mHealth: A Design of an Exercise Recommendation System for the Android Operating System
Keywords:eHealth, mHealth, expert system, exercise recommendation system, Android mobile application
AbstractFor healthiness and wellness, exercising is one of the key factors. Therefore, this paper aims to present the first phase of a mobile health application developed to recommend healthcare support referring to exercises on an Android smartphone. This application has been designed to provide exercise advice depending on Body Mass Index (BMI), Basal Metabolic Rate (BMR) and the energy used in each activity or sport (e.g. aerobic dancing, cycling, jogging working and swimming). Also, this application has been designed to present special exercise advice for patients with health issues. Moreover, it has been designed to store information in a database and to have the ability to produce reports to users. After designing, this proposed mHealth application has been evaluated by 30 subjects who have computer programming skills. It has been found that all diagrams, including use the case diagram, sequence diagrams and overall were assessed as ‘good’, except the part of user interfaces that was assessed as ‘fair’. Therefore, this design can be used to implement in the next phase of this application development with minor revision concerning the user interfaces.
Gartner Identifies the Top 10 Consumer Mobile Applications for 2012. Available at: http://www.gartner.com/newsroom/id/1230413, accessed May 2014.
Gartner Identifies the Top 10 Strategic Technology Trends for 2013. Available at: http://www.gartner.com/newsroom/id/2209615, accessed May 2014.
mHealth in an mWorld: How mobile technology is transforming health care. Available at: http://www.deloitte.com/assets/Dcom-UnitedStates/Local%20Assets/Documents/us_chs_2012_mHealth_HowMobileTechnologyIsTransformingHealthcare_032213.pdf, accessed May 2014.
W Toyib, ES Lee and MG Park. An integrative method on the remote monitoring of walking activity using ubiquitous healthcare system. Int. J. Electron. Eng. Inform. 2011; 3, 453-63.
Android and iOS Combine for 91.1% of the Worldwide Smartphone OS Market in 4Q12 and 87.6% for the Year, According to IDC. Available at: http://www.idc.com/getdoc.jsp?containerId=prUS23946013, accessed May 2014.
EAV Navarro, JR Mas and JF Navajas. Analysis and measurement of a wireless telemedicine system. In: Proceeding of Pervasive Health Conference and Workshops, Innsbruck, Austria, 2006, p. 1-6.
CZ Qiang, M Yamamichi, V Hausman, R Miller and D Altman. Mobile Applications for the Health Sector. April 2012. Available at: http://siteresources.worldbank.org/INFORMATIONANDCOMMUNICATIONANDTECHNOLOGIES/Resources/mHealth_report_(Apr_2012).pdf, accessed May 2014.
BMI Calculator. Available at: http://www.bmi-calculator.net, accessed May 2014.
R Khwanchuea, S Thanapop, S Samuhasaneeto, S Chartwaingam and S Mukem. Bone mass, body mass index, and lifestyle factors: A case study of Walailak University staff. Walailak J. Sci. & Tech. 2012; 9, 263-75.
R Khwanchuea, S Thanapop, S Samuhasaneeto, S Chartwaingam and S Mukem. Waist circumference: A key determinant of bone mass in University students. Walailak J. Sci. & Tech. 2013; 10, 665-76.
BMR Formula. Available at: http://www.bmi-calculator.net/bmr-calculator/bmr-formula.php, accessed May 2014.
Calculate Basal Metabolic Rate (BMR). Available at: http://oregonstate.edu/uhds/nutritionalcalculator, accessed May 2014.
MET: The standard metabolic equivalent. Available at: http://sportsmedicine.about.com/od/glossary/g/MET.htm, accessed May 2014.
M Jette, K Sidney and G Blumchen. Metabolic equivalents (METS) in exercise testing, exercise prescription, and evaluation of functional capacity. Clin. Cardiol. 1990; 13, 555-65.
How to calculate calories burned. Available at: http://www.livestrong.com/article/18303-calculate-calories-burned, accessed May 2014.
B Bushman. Complete Guide to Fitness Health, Human Kinetics, Champaign, IL, 2011, p. 98-114.
Cardiac Conditions: Safe Exercise for Patients with Heart Disease. Available at: http://www.nationaljewish.org/healthinfo/conditions/cardio/exercise-and-heart-disease, accessed May 2014.
Android Overview. Available at: http://www.tutorialspoint.com/android/android_overview.htm, accessed May 2014.
Android Architecture. Available at: http://elinux.org/Android_Architecture, accessed May 2014.
JW Satzinger, RB Jackson and SD Burd. Systems Analysis and Design in a Changing World. 3rd ed. Massachusetts, Thomson, 2004, p. 36-56.
B Oestereich. Developing Software with UML, Essex, England, Addison Wesley, 1999, p. 171-274.
J Mattila, H Ding, E Mattila and A Särelä. Mobile tools for home-base cardiac rehabilitation based on heart rate and movement activity analysis. In: Proceeding of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, Minnesota, USA, 2009, p. 6448-52.
A Särelä, J Salminen, E Koskinen, O Kirkeby, I Korhonen and D Walters. A home-base care model for outpatient cardiac rehabilitation base on mobile technologies. In: Proceeding of the 3rd International Conference on Pervasive Computing Technologies for Healthcare 2009, Landon, UK, 2009, p. 1-8.
H Watanabe, M Kawarasaki, A Sato and K Yoshida. Development of wearable heart disease monitoring and alerting system associated with smartphone. In: Proceeding of the 14th IEEE International Conference on eHealth Networking, Applications and Services (Healthcom 2012), Beijing, China, 2012, pp. 292-297. Available at: http://ieeexplore.ieee.org/xpl/
articleDetails.jsp?arnumber=6379423, accessed May 2014.
PD Haghighi, A Zaslavsky, S Krishnaswamy and MM Gaber. Mobile data mining for intelligent healthcare support. In: Proceeding of the 42nd Hawaii International Conference on System Sciences 2009, Big Island, Hawaii, USA, 2009, p. 1-10.
V Jones, V Gay and P Leijdekkers. Body sensor networks for mobile health monitoring: Experience in Europe and Australia. In: Proceeding of the 4th International Conference on Digital Society 2010 (ICDS ’10), St. Maarten, Netherlands Antilles, 2010, p. 2004-9.
LUH Munoz, SI Woolley and C Baber. A mobile health device to help people with severe allergies. In: Proceeding of the 2nd International Conference on Pervasive Computing Technologies for Healthcare 2008, Tampere, Finland, 2008, p. 8-10.
BM Silva, IM Lopes, JJPC Rodrigues and P Ray. SapoFitness: A mobile health application for dietary evaluation. In: Proceeding of the 13th IEEE International Conference on eHealth Networking Applications and Services (Healthcom 2011), Columbia, Missouri, USA, 2011, p. 375-80.
G Kovasznai. Developing an expert system for diet recommendation. In: Proceeding of the 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) 2011, Timişoara, Romania, May 2011, p. 505-9.
B Parmanto, G Pramana, DX Yu, AD Fairman, BE Dicianno and MP McCue. iMHere: A novel mHealth system for supporting self-care in management of complex and chronic conditions. JMIR Mhealth Uhealth. 2013; 1, 1-16.
Performance review of Sodexo Ltd. Available at: http://whitehorsedc.moderngov.co.uk/mgConvert2PDF.aspx?ID=16124, accessed May 2014.
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