Repository logo
Log In(current)
  1. Home
  2. Colleges & Schools
  3. Graduate School
  4. Doctoral Dissertations
  5. PHYSICAL HEALTH, TRANSPORTATION AND SUSTAINABILITY IMPACTS OF SHARED MICROMOBILITY SERVICES
Details

PHYSICAL HEALTH, TRANSPORTATION AND SUSTAINABILITY IMPACTS OF SHARED MICROMOBILITY SERVICES

Date Issued
May 1, 2024
Author(s)
Wen, Yi
Advisor(s)
Christopher R. Cherry
Additional Advisor(s)
Candace E. Brakewood, Lee D. Han, David R. Bassett, Hamparsum Bozdogan
Abstract

Electric scooters (e-scooters) have reached a wide popularity since launch in 2017. Key questions around their mobility, safety and sustainability impacts have been raised and partially addressed by the existing literature. However, the physical activity aspects of riding an e-scooter have not been assessed. We recruited 20 subjects from the University of Tennessee, Knoxville network to measure the physical and muscle activity of riding an e-scooter, in comparison to walking and driving, the two common substitutes by e-scooters on a designated route. We used Cosmed Fitmate PRO for the physical activity measurement and the Delsys EMGworks Acquisition Software for the EMG data. Our results show that riding an e-scooter cannot provide moderate-intensity physical activity (MET=2.14) and should not be considered as active transportation, even when riding on uphill segments. However, it does provide more muscle activities compared to driving especially in the upper limb muscle group. We found that riding an e-scooter provides less physical activity than walking but more than driving both at the 95% confidence level. Policies that concern health should target at replacing car trips (driving and ride-hailing) with e-scooters without interfering the walking, biking and other active modes.

Subjects

micromobility

health

transportation

sustainability

shared mobility

China

Degree
Doctor of Philosophy
Major
Civil Engineering
File(s)
Thumbnail Image
Name

Yi_Wen_PhD_Dissertation___Final_for_Formatting_Review___6.docx

Size

4.95 MB

Format

Microsoft Word XML

Checksum (MD5)

9691eec43258058bdbc7f41faaca848e

Thumbnail Image
Name

auto_convert.pdf

Size

2.1 MB

Format

Adobe PDF

Checksum (MD5)

2f6cfb66a3fe2b4bf2feaed69757e182

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback
  • Contact
  • Libraries at University of Tennessee, Knoxville
Repository logo COAR Notify