About this Research Topic
The application of technology is designed to improve something, and to optimize and facilitate human work. Currently, new technologies are an essential piece in most professional sports; from those aimed at improving the performance of the athlete, to those designed to verify the result of the competition objectively. Technology is so established in professional sports, and has proven to have so many benefits, that it has crossed its borders and is also becoming established in amateur sports. Regardless of the sport discipline, we can take advantage of new technologies to improve many of the aspects that are too laborious without them. Sports and exercise medicine changed dramatically because of technological developments and data assessment methods, and future technological innovations will continue to transform sports and exercise medicine as we know it. For example, wearable devices allow the implementation of a large number of commercial and scientific solutions for, health and sports monitoring applications. These devices have been used in the areas of sports and health to monitor variables of load and physical work during exercise. They have contributed valuable knowledge by allowing us to collect data a non-invasive, remote, portable and safe way.
Despite the extensive use of new technologies in areas related to human movement, we are still lacking information in relation to data collection, mining, management, storage, analysis and reporting. Among other aspects to be considered, is the understanding of sample rates, chip sets, filtering methods, and data processing algorithms Also, the specific sample rate, chipsets, filtering methods and merging of devices data based on the principle of redundancy need to be more clearly understood. For example, it should be taken into account that each device manufacturer may apply some filtration processes before the “raw data” is available for users, and these filtration stages and filters could differ between companies. Also, the interaction between internal (metabolic) and external (mechanical – spatio-temporal) variables should be explored in more in depth. Vast evidence has been published regarding the outcome of observational studies using only one load constraint (internal/external), but now, new evidence is required about the link between the metabolic and physical/mechanical load in different sports, health conditions and settings. Additionally, these sensors usually report a high amount of data per second and from different sensors, which causes a series of difficulties when analyzing the information obtained. Whilst, some statistical proposals have been proposed in order to carry out an adequate data managing process , this mathematical and statistical approach should be studied in more depth.
In this Research Topic, we welcome researchers to submit manuscripts in the form of Original Research, Systematic and Narrative reviews, Methods, Meta-analysis, Opinion, Perspectives, Brief Research Reports and Case Studies; addressing the following topics:
• Methodological considerations for the use of new technologies in health and sports assessment
• Technical consideration in the use of new technologies in health and sport applications (e.g. calibration, validity, reliability)
• Data selection, data mining and processing methods
• New technologies and big data statistical reduction techniques and special software
• Validity and reliability of new technologies in different applications
• Relationship methods between novel external and internal workload variables in sport
• The use of wearable devices for health issues
• Relationship between internal and external workload variables in health and sports research
• Sensor fusion algorithms for sport and health monitoring applications
Despite the extensive use of new technologies in areas related to human movement, we are still lacking information in relation to data collection, mining, management, storage, analysis and reporting. Among other aspects to be considered, is the understanding of sample rates, chip sets, filtering methods, and data processing algorithms Also, the specific sample rate, chipsets, filtering methods and merging of devices data based on the principle of redundancy need to be more clearly understood. For example, it should be taken into account that each device manufacturer may apply some filtration processes before the “raw data” is available for users, and these filtration stages and filters could differ between companies. Also, the interaction between internal (metabolic) and external (mechanical – spatio-temporal) variables should be explored in more in depth. Vast evidence has been published regarding the outcome of observational studies using only one load constraint (internal/external), but now, new evidence is required about the link between the metabolic and physical/mechanical load in different sports, health conditions and settings. Additionally, these sensors usually report a high amount of data per second and from different sensors, which causes a series of difficulties when analyzing the information obtained. Whilst, some statistical proposals have been proposed in order to carry out an adequate data managing process , this mathematical and statistical approach should be studied in more depth.
In this Research Topic, we welcome researchers to submit manuscripts in the form of Original Research, Systematic and Narrative reviews, Methods, Meta-analysis, Opinion, Perspectives, Brief Research Reports and Case Studies; addressing the following topics:
• Methodological considerations for the use of new technologies in health and sports assessment
• Technical consideration in the use of new technologies in health and sport applications (e.g. calibration, validity, reliability)
• Data selection, data mining and processing methods
• New technologies and big data statistical reduction techniques and special software
• Validity and reliability of new technologies in different applications
• Relationship methods between novel external and internal workload variables in sport
• The use of wearable devices for health issues
• Relationship between internal and external workload variables in health and sports research
• Sensor fusion algorithms for sport and health monitoring applications
Keywords: performance analysis, sport medicine, injury prevention, monitoring, machine learning, wearable devices
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
