Smartphone Sensors for Health Monitoring and Diagnosis

Abstract

Over the past few decades, we have witnessed a dramatic rise in life expectancy owing to significant advances in medical science and technology, medicine as well as increased awareness about nutrition, education, and environmental and personal hygiene. Consequently, the elderly population in many countries are expected to rise rapidly in the coming years. A rapidly rising elderly demographics is expected to adversely affect the socioeconomic systems of many nations in terms of costs associated with their healthcare and wellbeing. In addition, diseases related to the cardiovascular system, eye, respiratory system, skin and mental health are widespread globally. However, most of these diseases can be avoided and/or properly managed through continuous monitoring. In order to enable continuous health monitoring as well as to serve growing healthcare needs; affordable, non-invasive and easy-to-use healthcare solutions are critical. The ever-increasing penetration of smartphones, coupled with embedded sensors and modern communication technologies, make it an attractive technology for enabling continuous and remote monitoring of an individual's health and wellbeing with negligible additional costs. In this paper, we present a comprehensive review of the state-of-the-art research and developments in smartphone-sensor based healthcare technologies. A discussion on regulatory policies for medical devices and their implications in smartphone-based healthcare systems is presented. Finally, some future research perspectives and concerns regarding smartphone-based healthcare systems are described.

Keywords: mHealth; medical device; regulation; remote healthcare; smartphone; smartphone sensor; telehealth.

Figure 1

Evolution of smartphones and smartphone-embedded sensors over time.

Figure 2

Built-in sensors in a typical present-day smartphone.

Figure 3

Measuring heart rate (a) from a typical trace of a single lead Electrocardiogram (ECG) signal, and (b) using a smartphone camera.

Figure 4

Photoplethysmograph (PPG) signal obtained from the pulsatile flow of blood volume.

Figure 5

Typical spirometric flow curves (a) volume-time curve, and (b) flow-volume curve.

Figure 6

Image of the retinal fundus of a healthy eye; Source: https://pixabay.com/en/eye-fundus-close-1636542/.

Figure 7

Typical arrangement of the optical components for fundus imaging with a smartphone.

Figure 8

Several types of skin diseases (a) Eczema, (b) Psoriasis and (c) two forms of Melanoma.

Figure 9

General architecture of a smartphone-based activity monitoring system.