Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.
References
[1]
LaJeunesse, S., Ryus, P., Kumfer, W., Kothuri, S. and Nordback, K. (2021) Measuring Pedestrian Level of Stress in Urban Environments: Naturalistic Walking Pilot Study. Transportation Research Record, 2675, 109-119. https://doi.org/10.1177/03611981211010183
[2]
Zhang, Z., Amegbor, P.M. and Sabel, C.E. (2021) Assessing the Current Integration of Multiple Personalised Wearable Sensors for Environment and Health Monitoring. Sensors, 21, Article 7693. https://doi.org/10.3390/s21227693
[3]
Roe, J., Mondschein, A., Neale, C., Barnes, L., Boukhechba, M. and Lopez, S. (2020) The Urban Built Environment, Walking and Mental Health Outcomes Among Older Adults: A Pilot Study. Frontiers in Public Health, 8, Article ID: 575946. https://doi.org/10.3389/fpubh.2020.575946
[4]
Fathullah, A. and Willis, K. (2018) Engaging the Senses: The Potential of Emotional Data for Participation in Urban Planning. Urban Science, 2, Article 98. https://doi.org/10.3390/urbansci2040098
[5]
Sagl, G., Resch, B., Petutschnig, A., Kyriakou, K., Liedlgruber, M. and Wilhelm, F.H. (2019) Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors. Sensors, 19, Article 4448. https://doi.org/10.3390/s19204448
[6]
Kuncoro, C.B.D., Efendi, A. and Sakanti, M.M. (2023) Wearable Sensor for Psychological Stress Monitoring of Pregnant Woman-State of the Art. Measurement, 221, Article ID: 113556. https://doi.org/10.1016/j.measurement.2023.113556
[7]
Kyriakou, K., Resch, B., Sagl, G., Petutschnig, A., Werner, C., Niederseer, D., Liedlgruber, M., Wilhelm, F., Osborne, T. and Pykett, J. (2019) Detecting Moments of Stress from Measurements of Wearable Physiological Sensors. Sensors, 19, Article 3805. https://doi.org/10.3390/s19173805
[8]
Weissman, D.G. and Mendes, W.B. (2021) Correlation of Sympathetic and Parasympathetic Nervous System Activity during Rest and Acute Stress Tasks. International Journal of Psychophysiology, 162, 60-68. https://doi.org/10.1016/j.ijpsycho.2021.01.015
[9]
Birenboim, A., Dijst, M., Scheepers, F.E., Poelman, M.P. and Helbich, M. (2019) Wearables and Location Tracking Technologies for Mental-State Sensing in Outdoor Environments. The Professional Geographer, 71, 449-461. https://doi.org/10.1080/00330124.2018.1547978
[10]
Shoval, N., Schvimer, Y. and Tamir, M. (2018) Tracking Technologies and Urban Analysis: Adding the Emotional Dimension. Cities, 72, 34-42. https://doi.org/10.1016/j.cities.2017.08.005
[11]
Zeile, P. and Resch, B. (2018) Combining Biosensing Technology and Virtual Environments for Improved Urban Planning. Journal for Geographic Information Science, 6, 344-357. https://doi.org/10.1553/giscience2018_01_s344
[12]
Peabody, J.E., Ryznar, R., Ziesmann, M.T. and Gillman, L. (2023) A Systematic Review of Heart Rate Variability as a Measure of Stress in Medical Professionals. Curēus, 15, e34345-e34345. https://doi.org/10.7759/cureus.34345
[13]
Shaffer, F. and Ginsberg, J.P. (2017) An Overview of Heart Rate variability Metrics and Norms. Frontiers in Public Health, 5, 258-258. https://doi.org/10.3389/fpubh.2017.00258
[14]
Porges, S.W. (1995) Orienting in a Defensive World: Mammalian Modifications of our Evolutionary Heritage. A Polyvagal Theory. Psychophysiology, 32, 301-318. https://doi.org/10.1111/j.1469-8986.1995.tb01213.x
[15]
Sewell, M.W. (2022) Biometric Feedback System (U.S. Patent No. 11,501,501 B1). U.S. Patent and Trademark Office. https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11501501
[16]
Salahuddin, L., Cho, J., Jeong, M.G. and Kim, D. (2007) Ultra Short Term Analysis of Heart Rate Variability for Monitoring Mental Stress in Mobile Settings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, 22-26 August, 2007, 4656-4659. https://doi.org/10.1109/IEMBS.2007.4353378
[17]
Studio-X, Smith, G. (2023) MPATH Empathic Insights. https://empathic.greshamsmith.com/sharedata/327#getstarted
