The release of smart phones equipped with a rich set of sensors has enabled human activity recognition on mobile platforms. Monitoring the daily activities and their levels helps in recognizing the health and wellness of the users as a practical application. Mobile phone’s ubiquity, unobtrusiveness, ease of use, communication channels, and playfulness make mobile phones a suitable platform also for inducing behavior change for a healthier and more active lifestyle. In this paper, we provide a review on the activity recognition systems that use integrated sensors in the mobile phone with a special focus on the systems that target personal health and well-being applications. Initially, we provide background information about the activity recognition process, such as the sensors used, activities targeted, and the steps of activity recognition using machine learning algorithms, before listing the challenges of activity recognition on mobile phones. Next, we focus on the classification of existing work on the topic together with a detailed taxonomy. Finally, we investigate the directions for future research.

A Review and Taxonomy of Activity Recognition on Mobile Phones

Over the past century, in most countries, there has been a continual increase in life expectancy primarily due to improvements in public health, nutrition, personal hygiene and medicine. However, these improvements are now coupled with aging population demographics and falling birth rates, which, when combined, are expected to significantly burden the socioeconomic well-being of many of these countries. In fact, never before in human history have we been confronted with such a large aging population, nor have we developed solid, cost-effective solutions for the well-being, healthcare and social needs of the elderly. One efficient and cost-effective solution to the problem of elderly/patient care is remote healthcare monitoring so they can continue to live at home rather than in nursing homes or hospitals that are very expensive and with limited spaces. These remote monitoring systems will allow medical personnel to keep track of important physiological signs with reduced human resources, at less cost and in real time. This paper introduces several low-cost, noninvasive, user-friendly sensing and actuating systems using information and communication technologies. Such systems can be used to create engineering solutions to some of the pressing healthcare problems in our society, especially as it pertains to the elderly. One example is the integration of sensors, wireless communications, low-power electronics and intelligent computing to determine health-related information using signals from walking patterns. Such a sensing system will be suitable for prolonged use in a home environment. It will be wearable, noninvasive and non-intrusive, similar to smart socks, smart wrist-bands or smart belts. Other examples such as a smart joint monitor and a smart sleeping environment will be discussed, and future perspectives and research challenges in smart home technologies will be described.

Information and communications technologies for elderly ubiquitous healthcare in a smart home

The ubiquity of smartphones and the growth of computing resources, such as connectivity, processing, portability, and power of sensing, have greatly changed people’s lives. Today, many smartphones contain a variety of powerful sensors, including motion, location, network, and direction sensors. Motion or inertial sensors (e.g., accelerometer), specifically, have been widely used to recognize users’ physical activities. This has opened doors for many different and interesting applications in several areas, such as health and transportation. In this perspective, this work provides a comprehensive, state of the art review of the current situation of human activity recognition (HAR) solutions in the context of inertial sensors in smartphones. This article begins by discussing the concepts of human activities along with the complete historical events, focused on smartphones, which shows the evolution of the area in the last two decades. Next, we present a detailed description of the HAR methodology, focusing on the presentation of the steps of HAR solutions in the context of inertial sensors. For each step, we cite the main references that use the best implementation practices suggested by the scientific community. Finally, we present the main results about HAR solutions from the perspective of the inertial sensors embedded in smartphones.

https://www.mdpi.com/1424-8220/19/14/3213/pdf

Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview

Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review.

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature However, their application to older adults can present particular constraints This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future

A Review of Activity Trackers for Senior Citizens: Research Perspectives, Commercial Landscape and the Role of the Insurance Industry.

Numerous laboratory-based studies have been reported on the use of accelerometry for gait and activity analysis particularly among cohorts of elderly subjects. A drawback of such studies is the use of custom hardware platforms worn by subjects. This paper introduces a system solely utilizing accelerometers embedded in off-the-shelf cellular handsets that allow medical professionals and caregivers to remotely monitor the activity characteristics of elderly patients in the home or in the community. The use of ubiquitous cellular handsets makes the system far more acceptable to patients and enables the use of the system to be extended beyond healthcare facilities into the home environment. Mobile handset power consumption issues and other relevant handset and mobile handset application characteristics have been investigated in the context of the deployment of the proposed system.

Accurate monitoring of human physical activity levels for medical diagnosis and monitoring using off-the-shelf cellular handsets

Numerous laboratory based studies have been reported on the use of accelerometry for gait and activity analysis. A drawback of such studies is the use of custom hardware platforms worn by subjects. This paper introduces a system solely utilising accelerometers embedded in off-the-shelf cellular handsets which allow medical professionals and caregivers to remotely monitor the activity characteristics of elderly patients in the home or in the community. The use of ubiquitous cellular handsets makes the system far more acceptable to patients and enables use of the system to be extended beyond primary health-care facilities into the home environment. Mobile handset power consumption issues and other relevant handset characteristics for a variety of different COTS handsets are investigated in the context of deploying this system.

Monitoring of activity levels of the elderly in home and community environments using off the shelf cellular handsets

This paper provides a case study of a service learning based project module which has been integrated into the under-graduate degree programmes delivered by the Electrical & Electronic Engineering discipline within the College of Engineering and Informatics at the National University of Ireland, Galway. Community based service learning has long been promoted as a viable and effective means of improving student engagement by the use of both practical experiences and periods of reflection. In 2008, a pilot project was initiated to examine opportunities to embed service learning into the degree programmes offered by the discipline of Electrical & Electronic Engineering. This has now evolved into a programme which all undergraduate students of the discipline (i.e. completing bachelor programmes in Electronic Engineering and Electronic & Computer Engineering) must complete during the third year of their four year under-graduate degree programme. This module has replaced a traditional group project based module which typically involved project topics related to either course work or the research interests of academic staff. The new service learning based module requires the students to complete a 6 month group project involving community partner organisations who work with clients who have various forms of physical disabilities. A focus group based evaluation of the module involving the various stakeholders in the initiative is presented in the paper. This review highlights the degree to which the module achieves its aim of enhancing the learning outcomes across the complete technical and non-technical skills spectrum.

Eleanor McCarrick

Papers

Accurate monitoring of human physical activity levels for medical diagnosis and monitoring using off-the-shelf cellular handsets

Monitoring of activity levels of the elderly in home and community environments using off the shelf cellular handsets

A Case Study of Enhancing Learning Outcomes for Undergraduate Electronic\Computer Engineering Students through a Service Learning Based Project Module