The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/4c91188a-ccdd-418e-a570-75497113096e

Boot, Mario; Geurs, Karst; Ulak, Baran; Havinga, Paul ; Dees, Dees et. al. (2023): Dataset supporting the paper "Measuring and Supporting Simultaneous Flow in Duos of Elderly Cyclists". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/4c91188a-ccdd-418e-a570-75497113096e.v1

Dataset

• Civil Engineering
• Other Psychology and Cognitive Sciences
• Cognitive Sciences
• Psychology
• Other Information and Computing Sciences
• Engineering
• Psychology and Cognitive Sciences
• Technology
• Information and Computing Sciences

bicycles, cadence, elderly, experience, flow, heart rate, sensor

CC BY 4.0

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by Mario Boot , Karst Geurs , Baran Ulak , Paul Havinga , Dees Dees , Laura Kahnt

This study investigates how simultaneous flow during cycling experiences can be measured and supported among duos of elderly cyclists, a demographic with increasing e-bike usage. We collected heart rate, cadence, and position data together with participant-generated labels in an experimental study with 21 participants. Data was collected via sensors on the bicycles and on the human participants, as well as via a forward-facing action camera on the bicycle handlebar. Via a post-ride video-based recall method, participants generated labels for each 30-second time window, indicating whether or not they where in individual flow in that time window. The sensor data and participant labels are shared in CSV data. The video recordings are not shared because anonimization was out of scope for the study, however the research team can be contacted in case of interest in these recordings. 

• 2023-11-09 first online, published, posted

4TU.ResearchData

Cadence data: Garmin FIT files in *.fit format. Empatica data: *.zip files containing *.txt and *.csv files. Processed data: Excel files in *.xlsx format. Scripts: Jupyter notebooks in *.ypnb format, and R script in *.r format.

• Project Smart Connected Bikes (grant code 18006) NWO Smart Industries 2019

University of Twente, Faculty of Engineering Technology (ET), Transport Engineering & Management (TEM) Research Group.
Accell Group, Heerenveen, the Netherlands.