ArticleSensors (Basel, Switzerland)2022
Implementation of a Low-Cost Data Acquisition System on an E-Scooter for Micromobility Research.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Data-Minimizing Motion-Gated Artificial Intelligence Decision Support for Electric Micro-Mobility: An Architecture-Feasibility Study.Sensors (Basel, Switzerland) · 2026Article
- Development of a Semi-Automated Tool Based on Computer Vision Methods for Safety Assessment of Micromobility Users.Sensors (Basel, Switzerland) · 2026Article
- Development of a Micromobility Riding Evaluation Platform for an Indoor Riding Lane Based on Multi-View Overhead Video Integration.Sensors (Basel, Switzerland) · 2026Article
- Network-Wide GIS Mapping of Cycling Vibration Comfort: From Methodology to Real-World Implementation.Sensors (Basel, Switzerland) · 2025Article
- Evaluating Bicycle Path Roughness: A Comparative Study Using Smartphone and Smart Bicycle Light Sensors.Sensors (Basel, Switzerland) · 2024Article
- An AI Safety Monitoring System for Electric Scooters Based on the Number of Riders and Road Types.Sensors (Basel, Switzerland) · 2023Article
- BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool.Sensors (Basel, Switzerland) · 2023Article
- Torque Measurement and Control for Electric-Assisted Bike Considering Different External Load Conditions.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
In recent years, cities are experiencing changes in the ways of moving around, increasing the use of micromobility vehicles. Bicycles are the most widespread transport mode and, therefore, cyclists' behaviour, safety, and comfort have been widely studied. However, the use of other personal mobility vehicles is increasing, especially e-scooters, and related studies are scarce. This paper proposes a low-cost open-source data acquisition system to be installed on an e-scooter. This system is based on Raspberry Pi and allows collecting speed, acceleration, and position of the e-scooter, the lateral clearance during meeting and overtaking manoeuvres, and the vibrations experienced by the micromobility users when riding on a bike lane. The system has been evaluated and tested on a bike lane segment to ensure the accuracy and reliability of the collected data. As a result, the use of the proposed system allows highway engineers and urban mobility planners to analyse the behaviour, safety, and comfort of the users of e-scooters. Additionally, the system can be easily adapted to another micromobility vehicle and used to assess pavement condition and micromobility users' riding comfort on a cycling network when the budget is limited.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.