Abstract
This study analyzes the technologies used in dealing with frailty within the following areas: prevention, care, diagnosis and treatment. The aim of this paper is, on the one hand, to analyze the extent to which technology is present in terms of its relationship with frailty and what technological resources are used to treat it. Its other purpose is to define new challenges and contributions made by physiotherapy using technology. Eighty documents related to research, validation and/or the ascertaining of different types of hardware, software or both were reviewed in prominent areas. The authors used the following scales: in the area of diagnosis, Fried’s phenotype model of frailty and a model based on trials for the design of devices. The technologies developed that are based on these models accounted for 55% and 45% of cases respectively. In the area of prevention, the results proved similar regarding the use of wireless sensors with cameras (35.71%), and Kinect™ sensors (28.57%) to analyze movements and postures that indicate a risk of falling. In the area of care, results were found referring to the use of different motion, physiological and environmental wireless sensors (46,15%), i.e. so-called smart homes. In the area of treatment, the results show with a percentage of 37.5% that the Nintendo® Wii™ console is the most used tool for treating frailty in elderly persons. Further work needs to be carried out to reduce the gap existing between technology, frail elderly persons, healthcare professionals and carers to bring together the different views about technology. This need raises the challenge of developing and implementing technology in physiotherapy via serious games that may via play and connectivity help to improve the functional capacity, general health and quality of life of frail individuals.
Highlights
According to the World Health Organization (WHO), it is estimated that there are more than 605 million people over 60 years of age in the world
The authors concluded by stating that the absolute sum of the wavelet coefficients of the details corresponding to orientation signals and acceleration were associated with the frailty syndrome
Preventing risky situations and preventing falls in elderly persons is of the utmost importance so as to in turn prevent any increase in their degree of frailty and ensure they remain independent for as long as possible. With this aim in mind, we found devices in most of the studies reviewed – wireless sensors of different types that determine the risk of falling in elderly persons according to the data recorded and compared to normal behavioural patterns
Summary
According to the World Health Organization (WHO), it is estimated that there are more than 605 million people over 60 years of age in the world. Spain is currently one of the countries in the world with the highest life expectancy after Japan, but when one speaks of life expectancy in terms of good health, the situation worsens in relation to other countries such as France, Sweden, Australia and Japan. For this reason, it is important to highlight the fact that living longer is not always a synonym for good quality of life and health [2]. The frailty in elderly persons has witnessed exponential growth in research and clinical practice in recent years [5], with there being consensus about the definition of frailty as a deregulated (potentially correctable or improvable) situation in many biological systems, accumulation of deficits, a reduction in physiological reserve and proneness to a range of adverse events [6,7]
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