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Towards Risk Indication In Mountain Biking Using Smart Wearables

Authors:

Andreas ButzAuthors Info & Claims

CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Article No.: 467, Pages 1 - 7

https://doi.org/10.1145/3411763.3451746

Published: 08 May 2021 Publication History

Abstract

Mountain biking as a recreational sport is currently thriving. During the ongoing COVID-19 pandemic, even more people started compensating for a lack of activity through individual outdoor sports, such as cycling. However, when executed beyond paved forest roads, mountain biking is a sport with subjective and objective risks, in which crashes often can not be entirely avoided and athletes may get injured. In this late-breaking work, we showcase a concept for a crash risk indication application for sports smartwatches. First, we review a wide range of related work, which formed the basis for our crash risk indication metric. We discuss options for the sensor-based detection of internal and external risk factors and propose a way to aggregate them, which will allow dynamic and potentially automatic fine-tuning by observing or obtaining feedback from the athlete. In addition, we present a concept for a smartwatch application that will provide constant feedback and an unobtrusive signal to the athlete when an unusually high risk is detected. Finally, we give an outlook on the necessary steps to implement our approach as a smartwatch app.

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Cited By

EKİNCİ E(2023)AÇIK ALAN REKREASYON AKTİVİTELERİNDE DİJİTAL TEKNOLOJİLERİN KULLANIMITHE USE OF DIGITAL TECHNOLOGIES IN OUTDOOR RECREATION ACTIVITIESSpor ve Rekreasyon Araştırmaları Dergisi10.52272/srad.13537895:2(108-124)Online publication date: 30-Dec-2023
https://doi.org/10.52272/srad.1353789

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cover image ACM Conferences

CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

May 2021

2965 pages

ISBN:9781450380959

DOI:10.1145/3411763

Editors:
Yoshifumi Kitamura
Tohoku University, Japan
,
Aaron Quigley
University of New South Wales, Australia
,
Katherine Isbister
University of California Santa Cruz, USA
,
Takeo Igarashi
The University of Tokyo, Japan

Copyright © 2021 ACM.

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Published: 08 May 2021

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CHI '21: CHI Conference on Human Factors in Computing Systems

May 8 - 13, 2021

Yokohama, Japan

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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EKİNCİ E(2023)AÇIK ALAN REKREASYON AKTİVİTELERİNDE DİJİTAL TEKNOLOJİLERİN KULLANIMITHE USE OF DIGITAL TECHNOLOGIES IN OUTDOOR RECREATION ACTIVITIESSpor ve Rekreasyon Araştırmaları Dergisi10.52272/srad.13537895:2(108-124)Online publication date: 30-Dec-2023
https://doi.org/10.52272/srad.1353789

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