Wearable systems and mobile applications for diabetes disease management

Health and Technology

Volumn 4, Issue 2, 2014, Pages 101-112

  Georga, Eleni I ^a   Protopappas, Vasilios C ^a   Bellos, Christos V ^a   Fotiadis, Dimitrios I ^a  

^a UNIVERSITY OF IOANNINA   (Greece)

Author keywords

Chronic disease self management; Diabetes; Lifestyle tracking; Mobile applications; Mobile health; Wearable medical devices

Indexed keywords

GLUCOSE; INSULIN;

ARTIFICIAL PANCREAS; AUTOMATION; BLOOD GLUCOSE MONITORING; CONTROL SYSTEM; DECISION SUPPORT SYSTEM; DIABETES MELLITUS; EQUIPMENT DESIGN; GLUCOSE BLOOD LEVEL; GLUCOSE SENSOR; HUMAN; INSULIN PUMP; INTERVENTION STUDY; MEDICAL DEVICE; MEDICAL TECHNOLOGY; META ANALYSIS (TOPIC); MOBILE APPLICATION; MOBILE PHONE; PORTABLE EQUIPMENT; REVIEW; SELF CARE; VALIDITY; WEARABLE MEDICAL DEVICE; WIRELESS COMMUNICATION;

EID: 84940285201     PISSN: 21907188     EISSN: 21907196     Source Type: Journal    
DOI: 10.1007/s12553-014-0082-y     Document Type: Review

References (106)

1. American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2013;36(1):67-74. doi:10.2337/dc13-S067.
2. American Diabetes A. Standards of medical care in diabetes-2013. Diabetes Care. 2013;36(1):11-66. doi:10.2337/dc13-S011.
3. Cobelli C, Renard E, Kovatchev B. Artificial pancreas: past, present, future. Diabetes. 2011;60(11):2672-82. doi:10.2337/db11-0654.
4. Kovatchev BP. Diabetes technology: markers, monitoring, assessment, and control of blood glucose fluctuations in diabetes. Sci. 2012;2012:14. doi:10.6064/2012/283821.
5. Baron J, McBain H, Newman S. The impact of mobile monitoring technologies on glycosylated hemoglobin in diabetes: a systematic review. J Diabetes Sci Technol. 2012;6(5):1185-96.
6. Eng DS, Lee JM. The promise and peril of mobile health applications for diabetes and endocrinology. Pediatr Diabetes. 2013;14(4):231-8. doi:10.1111/pedi.12034.
7. Holtz B, Lauckner C. Diabetes management via mobile phones: a systematic review. telemedicine journal and e-health. J American Telemedicine Association. 2012;18(3):175-84. doi:10.1089/tmj.2011.0119.
8. Kouris I, Mougiakakou S, Scarnato L, Iliopoulou D, Diem P, Vazeou A, et al. Mobile phone technologies and advanced data analysis towards the enhancement of diabetes self-management. Int J Electron Healthc. 2010;5(4):386-402.
9. Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, et al. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabetic medicine: a journal of the British Diabetic Association. 2011;28(4):455-63. doi:10.1111/j.1464-5491.2010.03180.x.
10. Tran J, Tran R, White JR. Smartphone-based glucose monitors and applications in the management of diabetes: an overview of 10 salient "apps" and a novel Smartphone-connected blood glucose monitor. Clin Diabetes. 2012;30(4):173-8. doi:10.2337/diaclin.30.4.173.
11. El-Gayar O, Timsina P, Nawar N, Eid W. Mobile applications for diabetes self-management: status and potential. J Diabetes Sci Technol. 2013;7(1):247-62.
12. Miller KM, Beck RW, Bergenstal RM, Goland RS, Haller MJ, McGill JB, et al. Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin a1c levels in t1d exchange clinic registry participants. Diabetes Care. 2013;36(7):2009-14. doi:10.2337/dc12-1770.
13. Ziegler R, Heidtmann B, Hilgard D, Hofer S, Rosenbauer J, Holl R, et al. Frequency of smbg correlates with hba1c and acute complications in children and adolescents with type 1 diabetes. Pediatr Diabetes. 2011;12(1):11-7. doi:10.1111/j.1399-5448.2010.00650.x.
14. Bergenstal RM, Ahmann AJ, Bailey T, Beck RW, Bissen J, Buckingham B, et al. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the ambulatory glucose profile (agp). Diabetes Technol Ther. 2013;15(3):198-211. doi:10.1089/dia.2013.0051.
15. Phillip M, Danne T, Shalitin S, Buckingham B, Laffel L, Tamborlane W, et al. Use of continuous glucose monitoring in children and adolescents (&z.ast;). Pediatr Diabetes. 2012;13(3):215-28. doi:10.1111/j.1399-5448. 2011.00849.x.
16. Hirsch IB, Armstrong D, Bergenstal RM, Buckingham B, Childs BP, Clarke WL, et al. Clinical application of emerging sensor technologies in diabetes management: Consensus guidelines for continuous glucose monitoring (cgm). Diabetes Technol Ther. 2008;10(4):232-44. doi:10.1089/dia.2008.0016. quiz 245-236.
17. Klonoff DC. Continuous glucose monitoring: road map for 21st century diabetes therapy. Diabetes Care. 2005;28(5):1231-9. (Pubitemid 40616646)
18. Battelino T, Phillip M, Bratina N, Nimri R, Oskarsson P, Bolinder J. Effect of continuous glucose monitoring on hypoglycemia in type 1 diabetes. Diabetes Care. 2011;34(4):795-800. doi:10.2337/dc10-1989.
19. Garg S, Zisser H, Schwartz S, Bailey T, Kaplan R, Ellis S, et al. Improvement in glycemic excursions with a trans cutaneous, real-time continuous glucose sensor: a randomized controlled trial. Diabetes Care. 2006;29(1):44-50. (Pubitemid 44033429)
20. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study G, Beck RW, Hirsch IB, Laffel L, Tamborlane WV, Bode BW, Buckingham B, Chase P, Clemons R, Fiallo-Scharer R, Fox LA, Gilliam LK, Huang ES, Kollman C, Kowalski AJ, Lawrence JM, Lee J, Mauras N, O'Grady M, Ruedy KJ, Tansey M, Tsalikian E, Weinzimer SA, Wilson DM, Wolpert H, Wysocki T, Xing D. The effect of continuous glucose monitoring in well-controlled type 1 diabetes. Diabetes care. 2009;32(8):1378-83. doi:10.2337/dc09-0108.
21. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study G, Tamborlane WV, Beck RW, Bode BW, Buckingham B, Chase HP, Clemons R, Fiallo-Scharer R, Fox LA, Gilliam LK, Hirsch IB, Huang ES, Kollman C, Kowalski AJ, Laffel L, Lawrence JM, Lee J, Mauras N, O'Grady M, Ruedy KJ, Tansey M, Tsalikian E, Weinzimer S, Wilson DM, Wolpert H, Wysocki T, Xing D. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008;359(14):1464-76. doi:10.1056/NEJMoa0805017.
22. Vigersky RA, Fonda SJ, Chellappa M, Walker MS, Ehrhardt NM. Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes. Diabetes Care. 2012;35(1):32-8. doi:10.2337/dc11-1438.
23. Pickup JC, Freeman SC, Sutton AJ. Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: Meta-analysis of randomised controlled trials using individual patient data. BMJ. 2011;343:3805. doi:10.1136/bmj.d3805.
24. Damiano ER, El-Khatib FH, Zheng H, Nathan DM, Russell SJ. A comparative effectiveness analysis of three continuous glucose monitors. Diabetes Care. 2013;36(2):251-9. doi:10.2337/dc12-0070.
25. Freckmann G, Pleus S, Link M, Zschornack E, Klotzer HM, Haug C. Performance evaluation of three continuous glucose monitoring systems: comparison of six sensors per subject in parallel. J Diabetes Sci Technol. 2013;7(4):842-53.
26. Garg SK, Smith J, Beatson C, Lopez-Baca B, Voelmle M, Gottlieb PA. Comparison of accuracy and safety of the seven and the navigator continuous glucose monitoring systems. Diabetes Technol Ther. 2009;11(2):65-72. doi:10.1089/dia.2008.0109.
27. Kovatchev B, Anderson S, Heinemann L, Clarke W. Comparison of the numerical and clinical accuracy of four continuous glucose monitors. Diabetes Care. 2008;31(6):1160-4. doi:10.2337/dc07-2401.
28. Rossetti P, Bondia J, Vehi J, Fanelli CG. Estimating plasma glucose from interstitial glucose: the issue of calibration algorithms in commercial continuous glucose monitoring devices. Sensors. 2010;10(12):10936-52. doi:10.3390/s101210936.
29. Sparacino G, Facchinetti A, Cobelli C. "Smart" continuous glucose monitoring sensors: on-line signal processing issues. Sensors. 2010;10(7):6751-72.
30. Facchinetti A, Sparacino G, Guerra S, Luijf YM, DeVries JH, Mader JK, et al. Real-time improvement of continuous glucose monitoring accuracy: the smart sensor concept. Diabetes Care. 2013;36(4):793-800. doi:10.2337/dc12-0736.
31. Keenan DB, Cartaya R, Mastrototaro JJ. Accuracy of a new realtime continuous glucose monitoring algorithm. J Diabetes Sci Technol. 2010;4(1):111-8.
32. McGarraugh G, Bergenstal R. Detection of hypoglycemia with continuous interstitial and traditional blood glucose monitoring using the freestyle navigator continuous glucosemonitoring system. Diabetes Technol Ther. 2009;11(3):145-50. doi:10.1089/dia.2008.0047.
33. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The diabetes control and complications trial research group. N Engl J Med. 1993;329(14):977-86. doi:10.1056/NEJM199309303291401.
34. Misso ML, Egberts KJ, Page M, O'Connor D, Shaw J. Continuous subcutaneous insulin infusion (csii) versus multiple insulin injections for type 1 diabetes mellitus. The Cochrane database of systematic reviews. 2010(1):Cd005103. doi:10.1002/14651858.CD005103.pub2.
35. Pickup JC, Sutton AJ. Severe hypoglycaemia and glycaemic control in type 1 diabetes: meta-analysis of multiple daily insulin injections compared with continuous subcutaneous insulin infusion. Diabet Med: J Br Diabet Assoc. 2008;25(7):765-74. doi:10.1111/j.1464-5491.2008.02486.x.
36. Yeh HC, Brown TT, Maruthur N, Ranasinghe P, Berger Z, Suh YD, et al. Comparative effectiveness and safety of methods of insulin delivery and glucose monitoring for diabetes mellitus: A systematic review and meta-analysis. Ann Intern Med. 2012;157(5):336-47. doi:10.7326/0003-4819-157-5-201209040-00508.
37. Hirsch IB. Reducing hypoglycemia in type 1 diabetes: An incremental step forward. Diabetes Technol Ther. 2013;15(7):531-2. doi:10.1089/dia.2013.0174.
38. Bergenstal RM, Tamborlane WV, Ahmann A, Buse JB, Dailey G, Davis SN, et al. Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes. N Engl J Med. 2010;363(4):311-20. doi:10.1056/NEJMoa1002853.
39. Bergenstal RM, Tamborlane WV, Ahmann A, Buse JB, Dailey G, Davis SN, et al. Sensor-augmented pump therapy for a1c reduction (star 3) study: results from the 6-month continuation phase. Diabetes Care. 2011;34(11):2403-5. doi:10.2337/dc11-1248.
40. Hirsch IB, Abelseth J, Bode BW, Fischer JS, Kaufman FR, Mastrototaro J, et al. Sensor-augmented insulin pump therapy: results of the first randomized treat-to-target study. Diabetes Technol Ther. 2008;10(5):377-83. doi:10.1089/dia.2008.0068.
41. Norgaard K, Scaramuzza A, Bratina N, Lalic NM, Jarosz-Chobot P, Kocsis G, et al. Routine sensor-augmented pump therapy in type 1 diabetes: the interpret study. Diabetes Technol Ther. 2013;15(4):273-80. doi:10.1089/dia.2012.0288.
42. Bergenstal RM, Klonoff DC, Garg SK, Bode BW, Meredith M, Slover RH, et al. Threshold-based insulin-pump interruption for reduction of hypoglycemia. N Engl J Med. 2013;369(3):224-32. doi:10.1056/NEJMoa1303576.
43. Ly TT, Nicholas JA, Retterath A, Lim EM, Davis EA, Jones TW. Effect of sensor-augmented insulin pump therapy and automated insulin suspension vs standard insulin pump therapy on hypoglycemia in patients with type 1 diabetes: a randomized clinical trial. JAMA. 2013;310(12):1240-7. doi:10.1001/jama.2013. 277818.
44. Buckingham B, Chase HP, Dassau E, Cobry E, Clinton P, Gage V, et al. Prevention of nocturnal hypoglycemia using predictive alarm algorithms and insulin pump suspension. Diabetes Care. 2010;33(5):1013-7. doi:10.2337/dc09- 2303.
45. Buckingham BA, Cameron F, Calhoun P, Maahs DM, Wilson DM, Chase HP, et al. Outpatient safety assessment of an in-home predictive low-glucose suspend system with type 1 diabetes subjects at elevated risk of nocturnal hypoglycemia. Diabetes Technol Ther. 2013;15(8):622-7. doi:10.1089/dia.2013.0040.
46. Hughes CS, Patek SD, Breton MD, Kovatchev BP. Hypoglycemia prevention via pump attenuation and red-yellow-green "traffic" lights using continuous glucose monitoring and insulin pump data. J Diabetes Sci Technol. 2010;4(5):1146-55.
47. Atlas E, Nimri R, Miller S, Grunberg EA, Phillip M. Md-logic artificial pancreas system: a pilot study in adults with type 1 diabetes. Diabetes Care. 2010;33(5):1072-6. doi:10.2337/dc09-1830.
48. Breton M, Farret A, Bruttomesso D, Anderson S, Magni L, Patek S, et al. Fully integrated artificial pancreas in type 1 diabetes: Modular closed-loop glucose control maintains near normoglycemia. Diabetes. 2012;61(9):2230-7. doi:10.2337/db11-1445.
49. Hovorka R, Allen JM, Elleri D, Chassin LJ, Harris J, Xing D, et al. Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial. Lancet. 2010;375(9716):743-51. doi:10.1016/S0140-6736(09)61998-X.
50. Hovorka R, Kumareswaran K, Harris J, Allen JM, Elleri D, Xing D, et al. Overnight closed loop insulin delivery (artificial pancreas) in adults with type 1 diabetes: crossover randomised controlled studies. BMJ. 2011;342:1855. doi:10.1136/bmj.d1855.
51. Kovatchev B, Cobelli C, Renard E, Anderson S, Breton M, Patek S, et al. Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results. J Diabetes Sci Technol. 2010;4(6):1374-81.
52. Weinzimer SA, Steil GM, Swan KL, Dziura J, Kurtz N, Tamborlane WV. Fully automated closed-loop insulin delivery versus semiautomated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas. Diabetes Care. 2008;31(5):934-9. doi:10.2337/dc07-1967.
53. Phillip M, Battelino T, Atlas E, Kordonouri O, Bratina N, Miller S, et al. Nocturnal glucose control with an artificial pancreas at a diabetes camp. N Engl J Med. 2013;368(9):824-33. doi:10.1056/NEJMoa1206881.
54. Elleri D, Allen JM, Biagioni M, Kumareswaran K, Leelarathna L, Caldwell K, et al. Evaluation of a portable ambulatory prototype for automated overnight closed-loop insulin delivery in young people with type 1 diabetes. Pediatr Diabetes. 2012;13(6):449-53. doi:10.1111/j.1399-5448.2012.00903.x.
55. O'Grady MJ, Retterath AJ, Keenan DB, Kurtz N, Cantwell M, Spital G, et al. The use of an automated, portable glucose control system for overnight glucose control in adolescents and young adults with type 1 diabetes. Diabetes Care. 2012;35(11):2182-7. doi:10.2337/dc12-0761.
56. Kovatchev BP, Renard E, Cobelli C, Zisser HC, Keith-Hynes P, Anderson SM, et al. Feasibility of outpatient fully integrated closed-loop control: first studies of wearable artificial pancreas. Diabetes Care. 2013;36(7):1851-8. doi:10.2337/dc12-1965.
57. Patek SD, Magni L, Dassau E, Karvetski C, Toffanin C, De Nicolao G, et al. Modular closed-loop control of diabetes. IEEE transactions on bio-medical engineering. 2012;59(11):2986-99. doi:10.1109/tbme.2012.2192930.
58. Breton M, Farret A, Bruttomesso D, Anderson S, Magni L, Patek S, et al. Group oboTIAPS. Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia. Diabetes. 2012;61(9):2230-7.
59. Miller S, Nimri R, Atlas E, Grunberg EA, Phillip M. Automatic learning algorithm for the md-logic artificial pancreas system. Diabetes Technol Ther. 2011;13(10):983-90. doi:10.1089/dia.2010.0216.
60. Kovatchev BP, Breton M, Man CD, Cobelli C. In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. J Diabetes Sci Technol. 2009;3(1):44-55.
61. Dalla Man C, Rizza RA, Cobelli C. Meal simulation model of the glucose-insulin system. IEEE transactions on bio-medical engineering. 2007;54(10):1740-9. doi:10.1109/TBME.2007.893506. (Pubitemid 47450539)
62. Rusin M, Arsand E, Hartvigsen G. Functionalities and input methods for recording food intake: a systematic review. Int J Med Inform. 2013;82(8):653-64. doi:10.1016/j.ijmedinf.2013.01.007.
63. Tatara N, Arsand E, Bratteteig T, Hartvigsen G. Usage and perceptions of a mobile self-management application for people with type 2 diabetes: qualitative study of a five-month trial. Stud Health Technol Inform. 2013;192:127-31.
64. Arsand E, Tatara N, Ostengen G, Hartvigsen G. Mobile phone-based self-management tools for type 2 diabetes: the few touch application. J Diabetes Sci Technol. 2010;4(2):328-36.
65. Carroll AE, DiMeglio LA, Stein S, Marrero DG. Using a cell phone-based glucose monitoring system for adolescent diabetes management. The Diabetes educator. 2011;37(1):59-66. doi:10.1177/0145721710387163.
66. Carroll AE, Marrero DG, Downs SM. The healthpia glucopack diabetes phone: a usability study. Diabetes Technol Ther. 2007;9(2):158-64. doi:10.1089/dia.2006.0002. (Pubitemid 46652550)
67. Faridi Z, Liberti L, Shuval K, Northrup V, Ali A, Katz DL. Evaluating the impact of mobile telephone technology on type 2 diabetic patients' self-management: the niche pilot study. J Eval Clin Pract. 2008;14(3):465-9. doi:10.1111/j.1365-2753.2007.00881.x. (Pubitemid 351643254)
68. Istepanian RS, Zitouni K, Harry D, Moutosammy N, Sungoor A, Tang B, et al. Evaluation of a mobile phone tele monitoring system for glycaemic control in patients with diabetes. J Telemed Telecare. 2009;15(3):125-8. doi:10.1258/jtt.2009.003006.
69. Katz DL, Nordwall B. Novel interactive cell-phone technology for health enhancement. J Diabetes Sci Technol. 2008;2(1):147-53.
70. Quinn CC, Clough SS, Minor JM, Lender D, Okafor MC, Gruber-Baldini A. Well doc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther. 2008;10(3):160-8. doi:10.1089/dia.2008.0283. (Pubitemid 351677598)
71. Turner J, Larsen M, Tarassenko L, Neil A, Farmer A. Implementation of tele health support for patients with type 2 diabetes using insulin treatment: an exploratory study. Inform Prim Care. 2009;17(1):47-53.
72. Arsand E, Froisland DH, Skrovseth SO, Chomutare T, Tatara N, Hartvigsen G, et al. Mobile health applications to assist patients with diabetes: lessons learned and design implications. J Diabetes Sci Technol. 2012;6(5):1197-206.
73. Klasnja P, Pratt W. Healthcare in the pocket: mapping the space of mobile-phone health interventions. J Biomed Inform. 2012;45(1):184-98. doi:10.1016/j.jbi.2011.08.017.
74. Cho JH, Lee HC, Lim DJ, Kwon HS, Yoon KH. Mobile communication using a mobile phone with a gluco meter for glucose control in type 2 patients with diabetes: as effective as an internet-based glucose monitoring system. J Telemed Telecare. 2009;15(2):77-82. doi:10.1258/jtt.2008.080412.
75. Farmer A, Gibson O, Hayton P, Bryden K, Dudley C, Neil A, et al. A real-time, mobile phone-based telemedicine system to support young adults with type 1 diabetes. Inform Prim Care. 2005;13(3):171-7. (Pubitemid 41684084)
76. Franklin VL, Greene A, Waller A, Greene SA, Pagliari C. Patients' engagement with "sweet talk" - a text messaging support system for young people with diabetes. J Med Internet Res. 2008;10(2):e20. doi:10.2196/jmir.962.
77. Kim SI, Kim HS. Effectiveness of mobile and internet intervention in patients with obese type 2 diabetes. Int JMed Inform. 2008;77(6):399-404. doi:10.1016/j.ijmedinf.2007.07.006.
78. Kwon HS, Cho JH, Kim HS, Lee JH, Song BR, Oh JA, et al. Development of web-based diabetic patient management system using short message service (sms). Diabetes Res Clin Pract. 2004;66(1):133-7. doi:10.1016/j.diabres.2003.10.028.
79. Larsen ME, Turner J, Farmer A, Neil A, Tarassenko L. Telemedicine- supported insulin optimisation in primary care. J Telemed Telecare. 2010;16(8):433-40. doi:10.1258/jtt.2010.100103.
80. Nes AA, van Dulmen S, Eide E, Finset A, Kristjansdottir OB, Steen IS, et al. The development and feasibility of a web-based intervention with diaries and situational feedback via smart phone to support self-management in patients with diabetes type 2. Diabetes Res Clin Pract. 2012;97(3):385-93. doi:10.1016/j.diabres.2012.04.019.
81. Vähätalo MA, Virtamo HE, Viikari JS, Rönnemaa T. Cellular phone transferred self blood glucose monitoring: prerequisites for positive outcome. Practical Diabetes International. 2004;21(5):192-4. doi:10.1002/pdi.642.
82. Quinn CC, Shardell MD, Terrin ML, Barr EA, Ballew SH, Gruber-Baldini AL. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care. 2011;34(9):1934-42. doi:10.2337/dc11-0366.
83. Charpentier G, Benhamou PY, Dardari D, Clergeot A, Franc S, Schaepelynck-Belicar P, et al. The diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves hba1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (telediab 1 study). Diabetes Care. 2011;34(3):533-9. doi:10.2337/dc10-1259.
84. Lim S, Kang SM, Shin H, Lee HJ, Won Yoon J, Yu SH, et al. Improved glycemic control without hypoglycemia in elderly diabetic patients using the ubiquitous healthcare service, a new medical information system. Diabetes Care. 2011;34(2):308-13. doi:10.2337/dc10-1447.
85. Curran K, Nichols E, Xie E, Harper R. An intensive insulinotherapy mobile phone application built on artificial intelligence techniques. J Diabetes Sci Technol. 2010;4(1):209-20.
86. Harris LT, Tufano J, Le T, Rees C, Lewis GA, Evert AB, et al. Designing mobile support for glycemic control in patients with diabetes. J Biomed Inform. 2010;43(5):S37-40. doi:10.1016/j.jbi.2010.05.004.
87. Kim CS, Park SY, Kang JG, Lee SJ, Ihm SH, Choi MG, et al. Insulin dose titration system in diabetes patients using a short messaging service automatically produced by a knowledge matrix. Diabetes Technol Ther. 2010;12(8):663-9. doi:10.1089/dia.2010.0031.
88. Mougiakakou SG, Bartsocas CS, Bozas E, Chaniotakis N, Iliopoulou D, Kouris I, et al. Smartdiab: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients. IEEE Trans Inf Technol Biomed. 2010;14(3):622 -33. doi:10.1109/TITB.2009.2039711.
89. Rossi MC, Nicolucci A, Di Bartolo P, Bruttomesso D, Girelli A, Ampudia FJ, et al. Diabetes interactive diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: An open-label, international, multicenter, randomized study. Diabetes Care. 2010;33(1):109-15. doi:10.2337/dc09-1327.
90. Yoo HJ, Park MS, Kim TN, Yang SJ, Cho GJ, Hwang TG, et al. A ubiquitous chronic disease care system using cellular phones and the internet. Diabetic medicine: a journal of the British Diabetic Association. 2009;26(6):628-35. doi:10.1111/j.1464-5491.2009.02732.x.
91. Skrovseth SO, Arsand E, Godtliebsen F, Hartvigsen G. Mobile phone-based pattern recognition and data analysis for patients with type 1 diabetes. Diabetes Technol Ther. 2012;14(12):1098-104. doi:10.1089/dia.2012.0160.
92. Skrovseth SO, Arsand E, Godtliebsen F, Joakimsen RM. Model-driven diabetes care: study protocol for a randomized controlled trial. Trials. 2013;14:139. doi:10.1186/1745-6215-14-139.
93. Georga E, Protopappas V, Guillen A, Fico G, Ardigo D, Arredondo MT, Exarchos TP, Polyzos D, Fotiadis DI. Data mining for blood glucose prediction and knowledge discovery in diabetic patients: The metabo diabetes modeling and management system. Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Conference. 2009;2009:5633-6. doi:10.1109/IEMBS. 2009.5333635.
94. Poulsen JU, Avogaro A, Chauchard F, Cobelli C, Johansson R, Nita L, Pogose M, Del Re L, Renard E, Sampath S, Saudek F, Skillen M, Soendergaard J. A diabetes management system empowering patients to reach optimised glucose control: From monitor to advisor. Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Conference. 2010;2010:5270-1. doi:10.1109/IEMBS.2010.5626313.
95. Stahl F, Johansson R. Diabetes mellitus modeling and short-term prediction based on blood glucose measurements. Math Biosci. 2009;217(2):101-17. doi:10.1016/j.mbs.2008.10.008.
96. Pappada SM, Cameron BD, Rosman PM, Bourey RE, Papadimos TJ, Olorunto W, et al. Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetes. Diabetes Technol Ther. 2011;13(2):135-41. doi:10.1089/dia.2010.0104.
97. Eren-Oruklu M, Cinar A, Rollins DK, Quinn L. Adaptive system identification for estimating future glucose concentrations and hypoglycemia alarms. automatica: the journal of IFAC. International Federation of Automatic Control. 2012;48(8):1892-7. doi:10.1016/j.automatica.2012.05.076.
98. Zecchin C, Facchinetti A, Sparacino G, De Nicolao G, Cobelli C. Neural network incorporating meal information improves accuracy of short-time prediction of glucose concentration. IEEE transactions on bio-medical engineering. 2012;59(6):1550-60. doi:10.1109/TBME.2012.2188893.
99. Daskalaki E, Norgaard K, Zuger T, Prountzou A, Diem P, Mougiakakou S. An early warning system for hypoglycemic/hyperglycemic events based on fusion of adaptive prediction models. J Diabetes Sci Technol. 2013;7(3):689-98.
100. Georga EI, Protopappas VC, Ardigo D, Polyzos D, Fotiadis DI. A glucose model based on support vector regression for the prediction of hypoglycemic events under free-living conditions. Diabetes Technol Ther. 2013;15(8):634-43. doi:10.1089/dia.2012.0285.
101. Georga EI, Protopappas VC, Ardigo D, Marina M, Zavaroni I, Polyzos D, et al. Multivariate prediction of subcutaneous glucose concentration in type 1 diabetes patients based on support vector regression. IEEE journal of biomedical and health informatics. 2013;17(1):71-81. doi:10.1109/TITB.2012.2219876.
102. Zecchin C, Facchinetti A, Sparacino G, Cobelli C. Reduction of number and duration of hypoglycemic events by glucose prediction methods: a proof-of-concept in silico study. Diabetes Technol Ther. 2013;15(1):66-77. doi:10.1089/dia.2012.0208.
103. Chomutare T, Fernandez-Luque L, Arsand E, Hartvigsen G. Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines. Journal of medical Internet research. 2011;13(3):65. doi:10.2196/jmir.1874.
104. Arora S, Peters AL, Agy C, Menchine M. A mobile health intervention for inner city patients with poorly controlled diabetes: proof-of-concept of the text-med program. Diabetes Technol Ther. 2012;14(6):492-6. doi:10.1089/dia.2011. 0252.
105. Brath H, Morak J, Kastenbauer T, Modre-Osprian R, Strohner-Kastenbauer H, Schwarz M, et al. Mobile health (mhealth) based medication adherence measurement - a pilot trial using electronic blisters in diabetes patients. Br J Clin Pharmacol. 2013;76(1):47-55. doi:10.1111/bcp.12184.
106. Patel S, Jacobus-Kantor L, Marshall L, Ritchie C, Kaplinski M, Khurana PS, et al. Mobilizing your medications: an automated medication reminder application for mobile phones and hypertension medication adherence in a high-risk urban population. J Diabetes Sci Technol. 2013;7(3):630-9.