An IoT-Based Non-Invasive Glucose Level Monitoring System Using Raspberry Pi

Abstract

Patients diagnosed with diabetes mellitus must monitor their blood glucose levels in order to control the glycaemia. Consequently, they must perform a capillary test at least three times per day and, besides that, a laboratory test once or twice per month. These standard methods pose difficulty for patients since they need to prick their finger in order to determine the glucose concentration, yielding discomfort and distress. In this paper, an Internet of Things (IoT)-based framework for non-invasive blood glucose monitoring is described. The system is based on Raspberry Pi Zero (RPi) energised with a power bank, using a visible laser beam and a Raspberry Pi Camera, all implemented in a glove. Data for the non-invasive monitoring is acquired by the RPi Zero taking a set of pictures of the user fingertip and computing their histograms. Generated data is processed by an artificial neural network (ANN) implemented on a Flask microservice using the Tensorflow libraries. In this paper, all measurements were performed in vivo and the obtained data was validated against laboratory blood tests by means of the mean absolute error (10.37%) and Clarke grid error (90.32% in zone A). Estimated glucose values can be harvested by an end device such as a smartphone for monitoring purposes.

IoT-Based Applications in Healthcare Devices

“…Alarcón-Paredes et al have designed a glove for the measurement of blood glucose level that is integrated with a Raspberry Pi camera and a visible laser beam. A set of pictures taken from the fingertip was used for detecting the diabetic condition of the patients [ 82 ]. In another study [ 83 ], an algorithm based on a double moving average was employed in the IoT architecture for the measurement of the glucose level.…”

The Internet of Things in Geriatric Healthcare

“…e glucose level reading was then sent to a mobile phone where the recorded data could be accessed through a mobile application. In another research [64], a smart device was developed, which used a single-chip computer (Raspberry Pi), a power bank, a visible laser beam, and a Pi camera, all integrated into a hand glove. e glove provides the body glucose level information.…”

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

“…In the case of wireless technologies, limitations persist for both personal use and short-range technologies, especially when they are handled by older persons. The importance of IoT technologies has been proven in recent studies, for example, in [25], authors developed an architecture based on a Raspberry Pi, and they analyzed the sensor's accuracy and the effectiveness of the transmission. Another example, in [26] proposed a glucose data classification to validate the architecture using data classification techniques for a correct diagnosis bythe prediction system.…”

“…Because the server is local, no delay is present, as in [26], where SMS messages are used. Contrary to [25], we do not use proprietary applications in order to obtain a more economical system with multiple connections (patients). We validated the operation of the architecture, the prognosis algorithm, and the sending of alerts for two conditions, normal (a patient with intake) and critical.…”