A Mobile Sensing Approach to Stress Detection and Memory Activation for Public Bus Drivers

被引:43
|
作者
Rodrigues, Joao G. P. [1 ]
Kaiseler, Mariana [1 ,2 ]
Aguiar, Ana [1 ]
Silva Cunha, Joao P. [3 ]
Barros, Joao [1 ]
机构
[1] Univ Porto, Fac Engn, Inst Telecommun, Dept Engn Eletrotecn & Comp, P-4200465 Oporto, Portugal
[2] Leeds Beckett Univ, Inst Sport Phys Act & Leisure, Leeds LS1 3HE, W Yorkshire, England
[3] Univ Porto, Fac Engn, INESC TEC, Dept Engn Eletrotecn & Comp, P-4200465 Oporto, Portugal
关键词
Public transportation; driver; stress detection; wearable technologies; georeferenced data analysis; POWER SPECTRUM ANALYSIS; HEART-RATE-VARIABILITY; JOB; FEATURES; HASSLES; TRANSIT;
D O I
10.1109/TITS.2015.2445314
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The experience of daily stress among bus drivers has shown to affect physical and psychological health, and can impact driving behavior and overall road safety. Although previous research consistently supports these findings, little attention has been dedicated to the design of a stress detection method able to synchronize physiological and psychological stress responses of public bus drivers in their day-to-day routine work. To overcome this limitation, we propose a mobile sensing approach to detect georeferenced stress responses and facilitate memory recall of the stressful situations. Data were collected among public bus drivers in the city of Porto, Portugal (145 h, 36 bus drivers, +2300 km), and results supported the validation of our approach among this population and allowed us to determine specific stressor categories within certain areas of the city. Furthermore, data collected throughout the city allowed us to produce a citywide "stress map" that can be used for spotting areas in need of local authority intervention. The enriching findings suggest that our system can be a promising tool to support applied occupational health interventions for public bus drivers and guide authorities' interventions to improve these aspects in "future" cities.
引用
收藏
页码:3294 / 3303
页数:10
相关论文
共 11 条
  • [1] A Public Transport Bus as a Flexible Mobile Smart Environment Sensing Platform for IoT
    Kang, Lin
    Poslad, Stefan
    Wang, Weidong
    Li, Xiuhua
    Zhang, Yinghai
    Wang, Chaowei
    12TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENVIRONMENTS - IE 2016, 2016, : 1 - 8
  • [2] SYSTEMATIC APPROACH TO PUBLIC TRANSPORT DRIVERS STRESS PREVENTION
    Kureckova, Veronika
    Simecek, Michal
    INPACT 2014: INTERNATIONAL PSYCHOLOGICAL APPLICATIONS CONFERENCE AND TRENDS, 2014, : 200 - 202
  • [3] A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers
    Tu, Wei
    Wei, Lei
    Hu, Wenyan
    Sheng, Zhengguo
    Nicanfar, Hasen
    Hu, Xiping
    Ngai, Edith C. -H.
    Leung, Victor C. M.
    SMART CITY 360, 2016, 166 : 3 - 15
  • [4] Occupational stress, neuroticism, and psychological well-being among public bus drivers in Hong Kong
    Wong, CK
    Lai, CLJ
    INTERNATIONAL JOURNAL OF PSYCHOLOGY, 2004, 39 (5-6) : 439 - 440
  • [5] Assessing Driving Behavior in Macau Public Transportation Through Mobile Crowd Sensing: A Study of the Macau Bus Passenger Profile
    Ma, Fei Chun
    Tong, Sok Han
    Cheang, Tak Son
    Cordeiro, Joao
    INTELLIGENT TRANSPORT SYSTEMS - FROM RESEARCH AND DEVELOPMENT TO THE MARKET UPTAKE, INTSYS 2017, 2018, 222 : 31 - 39
  • [6] An Explainable Machine Learning Approach Based on Statistical Indexes and SVM for Stress Detection in Automobile Drivers Using Electromyographic Signals
    Vargas-Lopez, Olivia
    Perez-Ramirez, Carlos A.
    Valtierra-Rodriguez, Martin
    Yanez-Borjas, Jesus J.
    Amezquita-Sanchez, Juan P.
    SENSORS, 2021, 21 (09)
  • [7] A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms
    Ravi Prasad Thati
    Abhishek Singh Dhadwal
    Praveen Kumar
    Sainaba P
    Multimedia Tools and Applications, 2023, 82 : 4787 - 4820
  • [8] A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms
    Thati, Ravi Prasad
    Dhadwal, Abhishek Singh
    Kumar, Praveen
    Sainaba, P.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (04) : 4787 - 4820
  • [9] An Approach for Real-Time Stress-Trend Detection Using Physiological Signals in Wearable Computing Systems for Automotive Drivers
    Singh, Rajiv Ranjan
    Conjeti, Sailesh
    Banerjee, Rahul
    2011 14TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2011, : 1477 - 1482
  • [10] INTRA-CANOPY SENSING USING MULTI-ROTOR SUAS: A NEW APPROACH FOR CROP STRESS DETECTION AND DIAGNOSIS
    Wiegman, Christopher R.
    Venkatesh, Ramarao
    Shearer, Scott A.
    JOURNAL OF THE ASABE, 2022, 65 (04): : 913 - 925