Run-Work-Sleep-Repeat: 24/7 monitoring for healthy running

FUNDING

  • The Netherlands Organization for Scientific Research (NWO)

PARTNERS

  • 2M Engineering

  • Golazo Sports

  • Inno Sports Lab

  • City of Eindhoven

  • Fontys University of Applied Sciences

  • School of Sport Studies

BACKGROUND

The prevailing lifestyle in the Western world (immobility, unhealthy eating, smoking and drinking habits) is an important factor in the etiology of many chronic diseases. Physical activity through sports participation helps to reduce this risk but introduces new risk factors associated with exercise related injuries. The aim of the program ‘Citius, Altius, Sanius’ is to stimulate people at all performance levels to engage in and sustain physical activity through sports and fitness, improve their performance and prevent injuries by providing informative and motivating information using advanced sensor and data science techniques. The information provided is tailored to the individual user, by taking into account his or her characteristics, and by using effective, personalized feedback methods. Innovative unobtrusive wearable sensors (in clothing, and advanced cameras) will be used to estimate the mechanical and physiological load. Data science techniques will relate the load to injury mechanisms and provide an individual training advice to stimulate the athlete and prevent injuries or return to sports and exercise quicker. Six applied projects are defined incorporating the activities that are associated with most injuries. Sports associations, sports medicine and physical therapy, but also many small-to-medium-sized companies are involved to commercialize this innovative approach for recreational and elite athletes, but also for rehabilitation patients.

Physical activity is the best medicine to prevent health problems across the lifespan: it is more efficient than cure or rehabilitation, both from a health and an economic perspective. The goal of the present program is to stimulate people to start and continue participating in sports by providing motivational and informational cues about their performance, using (big) data science and unobtrusive sensor technology. Simultaneously, personalized information, based on a combination of individual and cohort data, will be provided to recreational and elite athletes to reduce the risk of injury and overload. There is a clear trend towards individualized sports participation. Tailoring information to individual needs concerning physical activity is therefore crucial. Modern sensor technology and data science, as well as web solutions and apps like Strava, provide opportunities for obtaining this tailored information. The internet enables comparison with peers of the same age, gender, experience, training and performance objectives, etc., as well as the full history of previous performances in the cloud. Knowledge about performance improvement is a highly stimulating factor that contributes to lasting engagement and attaining higher performance levels.

The challenges in promoting healthy participation in physical exercise are twofold: (1), to provide engaging information about the athlete’s physical and performance improvement, and (2) to ensure that no injuries will occur. Although injuries prevail in many sports (see Section 4.1), little is known about their relationship with physical load.

Hence, there is a clear need to strengthen the information chain from sensor information, via data science and analysis, to informative feedback applications, which we will pursue in three fundamentally oriented projects. This not only requires innovative research regarding each of these components, but also regarding the effectiveness of the resulting information chains. For the latter purpose, we will perform research in six sports-related domains with a high prevalence of injuries. The general relationship between physical exercise and injury incidence in these domains will be investigated by acquiring large amounts of data using new sensor technology and will then be tuned to individual athletes using their individual data. The resulting individualized information will be fed back to the athlete to improve performance in a healthy manner. The feedback in question will be based on novel technological possibilities, including virtual and augmented realities, as well as novel psychological insights into mechanisms of behavioral changes.

Within each of the fundamental projects, innovative devices or mathematical approaches will be developed. Within the applied projects, these innovations will be combined, and applied to six different sport specific domains to motivate athletes and improve their performance, as well as to prevent injuries. This general approach adopted in the program as a whole is unprecedented, both in terms of its interdisciplinary and translational nature and in terms of its scale and scope.