Smartphone Applications for Patients' Health and Fitness

Higgins, Julian P T

doi:10.1016/j.amjmed.2015.05.038

Cited by 325 publications

(218 citation statements)

References 34 publications

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“…Cellnovo has developed an insulin pump approved for use in the United Kingdom and France that incorporates a 3-axis accelerometer capable of monitoring physical activity. 52,56 With the computational power enabling both integration of data and high-level analysis now available in smartphones, there has been great interest in using these as an intelligent hub 57,58 for the integration of physiological signals in CLC. [59][60][61][62][63][64] Furthermore, cloud-based data systems enable the health care team to access and analyze CGM, CSII, and CLC data.…”

Section: Future Technologies Patient Factors and Prospects For Futumentioning

confidence: 99%

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Dadlani

Levine

McCrady-Spitzer

et al. 2015

J Diabetes Sci Technol

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Type 1 diabetes (T1D) is characterized by complete or near complete absence of endogenous insulin secretion resulting in the need to deliver exogenous insulin in an individualized, precise manner.1 Current clinically approved technologies to replace insulin result in unacceptable risk for hypoglycemia, hyperglycemia, and glycemic variability (GV).2 Changes in plasma glucose concentration are more pronounced in T1D, occur rapidly and are related to food intake, physical activity and imprecise insulin delivery. The maturation of technologies such as continuous glucose monitoring (CGM), continuous subcutaneous insulin infusion (CSII) or insulin pump, rapid acting insulin analogs and closed-loop control (CLC) algorithms that deliver insulin based on CGM data processing has resulted in CLC therapy becoming an area of active research with rapid therapeutic translation to clinical practice. 4 Current CLC studies show significant improvement in hypoglycemia and a bigger burden of hyperglycemia relative to time spent in hypoglycemic range. 4,5 Occurrence of hyper and hypoglycemia with current CLC, the burden associated with current CLC and limitations of eligible populations to use current technologies indicate the need for further innovation. Important variables in this context with potentially significant effect sizes are physical activity and meals. Significant efforts have been made to model the aforementioned parameters and understand their effect on glucose-insulin dynamics by incorporating/adapting them into CLC simulators. 6,7 Even though the day to day effect of physical activity on glucose status poses major challenges for T1D, limited research in this area has been conducted. 8 Since obesity and type 2 diabetes mellitus (T2D), 2 major disorders of whole body energy balance, continue to rise worldwide, most research to-date regarding physical activity capture device use has been pursued in these 2 disorders.9,10 T2D is characterized by hyperglycemia for a significant proportion of the day with the majority of such subjects having limited hypoglycemia AbstractPhysical activity is an important determinant of glucose variability in type 1 diabetes (T1D). It has been incorporated as a nonglucose input into closed-loop control (CLC) protocols for T1D during the last 4 years mainly by 3 research groups in single center based controlled clinical trials involving a maximum of 18 subjects in any 1 study. Although physical activity data capture may have clinical benefit in patients with T1D by impacting cardiovascular fitness and optimal body weight achievement and maintenance, limited number of such studies have been conducted to date. Clinical trial registries provide information about a single small sample size 2 center prospective study incorporating physical activity data input to modulate closed-loop control in T1D that are seeking to build on prior studies. We expect an increase in such studies especially since the NIH has expanded support of this type of research with additional grants starting in the second hal...

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Section: Future Technologies Patient Factors and Prospects For Futumentioning

confidence: 99%

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Dadlani

Levine

McCrady-Spitzer

et al. 2015

J Diabetes Sci Technol

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“…An apps inventory by Higgins 11 and Knight et al, 12 found a typical fitness App to be more effective when behaviour change techniques are incorporated, though very few of the apps included this element in the design. Social networking, pairing with health device and additional health parameters were some of the common technological features.…”

Section: Physical Activitymentioning

confidence: 99%

Potential of Mobile Applications in Prevention and Management of Cardio-Metabolic Diseases

Ramadas¹,

Fatt²

2017

Public Health Open J

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Citation, with limitation to 'reviews', English publications and the last 5 years. Databases searched include OVID MEDLINE, PUBMED, COCHRANE, CINAHL, SCOPUS and PROQUEST. The shortlisted reviews including meta-analysis, narrative and systematic reviews were qualitatively evaluated and findings were compared. Results: Twenty-six articles (n=26) comprised of apps inventory, narrative and systematic reviews were included in the following areas: nutrition (n=3), physical activity (n=4), tobacco smoking (n=1) and cardiovascular (n=1), type 2 diabetes (n=8) and obesity/weight loss (n=9). Conclusion: Although there is limited evidence, we can now see a shift towards development and investigation of existing and new apps in prevention and management of cardio-metabolic diseases. Future studies could explore the feasibility and long-term effectiveness of theorysupported apps that were developed with newest evidence.

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“…With such monitors and trackers, behavioural changes that improve eating habits and physical activity levels have been observed in young adults. Thus such monitoring apps do encourage patients to be more aware of their daily condition (Higgins 2015).…”

Section: Patient Data Management [Table 2]mentioning

confidence: 99%

An overview of clinically and healthcare related apps in Google and Apple app stores: connecting patients, drugs, and clinicians

Gan

Koshy

Nguyen

et al. 2016

Sci Phone Appl Mob Devices

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Successful clinical outcomes involve both clinician and patient factors such as good decision making, accurate diagnosis, patient compliance, effective monitoring of the condition, and accurate interpretation of clinical results. With a general trend in healthcare towards personalized medicine, the smartphone holds great potential to play a role in personalized care and aid in the above mentioned factors. Through the use of apps, the increasingly powerful smartphone may be a useful aid in the healthcare and clinical industries. This review surveys the currently available apps in Google and Apple app stores that are purposed for aiding healthcare and clinical use, and discusses how they may also help transform the smartphone in a medically relevant device.

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Smartphone Applications for Patients' Health and Fitness

Cited by 325 publications

References 34 publications

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Potential of Mobile Applications in Prevention and Management of Cardio-Metabolic Diseases

An overview of clinically and healthcare related apps in Google and Apple app stores: connecting patients, drugs, and clinicians

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