Design and Implementation of a Low-Cost IoT-Enabled Smartwatch for Monitoring Patient Health

This is the authors' abstract. We don't add key points for this paper.

Continuous monitoring of vital signs is central to preventive healthcare and chronic-disease management, yet commercial smartwatches from manufacturers such as Apple, Fitbit, and Samsung remain prohibitively expensive for most users in developing countries, with prices in Nigeria ranging from roughly ₦340,000 to ₦1,200,000. This creates a significant accessibility gap in personal health technology. This work presents the design, implementation, and validation of a low-cost, Internet of Things (IoT)-enabled smartwatch capable of real-time monitoring of blood oxygen saturation (SpO₂), heart rate, and body temperature. The prototype integrates a MAX30102 pulse-oximetry and heart-rate sensor, a DS18B20 digital temperature sensor, and an ATmega328P microcontroller, together with a DS3231 real-time clock, an HC-06 Bluetooth module, and an SSD1306 OLED display. A three-stage power tree (TP4056 charge controller, MCP1700 low-dropout regulator, and MOSFET-based peripheral load switching) manages the rechargeable lithium-polymer battery. Firmware developed in the Arduino IDE implements peak-detection heart-rate estimation, ratio-of-ratios SpO₂ calculation with local calibration, and a signal-quality gate that withholds unreliable readings rather than reporting them. The device was validated against medical-grade reference instruments (Masimo MightySat, Polar H10, Braun tympanic thermometer) across 1,440 paired SpO₂ and heart-rate samples and 120 paired temperature samples from 20 participants, with usability assessed by 30 additional respondents. The prototype achieved an SpO₂ accuracy of 1.78% ARMS (mean absolute error 1.62%), a combined heart-rate mean absolute error of 2.58 bpm, and a temperature mean absolute error of 0.31 °C, meeting the ISO 80601-2-61 clinical threshold and comparing favourably with flagship consumer devices costing more than ten times as much. Aggressive duty cycling extended battery life from 17.4 h in continuous-monitoring mode to 102 h in power-saving mode. These results demonstrate that careful engineering of commodity components, rather than exotic hardware, is the binding constraint on affordable, clinically credible wearable health monitoring.