Digitalization has become and continues to be a very important aspect in all realms of our lives (1). Rapidly developing new technologies are constantly implemented by lay persons and health care personnel across the health sciences (2,3). We are currently witnessing a digital transformation and progressing coalescence of our daily life and health technologies by the use of various digital features that are carried into medical application (e.g., mobile applications, exergaming (4,5)).
Medicine throughout the years has seen major advances in the fields of surgery, pharmacology, radiology, genetics, or disease prevention (6). The main impact of the 21st century will lie heavily on the influences of digital innovations (2). Some of these innovations will have minimal impact while others may potentially change the existing structures and norms, so much so that they may be termed “disruptive technologies” (7). Health care continues to change and the pace in the near future may be the greatest one has ever seen. The amount and fidelity of data available to base decisions on will change the interactions between physicians and patients (8,9). Sports medicine, like other areas of health care, is interdisciplinary and international, and digitalization can be a way to improve the collaboration and the health of individual patients or a population (10). With its potential in prevention, therapy, and rehabilitation of various illnesses, it can have a substantial socioeconomic impact, especially when the demographic changes in many countries worldwide are taken into consideration (11).
Due to the vast nature of the digital landscape, this review will just provide a general overview in the area of sports medicine. We will not just focus on diagnosis, but on broader areas of sports medicine and health promotion and give single practical examples of digital applications' use in the literature.
Mobile Applications in Exercise Health and Sport Medicine
The use of mobile applications (apps) in medicine and health-related contexts is a booming market with great potential to improve health care (12,13). There is an ever-increasing number of apps for the use in sports and fitness (14), which are marketed to a diverse audience. The apps provide information for those who are health conscious (14) or to people who are more serious about their training (15). Aside from simple data tracking, many of the apps try to provide solutions that can be used to exert a beneficial influence for their users by promoting behavioral changes (16) and improving health consciousness concerning healthy eating and physical activities (17). Others touch upon areas, such as sleep monitoring (18) or include functionalities for social interaction; for example, by sharing training data or allowing competition to improve motivation (14,19). Nutritional coaching, as well as advice for necessary adaptations to food habits, can be included (17), meanwhile another popular feature encourages exercise via digital games known as “exergaming” (20,21). Other apps are even used to support medical rehabilitation programs (22).
Despite all enthusiasm, there is little overall scientific evidence, either for content and functionalities or for the long-term health benefits of the various apps offered (23,24). The number of apps for exercise health and sports medicine is quite difficult to quantify, partially due to how they are presented. In the multiple app stores available, there are categories for a lot of “sport-related” applications (e.g., in August 2018, ca. 70,000 apps in the U.S. Apple store (25), and ca. 53,000 apps in Google's Play Store (26)), but many apps also may be listed in the “Medicine” or “Health & Fitness” categories, which may even result in an overlap, making a selection for athletes or doctors difficult.
Even though both the medical community and end users are in need of high-quality apps (27), products' safety and efficacy, ideally proven by scientific evidence, cannot be taken for granted (24). To help this issue, apps serving a diagnostic or therapeutic purpose have to follow defined regulations (e.g., ”CE certification “in the European Union, FDA-approval in the United States). For products outside of this scope, quality seals or standardized rating processes may be applied (28) to help users to adequately assess the offerings. However, considering apps, there are examples that even well-designed approaches have failed to represent actual quality (29). Apps referencing either CE certification or quality seals in their descriptions are still few and far between within app stores (27). Facing the number of apps available, there may be a supportive role, for example, for medical associations by defining basic quality criteria (30) and clarifying the conditions under which the use of certain apps may be deemed appropriate by the respective field.
Wearables, Smart Devices, and Intelligent Machines
Wearables are highly integrated with compatible mobile applications with which they interface, making a delineation between the wearable and the smart devices hard to discern. The economics of wearables is undeniable with an estimated global market revenue of sports, fitness, and activity monitor devices running as high as 2.62 billion dollars (33). Besides mere fitness tracking for the training use of lay athletes, they also are getting increasingly important in exercise medicine. Sensor driven training will become a bigger interest for preventative or medical training, when the localization or speed tracking can be connected to, for example, the heart rate to assess demands of training and performance and protect athletes from overtraining (34,35). In team sports, the ability to evaluate parameters, such as accelerations or decelerations of players during attack or defense maneuvers, may be used for optimizing training programs (36).
Integrating digital sensors into clothes can help monitor the wearer's data for signs of fatigue or overexertion and possibly issue warnings when appropriate (34,35,37). So much so that smart outdoor shirt sensors have been described to be able to detect arrhythmias during daily sport exercises or rehabilitation (38). For contact sports, there also are applications and sensors that can be used by those supervising sports activities, for example, coaches or medical personnel, or even the athletes themselves, to aid them in assessing the extent of sports injuries (39). In the future, these technologies might be combined with innovations like intelligent helmets which can protect users' heads, for example, by inflatable airbags (40).
Other smart devices might be bigger, but can still promise great advances especially in the field of rehabilitation. For example, exoskeletons can be used for patients with spinal cord injuries after accidents. The upright position and walking can not only stimulate muscles and tissues but also can improve patients' suspected quality of life, leading to more motivation and participation in society (41). Other machines like antigravity treadmills can simulate different stages of weight bearing after orthopedic trauma and operations (42). More complex systems also can help physicians choose individualized training programs for patients' rehabilitation according to their premeasured strength (43). Altogether, it can be expected that future advances in wearables and machines will lie in data analyses and artificial intelligence.
Current treatment paths in sports medicine still largely depend on doctors' visits and decisions. While the human contact itself is important, the mode of when and where to contact a physician may be altered. The utility of telemedicine compared with clinic-based doctors' visits have been shown, for example, for cardiovascular consultations (45). From a patient perspective, telemedicine could achieve high levels of satisfaction while reducing visiting and waiting times as well as health care costs (46). In most cases, physicians offer digital consultation on their own, but there also are examples of specialized companies offering doctors' consultations (47). Telemedicine can play a variety of roles in sports medicine improving access to and quality of care (48). A survey revealed 8.6 million sports- and recreation-related injury episodes for the United States from 2011 to 2014 with about 50% of the patients being treated outside of emergency departments or without hospitalization (49). Regarding other data from England, up to 67% of sport-related emergency department visits were rather minor injuries (50), telemedicine might help to reasonably triage patients with sports-related injuries between visits of emergency departments, orthopedics, sport physicians, general practitioners, or maybe even address some minor cases at first glance. Telemedicine also might be useful for a primary assessment of injuries in amateur team games where, in contrast to high-level games, team-physicians are rarely onsite (51).
Another major area of telemedicine can be a digital company of athletes all around the world. Similar to high professional athletes or sport teams who have their own physicians in competition with them, telemedicine also can enable lay athletes to have their own familiar doctor online with them — especially interesting for athletes with a history of diseases (52). Additionally, improving the contact between sports medicine providers, specialist physicians, primary care providers, and other allied health professionals could lead to better care through the faster exchange of knowledge and opinions for the sake of the athlete (53).
Beyond injury-related problems, athletes and patients also often seek doctors' advice for consultation about healthy nutrition, training programs, preventional behavior, as well as lifestyle adaptions that can be easily transferred into the digital space than, for example, contacts needing a physical orthopedic examination (54).
Although digital physician-patient contacts are growing in popularity (55), the advantages of a direct visit with a thorough physical examination are not yet replaceable by digital means.
Social Media and Social Networks
Various sports, like yoga, climbing, or parkour, partially owe their popularity to massive media presence, especially in social networks. This creates the opportunity for sports-specific medical content to be broadcasted to millions of athletes (56,57). More and more, social media continues to be used to gain information from users; and networks, such as Facebook or Instagram, are present around the world (58).
Besides multiple opportunities, this unlimited flood of information reveals a significant level of potential risk as data on social media is uncontrolled and barely ever based on evidence. When focusing on user behavior on social media and the effects on medical information retrieval, it can be shown that a) athletes use social media in large numbers; b) studying medical information on social media usage continues to gain in importance; and c) almost 80% of athletes consume medical information, such as injury prevention techniques on social media (59–61). From a socioeconomical point of view, social media has become a platform of unlimited range, with an easy accessibility to everyone. The use of social media for communications with the interested public (62,63) by sport medicine associations or journals should be encouraged.
Some authors report that the use of social media can be used to provide health care interventions (64). At the same time, a huge stage for uncontrolled, dangerous, or incorrect medical content is available on social media (9,65,66). Data on cost-benefit factors of medical content consumption in social media is pending. The expansion of social media and the inclusion in an athlete's daily life will have an increasing influence on sport medical care and supervision (59,61,67).
Consequently, doctors, clinics, patients, and the health industry itself would be well advised to acknowledge both difficulties and chances when communicating via social media and work to shape a modern medical information exchange platform.
Augmented Reality, Virtual Reality, and Exergaming
While most of the above-discussed digital tools have been utilized in varying degrees in clinical practice, other technologies still require more data to improve their value in the future of sports medicine. Augmented reality might have a relevant potential in this context. As an example, special applications for Microsoft's augmented and mixed reality device HoloLens can — combined with a personalized anatomical reconstruction of bony structures from medical imaging — be used for biomechanical assessments like the range of movement or pathologic gait patterns and can support diagnostic processes (69).
Also, original gaming tools like the Kinect camera system have been tested for measuring the range of movement of a patient as an alternative to a goniometer (70). Motion cameras could help doctors or physiotherapists identify deficits in movement and address them specifically by individual digital training programs (71).
Video games and other digital reality systems may encourage children to develop and maintain a good grade in physical activity through things like gamification and exergaming (72). In terms of disease prevention, there are positive reports about using video games with movement components as training methods for obese children (73). However, it also has to be considered that such approaches would further profit from being embedded into organized programs with an additional social support for lifestyle changes not only for the children but also their families (74,75).
Virtual reality (VR) approaches also may be an important means of motivating people in terms of sports, training, and rehabilitation. The VR application has been described as part of a therapeutic program for the rehabilitation of neurological injuries, adaptable to the patient’s needs (76,77). In the future, educational approaches in medicine, physiotherapy, and sport sciences also may be an interesting option for VR, like the use of VR for improving surgical skills (78).
However, while various gaming tools like Playstation, Wii, or Xbox Kinect have been presented for their potential use in rehabilitation settings, their efficacy seems to depend highly on individual study-specific factors like setting, patients' cohort, or addressed pathologies (79). Hence, before recommending the use of such gaming tools for a general application in certain rehabilitation settings — also with potential impact, for example, on reimbursements by health insurances — more long-term results from large randomized controlled trials are still missing (80).
Big Data, Artificial Intelligence, System Interoperability
The term “big data” can somehow be regarded as a melting pot of all data generated by mobile apps, machines, wearables, or a combination thereof (83). The field of fitness, exercise, and sports medicine is one of the largest producers of health-related data worldwide. In soccer, these data are reported to support tailoring athlete-specific training programs, for example, by considering their moving behavior and vital signs and thus giving information or even advices to physiotherapists or sport physicians on how to adapt training or exercise (84). In this context, system interoperability will be one of the decisive new approaches in the future for the collection and analysis of data from apps, wearables, machines, diagnoses, therapies, and their outcomes.
To improve big data's utility, artificial intelligence (AI) solutions could enhance the process of data analysis and can thus be integrated for preventive measures, diagnosis, or even therapy recommendations (85). Initial studies have, for example, already shown that AI-driven systems might exceed the accuracy of cardiovascular risk prediction by “classical” medical society guidelines (86). Digital personal trainers, who do not only show measured parameters but also provide advice for progress or preventive measurements, will be able to help create individualized training plans (87), by taking into account day-depending changes in performance. On the other hand, AI applications might help reduce, or at least channelize, the number of doctor or emergency department visits by providing reliable, quality based diagnosis and recommendations for further questions in the context of fitness, health as per exercise, or minor sport injuries (88). One day, such tools may work as digital medical assistants, that by integrating existing illnesses and medication, as well as the ability to analyze symptoms, advise their users to change their sport behavior, up to even recommendations to see a doctor immediately. However, using random existing big amounts of data in the future will not be the only solution to establish recommendations for training or therapies. It will still be important to perform large scaled multicenter randomized controlled trials (RCT) (89). In such RCT, digital features, like mobile apps, might also be integrated as part of prospective studies, as the “back on track” study that uses an app to gain data so as to better understand the decision making in patients with acute anterior cruciate ligament ruptures (22).
More research on this topic is still necessary to gain more evidence for the best possibilities to use increasingly intelligent and interconnected systems.
Prospects and Conclusions
The focus of this article was to provide a mere overview of the vast field of digitalization in sport medicine. Due to the high variety of features and the complexity of this highly interdisciplinary specialty, systematic reviews on the individual subthemes of this publication will be necessary for thorough insights. The fields mentioned in this article will continue to further develop with new tools and features, which will enhance their efficacy. It will be highly important that doctors and other health care providers in sport, exercise, prevention, and rehabilitative medicine will be aware of this development and actively participate in it in the future.
Here, academic education also will be relevant to confront today's students early with the digital options of today and tomorrow and to provide them with necessary competencies in digitalization (92). Competent doctors in this field are important, knowing which digital features might be recommendable for athletes or patients, and how to use them in terms of diagnostics, prevention, or therapies.
Beyond this article, there are various other digital technologies, which are just emerging, but are not yet assessable for their importance for exercise-related health, like the field of genomics, which might provide new information about athletes' specific nutritional demands (93).
However, not only genetic analyses, but all data-related features are and should be under strict national and international surveillance of legal, ethical, and political guidelines and regulations to protect — despite all digital enthusiasm — the rights and data of the individuum according to existing laws (94). Here, data leaks or hacking attacks on companies or health institutions show again and again the weaknesses of present digital defense structures (95).
While smart technologies have become an integral part of life for many, there are hints that access and use may be limited due to cultural or educational related aspects — leading to a new digital social divide. As an example, a recent study on the use of self-tracking and fitness mobile applications suggested that sufficient technological capabilities, sufficient familiarity with the technology, and adequate levels of health education contributed to higher usage rates, while poorer participants reported a lack of technical skills, contributing to lower usage rates (96).
An important aspect also will be to find a balance between innovation and establishing long-termed evidence for digital features. As already postulated for terms of medical education, following every new hype might be less advantageous for many situations then to establish working diagnostics or therapy concepts (97). The use and also the possible financial reimbursement and cost-effectiveness of many new ideas for larger populations or even societies will have to be proven. The adaptation of laws to allow doctors, for example, to prescribe certain tools or exercises might be a consequent step. However, certification structures of digital tools have to, therefore, be established and clear criteria needs to be applied.
Digital innovations will change many fields of sport medicine in the future. The challenge will be to integrate these intelligently and wisely into the daily work of physicians, physiotherapists, and their athletes and patients.
The authors would like to thank Mr. Henry Charles Scheuermann and Mrs. Dawn C. Domaschk for native proofreading of the manuscript.
The authors declare no conflict of interest and do not have any financial disclosures.
1. Manyika J, Ramaswamy S, Khanna S, et al. Digital America: A tale of the haves and have-mores. McKinsey Global Institute [Internet]. 2015 [cited 2018 Nov 3]. Available from: https://www.mckinsey.com/industries/high-tech/our-insights
2. Müschenich M, Wamprecht L. Health 4.0 — how are we doing tomorrow? Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
. 2018; 61:334–9.
3. Wolf B, Scholze C. Medicine 4.0, the role of electronics, information technology and microsystems in modern medicine. Curr. Directions Biomedl Engineering
. 2017; 3:183–6.
4. Gabbiadini A, Greitemeyer T. Fitness mobile apps positively affect attitudes, perceived behavioral control and physical activities. J. Sports Med. Phys. Fitness
. [Internet]. 2018. Available from: https://www.minervamedica.it/en/journals/sports-med-physical-fitness/article.php?cod=R40Y9999N00A18040403
. doi: 10.23736/ S0022–4707.18.08260–9.
5. Tahmosybayat R, Baker K, Godfrey A, et al. Movements of older adults during exergaming interventions that are associated with the systems framework for postural control: a systematic review. Maturitas
. 2018; 111:90–9.
6. Parker S. Medical Advances (20th Century Inventions)
. Chicago (IL): Heinemann/Raintree; 1998.
7. Mesko B, Drobni Z, Benyei E, et al. Digital health is a cultural transformation of traditional healthcare. Mhealth
[Internet]. 2017 [cited 2018 Oct 28];3:38. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5682364
. doi: 10.21037/mhealth.2017.08.07.
8. Lupton D. The digitally engaged patient: self-monitoring and self-care in the digital health era. Soc. Theory Health
. 2013; 11:256–70.
9. Sillence E, Briggs P, Harris PR, Fishwick L. How do patients evaluate and make use of online health information? Soc. Sci. Med
. 2007; 64:1853–62.
10. Frontera WR, Micheli LJ, Herring SA, Silver JK. Clinical Sports Medicine: Medical Management and Rehabilitation
. Philadelphia (PA): Elsevier Inc.; 2007.
11. Saner H, van der Velde E. eHealth in cardiovascular medicine: a clinical update. Eur. J. Prev. Cardiol
. 2016; 23(Suppl. 2):5–12.
12. Projected global mHealth market size 2012–2020 [Internet]. Hamburg (Germany): Statista; [cited 2018 Aug 16]. Available from: https://www.statista.com/statistics/295771/mhealth-global-market-size
13. Global sports, fitness & activity monitor market revenue 2013-2019 [Internet]. Hamburg (Germany): Statista; [cited 2018 Aug 16]. Avalaible from: https://www.statista.com/statistics/302572/fitness-sports-and-activity-monitor-market-revenue-worldwide/2018
14. Higgins JP. Smartphone applications for patients' health and fitness. Am. J. Med
. 2016; 129:11–9.
15. Machado GC, Pinheiro MB, Lee H, et al. Smartphone apps for the self-management of low back pain: a systematic review. Best Pract. Res. Clin. Rheumatol
. 2016; 30:1098–109.
16. Duncan MJ, Vandelanotte C, Trost SG, et al. Balanced: a randomised trial examining the efficacy of two self-monitoring methods for an app-based multi-behaviour intervention to improve physical activity, sitting and sleep in adults. BMC Public Health
. 2016; 16:670.
17. Wang Q, Egelandsdal B, Amdam GV, et al. Diet and physical activity apps: perceived effectiveness by app users. JMIR Mhealth Uhealth
. 2016; 4:e33.
18. Ong AA, Gillespie MB. Overview of smartphone applications for sleep analysis. World J. Otorhinolaryngol Head Neck Surg
. 2016; 2:45–9.
19. Chen J, Bauman A, Allman-Farinelli M. A study to determine the most popular lifestyle smartphone applications and willingness of the public to share their personal data for health research. Telemed. J. E Health
. 2016; 22:655–65.
20. Kamboj AK, Krishna SG. Pokémon GO: an innovative smartphone gaming application with health benefits. Prim. Care Diabetes
. 2017; 11:397–9.
21. Cowdery J, Majeske P, Frank R, Brown D. Exergame apps and physical activity: the results of the ZOMBIE trial. Am. J. Health Educ
. 2015; 46:216–22.
22. Zens M, Woias P, Suedkamp NP, Niemeyer P. “Back on Track”: a mobile app observational study using Apple's ResearchKit Framework. JMIR Mhealth Uhealth
. 2017; 5:e23.
23. Modave F, Bian J, Leavitt T, et al. Low quality of free coaching apps with respect to the American College of Sports Medicine Guidelines: a review of current mobile apps. JMIR Mhealth Uhealth
. 2015; 3:e77.
24. van Mechelen DM, van Mechelen W, Verhagen EA. Sports injury prevention in your pocket?! Prevention apps assessed against the available scientific evidence: a review. Br. J. Sports Med
. 2014; 48:878–82.
25. App Store Metrics. PocketGamer.biz
. [Internet]. Bath (UK): PocketGamer.biz; [cited 2018 Dec 10]. Available from: https://www.pocketgamer.biz/metrics/app-store/categories
26. Most popular Google Play categories. AppBrain. [Internet]. Zurich (Switzerland): AppBrain; [cited 2018 Dec 10]. Available from: https://www.appbrain.com/stats/android-market-app-categories
27. Albrecht UV, Hillebrand U, von Jan U. Relevance of trust marks and CE labels in German-language store descriptions of health apps: analysis. JMIR Mhealth Uhealth
. 2018; 6:e10394.
28. Boulos MN, Brewer AC, Karimkhani C, et al. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform
. 2014; 5:229.
29. Dolan B. Happtique suspends mobile health app certification program. MobiHealthNews Web site [Internet]. Portland (ME): MobiHealthNews; 2013 [cited 2018 Dec 9]. Available from: https://www.mobihealthnews.com/28165/happtique-suspends-mobile-health-app-certification-program
30. Albrecht UV. Gesundheits-Apps: Fachübergreifende Qualitätskriterien sind unabdingbar. Dtsch Arztebl
. 2018; 115: A – 67/B – 1/C – 1.
31. Cobbs L, Hasanaj L, Amorapanth P, et al. Mobile universal lexicon evaluation system (MULES) test: a new measure of rapid picture naming for concussion. J. Neurol. Sci
. 2017; 372:393–8.
32. Clugston JR, Chrisman SPD, Houck ZM, et al. King-Devick Test time varies by testing modality. Clin. J. Sport Med
. 2018 [cited 2018 Aug 12]. Available from: https://insights.ovid.com/crossref?an=00042752-900000000-99111
. doi: 10.1097/JSM.0000000000000691.
33. Global forecast of sports, fitness & activity monitor market revenue from 2013 to 2019 [Internet]. Hamburg (Germany): Statista; [cited 2018 Nov 16]. Avalaible from: https://www.statista.com/statistics/302572/fitness-sports-and-activity-monitor-market-revenue-worldwide/2018
34. Dellaserra CL, Gao Y, Ransdell L. Use of integrated technology in team sports: a review of opportunities, challenges, and future directions for athletes. J. Strength Cond. Res
. 2014; 28:556–73.
35. Seshadri DR, Drummond C, Craker J, et al. Wearable devices for sports: new integrated technologies allow coaches, physicians, and trainers to better understand the physical demands of athletes in real time. IEEE Pulse
. 2017; 8:38–43.
36. Read DB, Jones B, Williams S, et al. The physical characteristics of specific phases of play during rugby union match play. Int. J. Sports Physiol. Perform
. 2018; 1–21.
37. Elliot CA, Hamlin MJ, Lizamore CA. Validity and reliability of the Hexoskin(R) wearable biometric vest during maximal aerobic power testing in elite cyclists. J. Strength. Cond. Res. [Internet]
. 2017 [cited 2018 Sep 10]. Available from: https://insights.ovid.com/crossref?an=00124278-900000000-95836
. doi: 10.1519/ JSC.0000000000002005.
38. Park JA, Han HJ, Heo JC, Lee JH. Computer aided diagnosis sensor integrated outdoor shirts for real time heart disease monitoring. Comput. Assist. Surg. (Abingdon)
. 2017; 22(sup1):176–85.
39. O'Connor KL, Rowson S, Duma SM, Broglio SP. Head-impact-measurement devices: a systematic review. J. Athl. Train
. 2017; 52:206–27.
40. Kurt M, Laksari K, Kuo C, et al. Modeling and optimization of airbag helmets for preventing head injuries in bicycling. Ann. Biomed. Eng
. 2017; 45:1148–60.
41. Cahill A, Ginley OM, Bertrand C, Lennon O. Gym-based exoskeleton walking: a preliminary exploration of non-ambulatory end-user perspectives. Disabil. Health J
. 2018; 11:478–85.
42. McNeill DK, de Heer HD, Bounds RG, Coast JR. Accuracy of unloading with the anti-gravity treadmill. J. Strength Cond. Res
. 2015; 29:863–8.
43. Torpel A, Becker T, Thiers A, et al. Inter-session reliability of isokinetic strength testing in knee and elbow extension and flexion using the BTE PrimusRS. J. Sport Rehabil
. 2017; 26.
44. Hochsmann C, Knaier R, Eymann J, et al. Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions. Scand. J. Med. Sci. Sports
. 2018; 28:1818–27.
45. Rawstorn JC, Gant N, Direito A, et al. Telehealth exercise-based cardiac rehabilitation: a systematic review and meta-analysis. Heart
. 2016; 102:1183–92.
46. Atanda A Jr, Pelton M, Fabricant PD, et al. Telemedicine utilisation in a paediatric sports medicine practice: decreased cost and wait times with increased satisfaction. J. ISAKOS
. 2018; 3:94–7.
47. Hosperity Web site [Internet]. Kansas City (MO): Hosperity Care; [cited 2018 Dec 5]. Available from: https://hosperity.com
48. Tenforde AS, Hefner JE, Kodish-Wachs JE, et al. Telehealth in physical medicine and rehabilitation: a narrative review. PM R
. 2017; 9(5S):S51–8.
49. Sheu Y, Chen LH, Hedegaard H. Sports- and recreation-related injury episodes in the United States, 2011–2014. Natl. Health Stat. Rep
50. Boyce SH, Quigley MA. Review of sports injuries presenting to an accident and emergency department. Emerg. Med. J
. 2004; 21:704–6.
51. Vargas BB, Shepard M, Hentz JG, et al. Feasibility and accuracy of teleconcussion for acute evaluation of suspected concussion. Neurology
. 2017; 88:1580–3.
52. Hwang R, Mandrusiak A, Morris NR, et al. Assessing functional exercise capacity using telehealth: is it valid and reliable in patients with chronic heart failure? J. Telemed. Telecare
. 2017; 23:225–32.
53. Gitlin-Nitti YJ, Shah CD, Kharlamb V. A physical therapist's role in clinical video telehealth. Fed Pract
. 2015; 32:40–1.
54. Alencar MK, Johnson K, Mullur R, et al. The efficacy of a telemedicine-based weight loss program with video conference health coaching support. J. Telemed. Telecare
. 2019; 25:151–7.
55. Tates K, Antheunis ML, Kanters S, et al. The effect of screen-to-screen versus face-to-face consultation on doctor-patient communication: an experimental study with simulated patients. J. Med. Internet Res
. 2017; 19:e421.
56. Filo K, Lock D, Karg A. Sport and social media research: a review. Sport Management Review
. 2015; 18:166–81.
57. Pedersen PM. A commentary on social media research from the perspective of a sport communication journal editor. Commun. Sport
. 2014; 2:138–42.
58. Most popular social networks worldwide as of April 2018, ranked by number of active users (in millions) [Internet]. Hamburg (Germany): Statista; [cited 2018 Nov 14]. Avalaible from: https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users
59. Campbell L, Evans Y, Pumper M, Moreno MA. Social media use by physicians: a qualitative study of the new frontier of medicine. BMC Med. Inform. Decis. Mak
. 2016; 16:91.
60. Grajales FJ 3rd, Sheps S, Ho K, et al. Social media: a review and tutorial of applications in medicine and health care. J. Med. Internet Res
. 2014; 16:e13.
61. Lutter C. Generation "Social Media" — Use of modern media to gain information on sports injuries using the example of climbing
. Nuremberg: Friedrich-Alexander University Erlangen-Nuremberg; 2017.
62. British Journal of Sports Medicine Web site [Internet]. London (UK). Br. J. Sports Med
. [cited 2018 Sep 9]. Available from: https://bjsm.bmj.com
63. American College of Sports Medicine Web site [Internet]. Indianapolis (IN): American College of Sports Medicine; [cited 2018 Sep 9]. Available from: https://www.acsm.org
64. Ahmed OH, Sullivan SJ, Schneiders AG, et al. Ethical considerations in using Facebook for health care support: a case study using concussion management. PM R
. 2013; 5:328–34.
65. Moorhead SA, Hazlett DE, Harrison L, et al. A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. J. Med. Internet Res
. 2013; 15:e85.
66. Pentescu A, Cetină I, Orzan G. Social media's impact on healthcare services. Procedia Economics and Finance
. 2015; 27:646–51.
67. Alsobayel H. Use of social media for professional development by health care professionals: a cross-sectional web-based survey. JMIR Med Educ
. 2016; 2:e15.
68. Ramkumar PN, Navarro SM, Cornaghie MM, et al. Social media in shoulder & elbow surgery: an analysis of twitter and Instagram. Int. J. Sports Med
. 2018; 39:564–70.
69. Galvan Debarba H, Elias des Oliveira M, Lädermann A, Chagué S, Charbonier C. Augmented reality visualization of joint movements for physical examination and rehabilitation. IEEE Conference on Virtual Reality and 3D User Interfaces (VR) [Internet]. 2018 [cited 2018 Aug 30]; Available from: https://www.computer.org/csdl/proceedings/vr/2018/3365/00/08446368-abs.html
70. Lee SH, Yoon C, Chung SG, et al. Measurement of shoulder range of motion in patients with adhesive capsulitis using a kinect. PLoS One
. 2015; 10:e0129398.
71. Sugarman H, Weisel-Eichler A, Burstin A. Use of novel virtual reality system for the assessment and treatment of unilateral spatial neglect: a feasibility study. International Conference on Virtual Rehabilitation IEEE [Internet]. 2011 [cited 2018 Aug 30]; Available from: https://ieeexplore.ieee.org/document/5971859
. doi: 10.1109/ICVR.2011.5971859.
72. Lau PW, Liang Y, Lau EY, et al. Evaluating physical and perceptual responses to exergames in Chinese children. Int. J. Environ. Res. Public Health
. 2015; 12:4018–30.
73. Christison A, Khan HA. Exergaming for health: a community-based pediatric weight management program using active video gaming. Clin. Pediatr. (Phila)
. 2012; 51:382–8.
74. Staiano AE, Beyl RA, Guan W, et al. Home-based exergaming among children with overweight and obesity: a randomized clinical trial. Pediatr. Obes
. 2018; 13:724–33.
75. Van Grouw JM, Volpe SL. Childhood obesity in America. Curr. Opin. Endocrinol. Diabetes Obes
. 2013; 20:396–400.
76. Perez-Marcos D, Chevalley O, Schmidlin T, et al. Increasing upper limb training intensity in chronic stroke using embodied virtual reality: a pilot study. J. Neuroeng. Rehabil
. 2017; 14:119.
77. Levac D, Glegg SM, Sveistrup H, et al. A knowledge translation intervention to enhance clinical application of a virtual reality system in stroke rehabilitation. BMC Health Serv. Res
. 2016; 16:557.
78. Samadbeik M, Yaaghobi D, Bastani P, et al. The applications of virtual reality technology in medical groups teaching. J. Adv. Med. Educ. Prof
. 2018; 6:123–9.
79. Donath L, Rossler R, Faude O. Effects of virtual reality training (Exergaming) compared to alternative exercise training and passive control on standing balance and functional mobility in healthy community-dwelling seniors: a meta-analytical review. Sports Med
. 2016; 46:1293–309.
80. Jaarsma T, Klompstra L, Ben Gal T, et al. Increasing exercise capacity and quality of life of patients with heart failure through Wii gaming: the rationale, design and methodology of the HF-Wii study; a multicentre randomized controlled trial. Eur. J. Heart Fail
. 2015; 17:743–8.
81. Ku J, Kim YJ, Cho S, et al. Three-dimensional augmented reality system for balance and mobility rehabilitation in the elderly: a randomized controlled trial. Cyberpsychol. Behav. Soc. Netw
. 2019; 22:132–41.
82. Laver KE, Lange B, George S, et al. Virtual reality for stroke rehabilitation. Cochrane Database Syst. Rev
. 2017; 11:CD008349.
83. Tan SS, Gao G, Koch S. Big data and analytics in healthcare. Methods Inf. Med
. 2015; 54:546–7.
84. Rein R, Memmert D. Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. Springerplus
. 2016; 5:1410.
85. Neborachko M, Pkhakadze A, Vlasenko I. Current trends of digital solutions for diabetes management. Diabetes Metab. Syndr
. 2019; 13:2997–3003.
86. Weng SF, Reps J, Kai J, et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One
. 2017; 12:e0174944.
87. Huang CC, Liu HM, Huang CL. Intelligent scheduling of execution for customized physical fitness and healthcare system. Technol. Health Care
. 2015; 24(Suppl. 1):S385–92.
88. Ada Web site [Internet]. Berlin (Germany): Ada Health GmbH; [cited 2018 Nov 7]. Available from: https://ada.com
89. Niederer D, Vogt L, Wippert PM, et al. Medicine in spine exercise (MiSpEx) for nonspecific low back pain patients: study protocol for a multicentre, single-blind randomized controlled trial. Trials
. 2016; 17:507.
90. de Leeuw AW, Meerhoff LA, Knobbe A. Effects of pacing properties on performance in long-distance running. Big Data
. [Internet]. 2018 [cited 2019 Aug 13]. Available from: https://www.liebertpub.com/doi/full/10.1089/big.2018.0070?url_ver=Z39.88--2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed
. doi: 10.1089/big. 2018.0070.
91. Brodie MA, Pliner EM, Ho A, et al. Big data vs accurate data in health research: large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias. Med. Hypotheses
. 2018; 119:32–6.
92. Kuhn S, Frankenhauser S, Tolks D. Digital learning and teaching in medical education: already there or still at the beginning? Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
. 2018; 61:201–9.
93. Lifanov D, Khadyeva MN, Rahmatullina LSh, et al. Effect of creatine supplementation on physical performance are related to the AMPD1 and PPARG genes polymorphisms in football players. Ross. Fiziol. Zh. Im. I M Sechenova
. 2014; 100:767–76.
94. European Union Web site. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [Internet]. Brussels (Belgium): European Union; [cited 2018 Oct 11]. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32016R0679
95. Luna R, Rhine E, Myhra M, et al. Cyber threats to health information systems: a systematic review. Technol. Health Care
. 2016; 24:1–9.
96. Ridgers ND, Timperio A, Brown H, et al. A cluster-randomised controlled trial to promote physical activity in adolescents: the Raising Awareness of Physical Activity (RAW-PA) study. BMC Public Health
. 2017; 17:6.
97. Cook DA, Triola MM. What is the role of e-learning? Looking past the hype. Med. Educ
. 2014; 48:930–7.