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. 2021 Jun 3;9(6):e25138. doi: 10.2196/25138

Table 1.

Summary of medical topics, diabetes types, and research goals, ordered by the year of publication.

Manuscript Medical classification Diabetes type Research goals
Najafi et al (2010) [44] Patients with DMa used as case study Not specified Find association between posture and balance control among patients with different DM complications
Grewal et al (2013) [56] DM complication: DPNb and DPN with diabetic foot Not specified Find association between DPN and DFUc for gait
Luštrek et al (2014) [36] Focused on DM Not specified Activity recognition of walking, running, cycling, lying, sitting, and standing
Luštrek et al (2015) [37] Focused on DM Not specified Activity recognition of sleeping, home chores, home leisure, eating, and exercising
Cvetković et al (2016) [47] Focused on DM Not specified Activity recognition of working, eating, exercising, and home activities
Calbimonte et al (2017) [38] Focused on DM T1Dd Predict glycemic events
Fraiwan et al (2017) [48] DM complication: diabetic foot Not specified Diagnose development of DFU
McLean et al (2017) [49] Patients with DM used as case study GDe Measure physical proximity, physical activity, and magnetic field strength
Razjouyan et al (2017) [57] DM complication: diabetic foot Not specified Find association between physiological stress response and healing speed among outpatients with active DFU
Reddy et al (2017) [39] Focused on DM T2Df Diagnose individual’s diabetic status
Turksoy et al (2017) [50] Focused on DM T1D Find association between biometric variables and changes in glucose concentration
Bartolic et al (2018) [40] Focused on DM Not specified Measure GLg, insulin dosage, physical activity, daily movement, and sleep duration and quality
Faccioli et al (2018) [45] Focused on DM T1D Find association between glucose prediction models’ performance
Groat et al (2018) [51] Focused on DM T1D Find association between exercise behavior data with the rate of change in GL
McMillan et al (2018) [46] Focused on DM T2D Measure combined GL data, physical activity, and sedentary behavior
Merickel et al (2018) [32] Focused on DM T1D Find association between pattern of glucose and at-risk pattern of vehicle acceleration behavior
Nguyen Gia et al (2019) [41] DM in conjunction with other diseases: DM+cardiovascular disease Not specified Activity recognition of fall detection and remote health monitoring
Rescio et al (2019) [33] DM complication: diabetic foot Not specified Measure temperature and pressure of the plantar foot
Sarda et al (2019) [52] DM in conjunction with other diseases: DM+depression Not specified Find association between smartphone-sensing parameters and symptoms of depression
Ramazi et al (2019) [34] Focused on DM T2D Predict the progression of T2D
Garcia et al (2019) [35] Focused on DM Not specified Diagnose DM from facial images
Sevil et al (2019) [42] DM in conjunction with other diseases: DM+acute psychological stress T1D Find the association between acute psychological stress and the glucose dynamics
Zherebtsov et al (2019) [43] Patients with DM used as case study T2D Measure the changes in the microcirculatory blood flow of healthy patients and patients with T2D
Rodriguez-Rodriguez et al (2019) [53] Focused on DM T1D Predict blood GL for T1D with limited computational and storage capabilities using only CGMh data
Sanz et al (2019) [54] Focused on DM T1D Find the association between different signals provided by 3 different wearables devices and the accuracy of a CGM device during aerobic exercises
Whelan et al (2019) [55] Focused on DM T2D Measure the use, feasibility, and acceptability of behavioral and physiological self-monitoring technologies in individuals at risk of developing T2D

aDM: diabetes mellitus.

bDPN: diabetic peripheral neuropathy.

cDFU: diabetic foot ulcer.

dT1D: type 1 diabetes.

eGD: gestational diabetes.

fT2D: type 2 diabetes.

gGL: glucose level.

hCGM: continuous glucose monitor.