Low-Cost Versatile Remote Healthcare Monitoring of Bedridden Patients

Abstract

In underdeveloped countries, the implementation of remote monitoring of bedridden patients out of hospitals presents challenges due to the need for more infrastructure and the high hardware cost required for remote monitoring. Healthcare 4.0 can provide new technologies to aid caregivers of bedridden patients in making timely decisions using sensors, embedded systems, wireless networks, and mobile and cloud computing technologies. The main objective is to integrate low-cost and software components for sensor data acquisition and storage into a functional system to monitor the physiological parameters of bedridden patients. This chapter involves the design and implementation of electronic circuits and sensors for the acquisition of physiological parameters (blood pressure, blood oxygen, galvanic resistance, heart rate, respiratory rate, and body temperature of the patient), which, integrated with various mobile applications, allow the transmission and storage in the cloud of such data, through which a remote caregiver monitoring a bedridden patient to detect anomalies and take appropriate actions. The proposed system includes a Remote Vital Signs Monitoring Embedded System (ReViSMoES), composed of a microcontroller receiving information from the physiological data sensors; a dedicated app (ReViSiAApp) hosted on a smartphone near the ReViSMoES, which manages the remote connectivity with a cloud server, where the sensor data obtained from the ReViSMoES are stored; finally, the caregiver uses the Remote Vital Signals Monitoring Application (ReViSiMoApp), hosted on his smartphone located in a different neighbor, city, or state where the bedridden patient is, getting reports from one or more patients to give feedback to the clinician. We obtained battery consumption measurements for the application that concentrates the data from the sensors and sends them to a cloud module, applying various profiles. We compared the heart-rate acquisition module performance against leading smartphone applications. It is possible to build a low-cost system that integrates sensors to monitor multiple physiological parameters and allows a caregiver to have patient data for decision-making.