Sensors and Functionalities of Non-Invasive Wrist-Wearable Devices: A Review

Abstract

Wearable devices have recently received considerable interest due to their great promise for a plethora of applications. Increased research efforts are oriented towards a non-invasive monitoring of human health as well as activity parameters. A wide range of wearable sensors are being developed for real-time non-invasive monitoring. This paper provides a comprehensive review of sensors used in wrist-wearable devices, methods used for the visualization of parameters measured as well as methods used for intelligent analysis of data obtained from wrist-wearable devices. In line with this, the main features of commercial wrist-wearable devices are presented. As a result of this review, a taxonomy of sensors, functionalities, and methods used in non-invasive wrist-wearable devices was assembled.

Keywords: intelligent analysis; non-invasive; sensor; taxonomy; visualization; wrist-wearable device.

Figure 1

The taxonomy of functionalities of wrist-wearable devices with three levels. Our paper focuses on wrist-wearable devices with Level 3 functionalities of intelligent output.

Figure 2

Trajectory plot (full map) of a short mountain bike ride that was completed in Maribor (Slovenia). The data were recorded by a Garmin Vivo Active HR watch that allows one to measure one’s heart rate directly on the wrist.

Figure 3

Figure presents visualized graphs of the three main parameters of workout (Figure 2), i.e., elevation, speed, and heart rate according to time.

Figure 4

Visualization of running activity on the Movescount platform.

Figure 5

Figure shows the main basic parameters of sport training. The main basic parameters that are part of every cycling training are: total duration, total distance, temperature, average speed, altitude, power-meter values and average heart rate. Note: The Figure is reproduced with permission from [123].