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Vaz JR, Cortes N, Gomes JS, Reis JF, Stergiou N. Stride-to-stride variability is altered when running to isochronous visual cueing but remains unaltered with fractal cueing. Sports Biomech 2024:1-13. [PMID: 38164700 DOI: 10.1080/14763141.2023.2298958] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/15/2023] [Indexed: 01/03/2024]
Abstract
Running synchronised to external cueing is often implemented in both clinical and training settings, and isochronous cueing has been shown to improve running economy. However, such cueing disregards the natural stride-to-stride fluctuations present in human locomotion which is thought to reflect higher levels of adaptability. The present study aimed to investigate how alterations in the temporal structure of cueing affect stride-to-stride variability during running. We hypothesised that running using cueing with a fractal-like structure would preserve the natural stride-to-stride variability of young adults. Thirteen runners performed four 8-min trials: one uncued (UNC) trial and three cued trials presenting an isochronous (ISO), a fractal (FRC) and a random (RND) structure. Repeated measures ANOVAs were used to identify changes in the dependent variables. We have found no main effect on the cardiorespiratory parameters, whereas a significant main effect was observed in the temporal structure of stride-to-stride variability. During FRC, the participants were able to retain the fractal patterns of their natural locomotor variability observed during the UNC condition, while during the ISO and RND they exhibited more random of fluctuations (i.e., lower values of fractal scaling). Our results demonstrate that cueing based on the natural stride-to-stride fluctuations opens new avenues for training and rehabilitation.
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Affiliation(s)
- João R Vaz
- Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Egas Moniz - Cooperativa de Ensino Superior, Monte da Caparica, Portugal
- CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
- Division of Biomechanics and Research Development, Department of Biomechanics, and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, USA
| | - Nelson Cortes
- School of Sport, Rehabilitation and Exercise Sciences, University of Essex, Colchester, UK
- Department of Bioengineering, George Mason University, Fairfax, VA, USA
| | - João S Gomes
- Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Egas Moniz - Cooperativa de Ensino Superior, Monte da Caparica, Portugal
- CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | - Joana F Reis
- CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | - Nick Stergiou
- Division of Biomechanics and Research Development, Department of Biomechanics, and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, USA
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Pegoraro N, Rossini B, Giganti M, Brymer E, Monasterio E, Bouchat P, Feletti F. Telemedicine in Sports under Extreme Conditions: Data Transmission, Remote Medical Consultations, and Diagnostic Imaging. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6371. [PMID: 37510603 PMCID: PMC10380087 DOI: 10.3390/ijerph20146371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 06/11/2023] [Accepted: 06/17/2023] [Indexed: 07/30/2023]
Abstract
Telemedical technologies provide significant benefits in sports for performance monitoring and early recognition of many medical issues, especially when sports are practised outside a regulated playing field, where participants are exposed to rapidly changing environmental conditions or specialised medical assistance is unavailable. We provide a review of the medical literature on the use of telemedicine in adventure and extreme sports. Out of 2715 unique sport citations from 4 scientific databases 16 papers met the criteria, which included all research papers exploring the use of telemedicine for monitoring performance and health status in extreme environments. Their quality was assessed by a double-anonymised review with a specifically designed four-item scoring system. Telemedicine was used in high-mountain sports (37.5%; n = 6), winter sports (18.7%; n = 3), water sports (25%; n = 4), and long-distance land sports (18.7%; n = 3). Telemedicine was used for data transfer, teleconsulting, and the execution of remote-controlled procedures, including imaging diagnostics. Telemedical technologies were also used to diagnose and treat sport-related and environmentally impacted injuries, including emergencies in three extreme conditions: high mountains, ultraendurance activities, and in/under the water. By highlighting sport-specific movement patterns or physiological and pathological responses in extreme climatic conditions and environments, telemedicine may result in better preparation and development of strategies for an in-depth understanding of the stress of the metabolic, cardiorespiratory, biomechanical, or neuromuscular system, potentially resulting in performance improvement and injury prevention.
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Affiliation(s)
- Nicola Pegoraro
- Dipartimento di Medicina Traslazionale e per la Romagna, Università degli Studi di Ferrara, 44122 Ferrara, Italy
| | - Benedetta Rossini
- Dipartimento di Medicina Traslazionale e per la Romagna, Università degli Studi di Ferrara, 44122 Ferrara, Italy
| | - Melchiore Giganti
- Dipartimento di Medicina Traslazionale e per la Romagna, Università degli Studi di Ferrara, 44122 Ferrara, Italy
| | - Eric Brymer
- Humans Sciences, Faculty of Health, Southern Cross University, Southern Cross Drive, Bilinga, QLD 4225, Australia
| | - Erik Monasterio
- Christchurch School of Medicine, University of Otago, Hillmorton Hospital, Private Bag 4733, Christchurch 8024, New Zealand
| | - Pierre Bouchat
- Psychological Sciences Research Institute, Université Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
| | - Francesco Feletti
- Dipartimento di Medicina Traslazionale e per la Romagna, Università degli Studi di Ferrara, 44122 Ferrara, Italy
- Dipartimento Diagnostica per Immagini-Ausl Romagna, U.O. Radiologia-Ospedale S. Maria delle Croci, 48121 Ravenna, Italy
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Direct Mobile Coaching as a Paradigm for the Creation of Mobile Feedback Systems. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
In sports feedback systems, digital systems perform tasks such as capturing, analysing and representing data. These systems not only aim to provide athletes and coaches with insights into performances but also help athletes learn new tasks and control movements, for example, to prevent injuries. However, designing mobile feedback systems requires a high level of expertise from researchers and practitioners in many areas. As a solution to this problem, we present Direct Mobile Coaching (DMC) as a design paradigm and model for mobile feedback systems. Besides components for feedback provisioning, the model consists of components for data recording, storage and management. For the evaluation of the model, its features are compared against state-of-the-art frameworks. Furthermore, the capabilities are benchmarked using a review of the literature. We conclude that DMC is capable of modelling all 39 identified systems while other identified frameworks (MobileCoach, Garmin Connect IQ SDK, RADAR) could (at best) only model parts of them. The presented design paradigm/model is applicable for a wide range of mobile feedback systems and equips researchers and practitioners with a valuable tool.
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Dobiasch M, Stafylidis S, Baca A. Effects of different feedback variants on pacing adherence in a field based running test. INT J PERF ANAL SPOR 2021. [DOI: 10.1080/24748668.2021.1968662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Martin Dobiasch
- Centre for Sport Science and University Sports, Department for Biomechanics, Kinesiology and Computer Science in Sport, University of Vienna, Vienna, Austria
| | - Savvas Stafylidis
- Centre for Sport Science and University Sports, Department for Biomechanics, Kinesiology and Computer Science in Sport, University of Vienna, Vienna, Austria
| | - Arnold Baca
- Centre for Sport Science and University Sports, Department for Biomechanics, Kinesiology and Computer Science in Sport, University of Vienna, Vienna, Austria
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Chatterjee A, Gerdes M, Prinz A, Martinez S. Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions With Information and Communication Technology: Systematic Review. J Med Internet Res 2021; 23:e23533. [PMID: 33759793 PMCID: PMC8074867 DOI: 10.2196/23533] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 12/28/2020] [Accepted: 02/15/2021] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND We systematically reviewed the literature on human coaching to identify different coaching processes as behavioral interventions and methods within those processes. We then reviewed how those identified coaching processes and the used methods can be utilized to improve an electronic coaching (eCoaching) process for the promotion of a healthy lifestyle with the support of information and communication technology (ICT). OBJECTIVE This study aimed to identify coaching and eCoaching processes as behavioral interventions and the methods behind these processes. Here, we mainly looked at processes (and corresponding models that describe coaching as certain processes) and the methods that were used within the different processes. Several methods will be part of multiple processes. Certain processes (or the corresponding models) will be applicable for both human coaching and eCoaching. METHODS We performed a systematic literature review to search the scientific databases EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MDPI, Google Scholar, and PubMed for publications that included personal coaching (from 2000 to 2019) and persuasive eCoaching as behavioral interventions for a healthy lifestyle (from 2014 to 2019). The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework was used for the evidence-based systematic review and meta-analysis. RESULTS The systematic search resulted in 79 publications, including 72 papers and seven books. Of these, 53 were related to behavioral interventions by eCoaching and the remaining 26 were related to human coaching. The most utilized persuasive eCoaching methods were personalization (n=19), interaction and cocreation (n=17), technology adoption for behavior change (n= 17), goal setting and evaluation (n=16), persuasion (n=15), automation (n=14), and lifestyle change (n=14). The most relevant methods for human coaching were behavior (n=23), methodology (n=10), psychology (n=9), and mentoring (n=6). Here, "n" signifies the total number of articles where the respective method was identified. In this study, we focused on different coaching methods to understand the psychology, behavioral science, coaching philosophy, and essential coaching processes for effective coaching. We have discussed how we can integrate the obtained knowledge into the eCoaching process for healthy lifestyle management using ICT. We identified that knowledge, coaching skills, observation, interaction, ethics, trust, efficacy study, coaching experience, pragmatism, intervention, goal setting, and evaluation of coaching processes are relevant for eCoaching. CONCLUSIONS This systematic literature review selected processes, associated methods, strengths, and limitations for behavioral interventions from established coaching models. The identified methods of coaching point toward integrating human psychology in eCoaching to develop effective intervention plans for healthy lifestyle management and overcome the existing limitations of human coaching.
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Affiliation(s)
- Ayan Chatterjee
- Department for Information and Communication Technologies, Centre for e-Health, University of Agder, Grimstad, Norway
| | - Martin Gerdes
- Department for Information and Communication Technologies, Centre for e-Health, University of Agder, Grimstad, Norway
| | - Andreas Prinz
- Department for Information and Communication Technologies, Centre for e-Health, University of Agder, Grimstad, Norway
| | - Santiago Martinez
- Department of Health and Nursing Science, Centre for e-Health, University of Agder, Grimstad, Norway
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Janssen M, Goudsmit J, Lauwerijssen C, Brombacher A, Lallemand C, Vos S. How Do Runners Experience Personalization of Their Training Scheme: The Inspirun E-Coach? SENSORS 2020; 20:s20164590. [PMID: 32824253 PMCID: PMC7472115 DOI: 10.3390/s20164590] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/11/2020] [Accepted: 08/13/2020] [Indexed: 11/16/2022]
Abstract
Among runners, there is a high drop-out rate due to injuries and loss of motivation. These runners often lack personalized guidance and support. While there is much potential for sports apps to act as (e-)coaches to help these runners to avoid injuries, set goals, and maintain good intentions, most available running apps primarily focus on persuasive design features like monitoring, they offer few or no features that support personalized guidance (e.g., personalized training schemes). Therefore, we give a detailed description of the working mechanism of Inspirun e-Coach app and on how this app uses a personalized coaching approach with automatic adaptation of training schemes based on biofeedback and GPS-data. We also share insights into how end-users experience this working mechanism. The primary conclusion of this study is that the working mechanism (if provided with accurate data) automatically adapts training sessions to the runners' physical workload and stimulates runners' goal perception, motivation, and experienced personalization. With this mechanism, we attempted to make optimal use of the potential of wearable technology to support the large group of novice or less experienced runners and that by providing insight in our working mechanisms, it can be applied in other technologies, wearables, and types of sports.
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Affiliation(s)
- Mark Janssen
- School of Sport Studies, Fontys University of Applied Science, 5644 HZ Eindhoven, The Netherlands; (J.G.); (S.V.)
- Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.L.); (A.B.)
- Correspondence:
| | - Jos Goudsmit
- School of Sport Studies, Fontys University of Applied Science, 5644 HZ Eindhoven, The Netherlands; (J.G.); (S.V.)
- Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.L.); (A.B.)
| | | | - Aarnout Brombacher
- Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.L.); (A.B.)
| | - Carine Lallemand
- Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.L.); (A.B.)
- HCI Research Group, Department of Behavioural and Cognitive Sciences, University of Luxembourg, 4366 Luxembourg, Luxembourg
| | - Steven Vos
- School of Sport Studies, Fontys University of Applied Science, 5644 HZ Eindhoven, The Netherlands; (J.G.); (S.V.)
- Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands; (C.L.); (A.B.)
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Understanding Different Types of Recreational Runners and How They Use Running-Related Technology. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17072276. [PMID: 32230999 PMCID: PMC7177805 DOI: 10.3390/ijerph17072276] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 03/26/2020] [Accepted: 03/27/2020] [Indexed: 11/22/2022]
Abstract
This study aims to help professionals in the field of running and running-related technology (i.e., sports watches and smartphone applications) to address the needs of runners. It investigates the various runner types—in terms of their attitudes, interests, and opinions (AIOs) with regard to running—and studies how they differ in the technology they use. Data used in this study were drawn from the standardized online Eindhoven Running Survey 2016 (ERS2016). In total, 3723 participants completed the questionnaire. Principal component analysis and cluster analysis were used to identify the different running types, and crosstabs obtained insights into the use of technology between different typologies. Based on the AIOs, four distinct runner types were identified: casual individual, social competitive, individual competitive, and devoted runners. Subsequently, we related the types to their use of sports watches and apps. Our results show a difference in the kinds of technology used by different runner types. Differentiation between types of runners can be useful for health professionals, policymakers involved in public health, engineers, and trainers or coaches to adapt their services to specific segments, in order to make use of the full potential of running-related systems to support runners to stay active and injury-free and contribute to a healthy lifestyle.
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Van Hooren B, Goudsmit J, Restrepo J, Vos S. Real-time feedback by wearables in running: Current approaches, challenges and suggestions for improvements. J Sports Sci 2019; 38:214-230. [PMID: 31795815 DOI: 10.1080/02640414.2019.1690960] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Injuries and lack of motivation are common reasons for discontinuation of running. Real-time feedback from wearables can reduce discontinuation by reducing injury risk and improving performance and motivation. There are however several limitations and challenges with current real-time feedback approaches. We discuss these limitations and challenges and provide a framework to optimise real-time feedback for reducing injury risk and improving performance and motivation. We first discuss the reasons why individuals run and propose that feedback targeted to these reasons can improve motivation and compliance. Secondly, we review the association of running technique and running workload with injuries and performance and we elaborate how real-time feedback on running technique and workload can be applied to reduce injury risk and improve performance and motivation. We also review different feedback modalities and motor learning feedback strategies and their application to real-time feedback. Briefly, the most effective feedback modality and frequency differ between variables and individuals, but a combination of modalities and mixture of real-time and delayed feedback is most effective. Moreover, feedback promoting perceived competence, autonomy and an external focus can improve motivation, learning and performance. Although the focus is on wearables, the challenges and practical applications are also relevant for laboratory-based gait retraining.
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Affiliation(s)
- Bas Van Hooren
- School of Sport Studies, Fontys University of Applied Sciences, Eindhoven, The Netherlands.,Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jos Goudsmit
- School of Sport Studies, Fontys University of Applied Sciences, Eindhoven, The Netherlands.,Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Juan Restrepo
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Steven Vos
- School of Sport Studies, Fontys University of Applied Sciences, Eindhoven, The Netherlands.,Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
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Banos O, Hermens H, Nugent C, Pomares H. Smart Sensing Technologies for Personalised e-Coaching. SENSORS 2018; 18:s18061751. [PMID: 29844292 PMCID: PMC6021907 DOI: 10.3390/s18061751] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 05/28/2018] [Indexed: 11/16/2022]
Abstract
People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help coach people to have healthier behaviors. The increasing accountability associated with app- and device-based behavior tracking not only provides timely and personalized information and support, but also gives us an incentive to set goals and do more. This paper outlines some of the recent efforts made towards automatic and autonomous identification and coaching of troublesome behaviors to procure lasting, beneficial behavioral changes.
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Affiliation(s)
- Oresti Banos
- Biomedical Signals and Systems Group, University of Twente, 7522 NB Enschede, The Netherlands.
- CITIC-UGR, University of Granada, E-18015 Granada, Spain.
| | - Hermie Hermens
- Biomedical Signals and Systems Group, University of Twente, 7522 NB Enschede, The Netherlands.
- Telemedicine Group, Roessingh Research and Development, 7500 AH Enschede, The Netherlands.
| | - Christopher Nugent
- Smart Environments Research Group, Ulster University, Newtownabbey BT37 0QB, UK.
| | - Hector Pomares
- CITIC-UGR, University of Granada, E-18015 Granada, Spain.
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