Sports Injury Prevention Screen (SIPS): Design and Architecture of an Internet of Things (IoT) Based Analytics Health App

Gruetzemacher, Ross and Gupta, Ashish and Wilkerson, Gary B. (2016) Sports Injury Prevention Screen (SIPS): Design and Architecture of an Internet of Things (IoT) Based Analytics Health App. International Conference on Information Resources Management (CONF-IRM).

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Abstract

At present, technology-based injury risk screening methods are typically utilized by large and well-funded athletic programs at both the professional and collegiate levels. Such screening is not available to athletes who participate in most scholastic and amateur programs, due to the high cost of testing equipment and the need for oversight by medical professionals who possess the appropriate level of expertise. However, a mobile health app for injury risk screening can eliminate these obstacles, thereby facilitating the availability of systematic injury prevention initiatives to a much larger population of athletes. This study describes the design and architecture of a mobile health app for Sports Injury Prevention Screening (SIPS). SIPS enables athletic programs with limited funding and personnel the ability to conduct individualized injury risk assessments and deploy personalized injury prevention plans that are currently available only at collegiate and professional levels. Even for well funded athletic programs, typical injury screening methods are restricted to assessing either an athlete’s musculoskeletal coordination or neurocognitive abilities; assessing both simultaneously is only possible in the laboratory environment. SIPS introduces a novel, dual-task assessment by using two devices simultaneously to measure an athlete’s neuromechanical responsiveness without the requirements of a laboratory and expert-level domain knowledge. Single device tests, designed specifically to replicate established injury screening techniques using just a mobile phone, are also available in SIPS. Data is collected for all of these tests from devices’ motion sensors and is synchronized using Bluetooth® technology. Ongoing work is integrating various predictive analytics algorithms for providing real time feedback to the athlete, medical director and coaches.

Item Type: Article
Subjects: T Technology > T Technology (General)
T Technology > TH Building construction
Divisions: Faculty of Industrial Engineering and Informatics > Information System
Depositing User: staff repository 2
Date Deposited: 31 Jul 2018 18:59
Last Modified: 31 Jul 2018 18:59
URI: http://repository.ittelkom-pwt.ac.id/id/eprint/1497

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