Authors:
Magno Mendes
;
Gonçalo Duarte
and
Patricia Baptista
Affiliation:
Universidade de Lisboa, Portugal
Keyword(s):
physiological signals; heart rate; electric and conventional bicycles monitoring
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Human-Computer Interaction
;
Pattern Recognition
;
Pervasive Technologies
;
Physiological Computing Systems
;
Software Engineering
Abstract:
Bicycle use in urban environments is an alternative mobility option, which enables people to travel longer, faster and with less effort than walking, with low environmental impacts. The use of electric bicycles (EB) has risen as another possibility to promote a more efficient transportation use. However, the quantification of the real impacts for the biker of shifting from conventional (CB) to EB is not yet quantified. This research work aims at estimating the impacts on physiological signals, namely, on heart rate, from using EB instead of CB, using a suitable methodology for on-road bio-signals data analysis. The on-road monitoring of 6 bikers, 2 routes and 3 bicycles in Lisbon presented a 57% average reduction in HR variation from using EB, since under high power demanding situations, the electric motor attenuates human effort. It was also possible to estimate the energy expenditure associated to the human effort that results from using the bicycles. For the CB the total energy sp
ent reaches ≈70 Wh/km, while the EB presents ≈51 Wh/km of human energy (28% lower than the CB) and ≈9 Wh/km of electricity consumption, resulting in a total of ≈60 Wh/km. Consequently, the total energy per km is 14% lower in the EB compared to the CB.
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