OBJECTIVES: The Internet of Things (IoT) and its applications are growing simultaneously. These applications need new intelligent devices along heterogeneous networking. Which makes them costly to implement indeed. Platforms and open devices designed for open-source hardware are possible solutions. This research was conducted under an IoT design, implementation, and assessment model for the remote monitoring of pulse oximetry via oxygen partial saturation (SpO2) and heart rate (HR) with low-energy consumption. METHODS: This study focused on the development of SpO2 and HR measurements that will allow the monitoring and estimation in real time of the user's state and health related to the established parameters. Measurements were acquired and recorded using a remote web server that recorded the acquired variables for further processing. The statistical analysis data allows comparison of the registered data measured with theoretical models. RESULTS: The IoT model was developed use Bluetooth low-energy devices, which comply with low-cost and open-hardware solutions operated via ‘HTTP requests’ for data transmission and reception from a cloud server to an edge device. Network performance assessment was conducted to guarantee the availability and integrity of the acquired values and signals. The system measured SpO2 and HR variables. The most significant result was to achieve energy consumption 20% lower than that of devices in the market. CONCLUSIONS: In summary, the acquired data validation based on the IoT model had a transmission error of 0.001% which proves its applicability in healthcare.
Delivery of Health Care ; Heart Rate ; Internet ; Models, Theoretical ; Monitoring, Physiologic ; Oximetry ; Oxygen ; Remote Sensing Technology

OBJECTIVES: Due to the uncontrolled increase of the mobile health applications and their scarce use by elderly for reason of absence credibility of measurements by lack scientific support, the aim of this study was to evaluate the differences between the biophysical measurements based on standard instrument against a mobile application using controlled experiments with elderly to propose an effective validation model of the developed apps. METHODS: The subjects of the study (50 people) were elderly people who wanted to check their weight and cardiac status. For this purpose, two mobile applications were used to measure energy expenditure based on physical activity (Activ) and heart rate (SMCa) during controlled walking at specific speeds. Minute-by-minute measurements were recorded to evaluate the average error and the accuracy of the data acquired through confidence intervals by means of statistical analysis of the data. RESULTS: The experimental results obtained by the Activ/SMCa apps showed a consistent statistical similarity with those obtained by specialized equipment with confidence intervals of 95%. All the subjects were advised and trained on the use of the applications, and the initial registration of data to characterize them served to significantly affect the perceived ease of use. CONCLUSIONS: This is the first model to validate a health-app with elderly people allowed to demonstrate the anthropometric and body movement differences of subjects with equal body mass index (BMI) but younger. Future studies should consider not only BMI data but also other variables, such as age and usability perception factors.
Aged* ; Body Mass Index ; Energy Metabolism ; Heart Rate ; Humans ; Mobile Applications ; Motor Activity ; Telemedicine ; Walking