JMIR Publications

ABSTRACT

Background:

Health monitoring smarthomes are becoming popular, with some experts arguing that nine-to-five healthcare service delivery might soon become a thing of the past. However, no scoping review has explored the landscape on using smarthomes to promote physical activities required by the aging population to live and function independently.

Objective:

The aim of this review is to systematically map published studies on smarthome technologies aimed to promote physical activities with the intention of unveiling the state of the art and uncovering opportunities for future research.

Methods:

Articles were extracted from six databases (PubMed, CINAHL, Scopus, IEEE Xplore, ACM Library, and Web of Science). The criterion for inclusion was that the articles must be user studies that dealt with smarthome or Active Assisted Living technologies and physical activity, be written in English, and published in a peer-reviewed journals. Three authors independently and collaboratively assessed the eligibility of retrieved studies, extract the relevant data, graphed, and tabularized the findings.

Results:

This review synthesized 20 articles that met the inclusion criteria. Three-quarter of the studies (15/20) were conducted in Western countries, with United States accounting for 25% of them. Sixty percent (12/20) of the reviewed studies were based on a quantitative design, while 15% were based on qualitative or mixed design. Seventy percent (14/20) of the studies were conducted between 2018 and 2020. Activities of daily living were the most studied activities (45%, 9/20), followed by physical activity (30%, 6/20), therapeutic exercise (20%, 4/20) and bodyweight exercise (5%, 1/20). K-Nearest Neighbor and Naïve Bayes Classifier were the most used machine learning algorithms in recognizing physical activities. At least 10% (2/20) of the studies used either algorithm. Ambient and wearable technologies were equally studied (40%, 8/20 each), followed by robots (15%, 3/20). Activity recognition turned out to be the most common goals of the evaluated smarthome technologies, with 55% (11/20) of the studies reporting it, followed by activity monitoring (35%, 7/20). Most of the studies (40%, 8/20) were carried out in a laboratory setting. Moreover, 25% (5/20) and 10% (2/20) were conducted in a home and hospital setting, respectively. Finally, 65% (13/20) had a positive outcome, while 15% (3/20) had a mixed outcome.

Conclusions:

Our results suggest that smarthome technologies, especially digital personal assistants, coaches, and robots are effective in promoting physical activities. They hold bright prospects in assisting and aiding the older population to age in place and function independently, especially in Western countries where there are shortages of long-term care workers and most of the smarthome technologies and studies are concentrated. However, there is a need to conduct more studies (including cross-cultural and country studies, and randomized control trials) on the effectiveness and acceptance of smarthome technologies, especially among underrepresented populations in Africa and South America.