Evidence map›Paper›PMID 32823519›Full record

ArticleSensors (Basel, Switzerland)2020

On Performance and Perceived Effort in Trail Runners Using Sensor Control to Generate Biosynchronous Music.

Duncan Williams, Bruno Fazenda, Victoria Williamson, György Fazekas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Duncan WilliamsSchool of Computing, Science & Engineering, the University of Salford, the Crescent, Salford M5 4WT, UK.ORCID 0000-0003-4793-8330
Bruno FazendaSchool of Computing, Science & Engineering, the University of Salford, the Crescent, Salford M5 4WT, UK.ORCID 0000-0002-3912-0582
Victoria WilliamsonLucerne University of Applied Sciences and Arts, 6002 Luzern, Switzerland.ORCID 0000-0002-1985-8547
György FazekasSchool of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4FZ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Monitoring, PhysiologicMusicRunningAthletesExercise TestFemaleHeart RateHumansMaleWearable Electronic Devicesalgorithmic compositionbiosynchronous music generationmusic mediated perceived effortmusic perceptionphysical activityrunning

Identifiers

PMID32823519
PMCPMC7472014

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.