title: Design, Implementation, and Wide Pilot Deployment of FitForAll: An Easy to use Exergaming Platform Improving Physical Fitness and Life Quality of Senior Citizens.
abstract: Many platforms have emerged as response to the call for technology supporting active and healthy aging. Key requirements for any such e-health systems and any subsequent business exploitation are tailor-made design and proper evaluation. This paper presents the design, implementation, wide deployment, and evaluation of the low cost, physical exercise, and gaming (exergaming) FitForAll (FFA) platform system usability, user adherence to exercise, and efficacy are explored. The design of FFA is tailored to elderly populations, distilling literature guidelines and recommendations. The FFA architecture introduces standard physical exercise protocols in exergaming software engineering, as well as, standard physical assessment tests for augmented adaptability through adjustable exercise intensity. This opens up the way to next generation exergaming software, which may be more automatically/smartly adaptive. 116 elderly users piloted FFA five times/week, during an eight-week controlled intervention. Usability evaluation was formally conducted (SUS, SUMI questionnaires). Control group consisted of a size-matched elderly group following cognitive training. Efficacy was assessed objectively through the senior fitness (Fullerton) test, and subjectively, through WHOQoL-BREF comparisons of pre-postintervention between groups. Adherence to schedule was measured by attendance logs. The global SUMI score was 68.33±5.85%, while SUS was 77.7. Good usability perception is reflected in relatively high adherence of 82% for a daily two months pilot schedule. Compared to control group, elderly using FFA improved significantly strength, flexibility, endurance, and balance while presenting a significant trend in quality of life improvements. This is the first elderly focused exergaming platform intensively evaluated with more than 100 participants. The use of formal tools makes the findings comparable to other studies and forms an elderly exergaming corpus.
authors.forename: Evdokimos I
authors.initials: EI
authors.lastname: Konstantinidis
authors.forename: Antonis S
authors.initials: AS
authors.lastname: Billis
authors.forename: Christos A
authors.initials: CA
authors.lastname: Mouzakidis
authors.forename: Vasiliki I
authors.initials: VI
authors.lastname: Zilidou
authors.forename: Panagiotis E
authors.initials: PE
authors.lastname: Antoniou
authors.forename: Panagiotis D
authors.initials: PD
authors.lastname: Bamidis
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005081:Exercise Therapy / Q000295:instrumentation* / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010809:Physical Fitness / Q000502:physiology*; D010865:Pilot Projects; D011788:Quality of Life; D014584:User-Computer Interface; D018910:Video Games