On performance and perceived effort in trail runners using sensor control to generate biosynchronous music

Williams, DAH ORCID: https://orcid.org/0000-0003-4793-8330, Fazenda, BM ORCID: https://orcid.org/0000-0002-3912-0582, Williamson, V ORCID: https://orcid.org/0000-0002-1985-8547 and Fazekas, G 2020, 'On performance and perceived effort in trail runners using sensor control to generate biosynchronous music' , Sensors, 20 (16) , e4528.

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Music has been shown to be capable of improving runners’ performance in treadmill and laboratory-based experiments. This paper evaluates a generative music system, namely HEARTBEATS, designed to create biosignal synchronous music in real-time according to an individual athlete’s heartrate or cadence (steps per minute). The tempo, melody, and timbral features of the generated music are modulated according to biosensor input from each runner using a combination of PPG (Photoplethysmography) and GPS (Global Positioning System) from a wearable sensor, synchronized via Bluetooth. We compare the relative performance of athletes listening to music with heartrate and cadence synchronous tempos, across a randomized trial (N = 54) on a trail course with 76 ft of elevation. Participants were instructed to continue until their self-reported perceived effort went beyond an 18 using the Borg rating of perceived exertion. We found that cadence-synchronous music improved performance and decreased perceived effort in male runners. For female runners, cadence synchronous music improved performance but it was heartrate synchronous music which significantly reduced perceived effort and allowed them to run the longest of all groups tested. This work has implications for the future design and implementation of novel portable music systems and in music-assisted coaching.

Item Type: Article
Additional Information: ** From MDPI via Jisc Publications Router ** Licence for this article: https://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 1424-8220 **History: published 13-08-2020; accepted 30-07-2020
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Sensors
Publisher: MDPI
ISSN: 1424-8220
Related URLs:
SWORD Depositor: Publications Router
Depositing User: Publications Router
Date Deposited: 18 Aug 2020 12:42
Last Modified: 16 Feb 2022 05:22
URI: https://usir.salford.ac.uk/id/eprint/57952

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