Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles
The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Safety |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-576X/9/2/29 |
| _version_ | 1797592683871469568 |
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| author | Rosemary Seva Imanuel Luir del Rosario Lorenzo Miguel Peñafiel John Michael Young Edwin Sybingco |
| author_facet | Rosemary Seva Imanuel Luir del Rosario Lorenzo Miguel Peñafiel John Michael Young Edwin Sybingco |
| author_sort | Rosemary Seva |
| collection | DOAJ |
| description | The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road. |
| first_indexed | 2024-03-11T01:57:35Z |
| format | Article |
| id | doaj.art-05a2167aa09a4fea81907d40e8193c28 |
| institution | Directory Open Access Journal |
| issn | 2313-576X |
| language | English |
| last_indexed | 2024-03-11T01:57:35Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Safety |
| spelling | doaj.art-05a2167aa09a4fea81907d40e8193c282023-11-18T12:29:17ZengMDPI AGSafety2313-576X2023-04-01922910.3390/safety9020029Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication GogglesRosemary Seva0Imanuel Luir del Rosario1Lorenzo Miguel Peñafiel2John Michael Young3Edwin Sybingco4Department of Industrial and Systems Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, PhilippinesDepartment of Industrial and Systems Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, PhilippinesDepartment of Industrial and Systems Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, PhilippinesDepartment of Industrial and Systems Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, PhilippinesDepartment of Electronics and Computer Engineering, De La Salle University, 2401 Taft Ave., Malate, Manila 1004, PhilippinesThe movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road.https://www.mdpi.com/2313-576X/9/2/29accident preventionalcohol intoxicationdeep learning |
| spellingShingle | Rosemary Seva Imanuel Luir del Rosario Lorenzo Miguel Peñafiel John Michael Young Edwin Sybingco Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles Safety accident prevention alcohol intoxication deep learning |
| title | Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles |
| title_full | Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles |
| title_fullStr | Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles |
| title_full_unstemmed | Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles |
| title_short | Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles |
| title_sort | predicting intoxication using motorcycle and head movements of riders wearing alcohol intoxication goggles |
| topic | accident prevention alcohol intoxication deep learning |
| url | https://www.mdpi.com/2313-576X/9/2/29 |
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