{"title":"Exploring the preferred load pattern and physiological intensity for on-road exercising with electrically assisted bicycles","authors":"Sheng-Chieh Yang , Yun-Ju Lee","doi":"10.1016/j.jth.2024.101831","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>Electrically-assisted bicycle (e-bike) riding is associated with health and environmental benefits. Through controlling assistive power and transmission settings, e-bike riders could theoretically manage their physical load to a preferred level under environmental resistance. The study aimed to examine whether using e-bikes for transportation can provide health benefits, despite barriers such as control complexity, and to assess if the physical activity associated with e-bike riding meets the recommended health standards.</p></div><div><h3>Methods</h3><p>A simulated indoor e-bike riding session with disturbances of environmental resistance was conducted to investigate riders' preferred load, control behaviors, and physiological and subjective responses. During the riding session, participants completed seven consecutive 3-min stages with preset resistance changes. They were directed to maintain their preferred resistance by adjusting the e-bike's assistive level and transmission.</p></div><div><h3>Results</h3><p>Twenty-three non-athlete participants completed the simulated e-bike riding session. The preferred load ranged from 0.92 to 1.17 W/kg (watts/body mass). It resulted in a moderate heart rate (66.77% maximal heart rate), metabolic equivalent of task (5.41 MET), and rate of perceived exertion (RPE: 12). The participants kept a stable intensity, regardless of higher or lower power output demand induced by the environmental resistance. Most of the e-bike controls take place right after external resistance changes. In contrast, only a tiny amount occurred at the end of each stage, indicating the urgent intent to retain the preferred intensity.</p></div><div><h3>Conclusions</h3><p>The preferred riding load and corresponding intensity were characterized by a stable pattern. An e-bike control strategy with a default assistive mode was suggested to automatically keep the rider's load at 0.92–1.17 W/kg, which might decrease the required manual controls, especially in variegated external resistance situations. Moreover, the moderate physiological responses induced by the self-selected intensity meet the criteria for generating health benefits and support the advocacy of on-road exercising by e-bikes.</p></div>","PeriodicalId":47838,"journal":{"name":"Journal of Transport & Health","volume":"37 ","pages":"Article 101831"},"PeriodicalIF":3.2000,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transport & Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221414052400077X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
Electrically-assisted bicycle (e-bike) riding is associated with health and environmental benefits. Through controlling assistive power and transmission settings, e-bike riders could theoretically manage their physical load to a preferred level under environmental resistance. The study aimed to examine whether using e-bikes for transportation can provide health benefits, despite barriers such as control complexity, and to assess if the physical activity associated with e-bike riding meets the recommended health standards.
Methods
A simulated indoor e-bike riding session with disturbances of environmental resistance was conducted to investigate riders' preferred load, control behaviors, and physiological and subjective responses. During the riding session, participants completed seven consecutive 3-min stages with preset resistance changes. They were directed to maintain their preferred resistance by adjusting the e-bike's assistive level and transmission.
Results
Twenty-three non-athlete participants completed the simulated e-bike riding session. The preferred load ranged from 0.92 to 1.17 W/kg (watts/body mass). It resulted in a moderate heart rate (66.77% maximal heart rate), metabolic equivalent of task (5.41 MET), and rate of perceived exertion (RPE: 12). The participants kept a stable intensity, regardless of higher or lower power output demand induced by the environmental resistance. Most of the e-bike controls take place right after external resistance changes. In contrast, only a tiny amount occurred at the end of each stage, indicating the urgent intent to retain the preferred intensity.
Conclusions
The preferred riding load and corresponding intensity were characterized by a stable pattern. An e-bike control strategy with a default assistive mode was suggested to automatically keep the rider's load at 0.92–1.17 W/kg, which might decrease the required manual controls, especially in variegated external resistance situations. Moreover, the moderate physiological responses induced by the self-selected intensity meet the criteria for generating health benefits and support the advocacy of on-road exercising by e-bikes.