Background Diabetes mellitus is a metabolic disorder that affects hundreds of millions of people worldwide and causes several million deaths every year. Such a dramatic scenario puts some pressure on administrations, care services, and the scientific community to seek novel solutions that may help control and deal effectively with this condition and its consequences. Objective This study aims to review the literature on the use of modern mobile and wearable technology for monitoring parameters that condition the development or evolution of diabetes mellitus. Methods A systematic review of articles published between January 2010 and July 2020 was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Manuscripts were identified through searching the databases Web of Science, Scopus, and PubMed as well as through hand searching. Manuscripts were included if they involved the measurement of diabetes-related parameters such as blood glucose level, performed physical activity, or feet condition via wearable or mobile devices. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Results The search yielded 1981 articles. A total of 26 publications met the eligibility criteria and were included in the review. Studies predominantly used wearable devices to monitor diabetes-related parameters. The accelerometer was by far the most used sensor, followed by the glucose monitor and heart rate monitor. Most studies applied some type of processing to the collected data, mainly consisting of statistical analysis or machine learning for activity recognition, finding associations among health outcomes, and diagnosing conditions related to diabetes. Few studies have focused on type 2 diabetes, even when this is the most prevalent type and the only preventable one. None of the studies focused on common diabetes complications. Clinical trials were fairly limited or nonexistent in most of the studies, with a common lack of detail about cohorts and case selection, comparability, and outcomes. Explicit endorsement by ethics committees or review boards was missing in most studies. Privacy or security issues were seldom addressed, and even if they were addressed, they were addressed at a rather insufficient level. Conclusions The use of mobile and wearable devices for the monitoring of diabetes-related parameters shows early promise. Its development can benefit patients with diabetes, health care professionals, and researchers. However, this field is still in its early stages. Future work must pay special attention to privacy and security issues, the use of new emerging sensor technologies, the combination of mobile and clinical data, and the development of validated clinical trials.

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BACKGROUND Diabetes mellitus is a metabolic disorder suffered by hundreds of millions of people worldwide and causing several million deaths every year. Such a dramatic scenario puts quite some pressure on administrations, care services and the scientific community to seek novel solutions that may help controlling and dealing effectively with this condition and its consequences. OBJECTIVE This study is aimed at reviewing the literature on the use of modern mobile and wearable technology for monitoring parameters that condition the development and/or evolution of diabetes mellitus. METHODS A systematic review of articles published between January 2010 and July 2020 was performed following PRISMA guidelines. Manuscripts indexed in Web of Science and SCOPUS databases were included if they involved the measurement of diabetes-related parameters, such as blood glucose level, performed physical activity or feet condition, via wearable or mobile devices. RESULTS The search yielded 1587 articles. Altogether, 26 publications met the eligibility criteria and were included in the review. Studies used predominantly wearable devices for monitoring diabetes-related parameters. The accelerometer was by far the most used sensor, followed by the glucose monitor and the heart rate monitor. Most studies applied some kind of processing to the collected data mainly consisting of statistical analysis or machine learning for activity recognition, finding associations among health outcomes, and diagnosing conditions related to diabetes. Privacy or security issues were seldom addressed, and if so, at a rather insufficient level. CONCLUSIONS The use of mobile and wearable devices for the monitoring of diabetes-related parameters shows early promise. Its development can benefit diabetes patients, healthcare professionals and researchers. To evolve this area future research must pay special attention to privacy and security issues, the use of new emerging sensor technologies, and the combination of mobile and clinical data for a holistic and seamless understanding of the patient's health state.