.
Item Type: | Final Year Project (Project Report) |
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Uncontrolled Keywords: | Experimental design, Response surfaces (Statistic), Computer programs, Regression analysis, Heart rate monitoring |
Subjects: | Q Science > QA Mathematics |
Divisions: | Library > Final Year Project > FKP |
Depositing User: | Mr Eiisaa Ahyead |
Date Deposited: | 06 Apr 2023 02:05 |
Last Modified: | 17 Dec 2024 03:52 |
URI: | http://digitalcollection.utem.edu.my/id/eprint/29487 |
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