The incidence and prevalence of various rheumatic diseases, such as rheumatoid arthritis, systemic lupus erythematosus, are increasing. Moreover, the etiology and risk factors for the progression of many chronic pain conditions are still unknown. Previous studies have shown an association between symptoms of rheumatic diseases and external factors such as diet, stress, quality of sleep, weather changes, smoking, alcohol use, and exercise.
However, real-time monitoring of rheumatic diseases patients in their natural surroundings, outside of the clinic’s boundaries is typically absent.
To address this unmet need, the RheumaticMonitor research focuses on detecting patterns from big data that will predict exacerbations or remissions of the disease and response to treatment. This research study includes the use of a smart bracelet and an app that works on mobile devices using the Xiomi mi-fit app to collect long-term information from patients with rheumatological conditions
About the RheumaticMonitor Mobile Device Application
The application presents users with a preliminary (baseline) questionnaire at registration, and with a daily questionnaire that the patient fills out, optimally, every day.
The initial questionnaire includes socio-demographic questions (age, sex, etc.) as well as questions about daily life such as symptoms, pain characteristics, sleep, quality of life, and smoking, nutrition, medication, and exercise. The daily questionnaire includes questions about daily patterns of these characteristics.
For patients recruited via Hadassah hospital, the collected information is based on data from the mobile device and from sensors in the smart (Xiaomi mi-fit) bracelet, which patients receive upon joining the study and wear for at least three months. The data collected from the bracelet include number of steps, walking distance, heart rate, sleep quality, and GPS.
We anticipate that the results of the study will contribute to a better, evidence-based understanding of the effect of behaviors on rheumatic diseases, by providing new insights regarding the prediction of short-term pain episodes and long-term systemic complications. This will eventually improve personalized management of patients with rheumatic diseases, and help the global effort in reducing the burden of rheumatic diseases.
RehumaticMonitor is composed of the following components:
a. Client web- this is a web page allows the researcher to insert new patients, watch data of all patients, and download an excel file of the relevant data.
b. Client iPhone mobile –iPhone app for the patient including Fitness bracelet.
c. Client Android mobile –android app for patient including Fitness bracelet.
a. REST API – APIs for mobile and web page:
c. Web-based dashboard for the researcher
Figure 1 describes the high-level architecture of the RehumaticMonitor system:
The Electronic Medical Records (EMR)
For Professional collaborators
In addition to the data collected from the application, RheumaticMonitor also analyzes patient data from the Hadassah Electronic Medical Record (EMR), in order to find predictive patterns for Rheumatic diseases disease course
Professional collaborations from industrial and academic institutions are welcomed.