Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care.
Tiago M Fernández-CaramésIván Froiz-MíguezOscar Blanco-NovoaPaula Fraga-LamasPublished in: Sensors (Basel, Switzerland) (2019)
Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.
Keyphrases
- blood glucose
- glycemic control
- public health
- type diabetes
- end stage renal disease
- healthcare
- newly diagnosed
- cardiovascular disease
- ejection fraction
- electronic health record
- prognostic factors
- chronic kidney disease
- health information
- peritoneal dialysis
- squamous cell carcinoma
- heart failure
- big data
- adipose tissue
- mental health
- risk assessment
- primary care
- patient reported outcomes
- social media
- palliative care
- atrial fibrillation
- patient reported
- rectal cancer
- neoadjuvant chemotherapy
- machine learning
- sentinel lymph node