Editorial: Remote assessment, measurement, and delivery in sport, physical activity and health

Daniel J Peart ^1* Michael Graham ² David E Lunn ³ Naomi Burn ⁴ John Derek Franklin ^2* John B Arnold ⁴

• ¹ Northumbria University, Newcastle upon Tyne, North East England, United Kingdom
• ² Teesside University, Middlesbrough, England, United Kingdom
• ³ Leeds Beckett University, Leeds, England, United Kingdom
• ⁴ University of South Australia, Adelaide, Australia

IntroductionTechnology has had an increasing influence on our lives for some time, and this was acceleratedby the enforced remote way of working five years ago. The first paper in this special topic fromChahin-Inostroza et al. (1) articulates some of the challenges faced during this time as countriesacross the world enforced distancing measures and remote working to control the spread ofCOVID-19. Sport was not exempt, and both national and global events were put on standby.However, this not only affected elite athletes, but amateur athletes too had fewer opportunities tosocialise with peers and receive feedback and advice. In their cross-section of amateur Chileanathletes, Chahin-Inostroza and colleagues (1) report how the use of some technologies and trainingsoftware changed during periods of quarantine, and remained elevated when quarantine ended.The increase in remote technology acceptance and usage in sport, health and exercise could presentan opportunity to move interventions and data collection out of the laboratory or any other fixedlocation to improve accessibility. However, researchers, practitioners and participants need to beconfident that the data collected, processed and analysed in this way is reliable, valid andtrustworthy, and that these aspects are not sacrificed as we strive to harness the opportunities andconvenience offered by such technology. Therefore, it is important that there is an evolvingevidence base as the technology itself evolves.The goal of this collection was to share evidence regarding remote data collection and interventionin sport, health and exercise sciences to support academics, practitioners and teachers to makeevidence informed decisions about the implementation of such technology.This editorial summarises three areas of interest that are informed by the papers within this specialedition.Validity of information integration based on subjective and physiological data from a realsports condition: application to the judgment of fatigue in sportThe measurement and assessment of fatigue in both sporting and health care contexts remainschallenging (2, 3) however, researchers, practitioners and athletes are becoming increasinglyaware of the impact of fatigue on performance and injury risk (4). If researchers can develop avalid and reliable method to effectively measure this construct remotely this could have real lifeapplication for developing training sessions with athletes.The paper by Legall et al (5) highlights that current subjective measures of fatigue do not allowfor the investigation into the possible cognitive processes that may be involved in how anindividual generates and perceives fatigue. This paper attempts to explore this by assessing ifexercise duration and intensity are used to create a judgement of fatigue. In this study 20 healthy,experienced participants conducted a laboratory session where they provided subjective self-reported fatigue scores based on six different cycling scenarios (15 or 30 mins at 30, 50 or 70%maximum intensity). They then undertook each of the six scenarios in a sports hall to see if theperceived fatigue score correlated with the actual fatigue score, as well as collecting objectivemeasures of fatigue. This study shows that all three measures of fatigue correlated with each other,which provides evidence of a correlation between physiological and psychological measures offatigue. Legall and colleagues (5) argue that this could be used as a judgement indicator that mayallow for more precise and individualised training programmes, although they highlighted thatathletes may underestimate their fatigue levels at higher workloads.Quantifying lumbar sagittal plane kinematics using a wrist-worn inertial measurement unitMeasuring human movement is important in many different contexts including health, sport andphysical activity. Until recently, accurate measurement of human movement has been confined towell controlled laboratory environments. This limits the environments where data is collected andlimits the ecological validity of many measurements. However, recent advancements in remotemonitoring have enabled human movement measurement outside the laboratory. Examples ofremote monitoring in the context of human movement include markerless motion capture (6) andwearable sensors (7).Wearable sensors, such as inertial measurement units (IMUs), are often small devices attached tothe human body and often consist of gyroscopes and accelerometers allowing for a range ofbiomechanical variables to be calculated. However, the reliability and validity of these devices isstill being assessed (8), particularly when movement data can only be measured using devicesworn on the area of interest.To understand the transferability of information from lumbar worn sensors to wrist worn sensors,the paper by Liew et al (9) in this special issue tested the feasibility of using a wrist-worn IMU toinfer lumbar sagittal plane kinematics as a substitute for a lumbar-worn IMU. Eighteen healthyparticipants performed spinal flexion and extension movements while wearing IMUs on the wristand lumbar spine. The results showed that flexion range of motion (RoM) was the only variablewith a statistically significant difference between sensor locations, with a mean difference of 4.54°(95% CI = 1.82°–7.27°). However, the maximal difference across all outcomes was less than 8°,suggesting that wrist-worn IMUs may provide a practical solution for remote lumbar mobilitymonitoring, potentially leading to more ergonomically acceptable methods of collecting lumbarspine data. Despite this potential, challenges remain. The accuracy of wrist-worn IMUs may beinfluenced by individual anthropometric differences and movement speeds. Further research isneeded to validate this method across different populations and movement conditions. Nonetheless,wrist-worn IMUs may present an alternative approach for remote lumbar mobility assessment,particularly in rehabilitation contexts where self-monitoring is essential.Promoting physical activity and a healthy active lifestyle in community-dwelling olderadults: a design thinking approach for the development of a mobile health applicationMobile health (mHealth) applications have become an integral part of modern healthcare,leveraging the ubiquity of smartphones and wearable devices to improve health outcomes, andplace a growing emphasis on more accessible, personalised healthcare. These applicationsencompass a broad range of functions, from monitoring chronic conditions and offering mentalhealth support to providing medication reminders and tracking physical activity (10).The paper from Daniels et al (11) in this issue focusses on the public health challenge of engagingolder adults (>65 years old) in PA and provides a qualitative synthesis of barriers and facilitatorsto PA in older adults. Outputs from one-to-one interviews (phase 1) directly informed the co-creation of an mHealth app prototype (phase 2) to promote an active lifestyle to community-dwelling older adults. The authors employ co-creation sessions with older adults and topic experts,underpinned by design thinking methodology (12). The co-produced mHealth prototype was thentested in a population of community-dwelling older adults (phase 3). This study highlights thediverse perceptions of PA engagement in this population, with key considerations for both theirown co-created mHealth app and future studies interested in the development of remote PApromotion in older adults.Challenges persist regarding data privacy and app efficacy (13), along with the need for furtherevaluation, particularly among those with limited digital access. As mHealth applications continueto develop, it holds the potential to transform how individuals manage their health and interactwith healthcare systems globally.SummaryTechnology in sport and health has accelerated the inclusion of remote data collection and mobileapplications. Current research reports on the increased use of technology in this way, the validityand feasibility of these measures, and the development of mobile health apps for promotingphysical activity. Despite promising advancements, challenges like data reliability, privacy, andaccessibility remain.