How wearable sensors have been utilised to evaluate frailty in older adults: a systematic review

Abstract

Background Globally the population of older adults is increasing. It is estimated that by 2050 the number of adults over the age of 60 will represent over 21% of the world’s population. Frailty is a clinical condition associated with ageing resulting in an increase in adverse outcomes. It is considered the greatest challenge facing an ageing population affecting an estimated 16% of community-dwelling populations worldwide. Aim The aim of this systematic review is to explore how wearable sensors have been used to assess frailty in older adults. Method Electronic databases Medline, Science Direct, Scopus, and CINAHL were systematically searched March 2020 and November 2020. A search constraint of articles published in English, between January 2010 and November 2020 was applied. Papers included were primary observational studies involving; older adults aged > 60 years, used a wearable sensor to provide quantitative measurements of physical activity (PA) or mobility and a measure of frailty. Studies were excluded if they used non-wearable sensors for outcome measurement or outlined an algorithm or application development exclusively. The methodological quality of the selected studies was assessed using the Appraisal Tool for Cross-sectional Studies (AXIS). Results Twenty-nine studies examining the use of wearable sensors to assess and discriminate between stages of frailty in older adults were included. Thirteen different body-worn sensors were used in eight different body-locations. Participants were community-dwelling older adults. Studies were performed in home, laboratory or hospital settings. Postural transitions, number of steps, percentage of time in PA and intensity of PA together were the most frequently measured parameters followed closely by gait speed. All but one study demonstrated an association between PA and level of frailty. All reports of gait speed indicate correlation with frailty. Conclusions Wearable sensors have been successfully used to evaluate frailty in older adults. Further research is needed to identify a feasible, user-friendly device and body-location that can be used to identify signs of pre-frailty in community-dwelling older adults. This would facilitate early identification and targeted intervention to reduce the burden of frailty in an ageing population.

Diurnal effects of polypharmacy with high drug burden index on physical activities over 23 h differ with age and sex

“…These findings also highlighted the importance of considering the time of day in experiments measuring functional outcomes. Our continuous monitoring platforms are comparable to the wearable devices currently being developed/trialed in clinical studies, which may be more beneficial than short physical tests in identifying positive/negative effects of different interventions on physical function over long periods of time 15 . We have also selected clinically relevant polypharmacy regimens and physical measures that can be translated to comparable outcomes in humans.…”

“…Recent research suggests that continuous monitoring of daily physical activities over longer periods using wearable sensor technology could detect more complex physical changes than traditional methods 14 . Older adults, in particular, could benefit from this 15 , because there are multiple age-related changes in circadian rhythm, leading to several altered body rhythmic characteristics including activity levels 16 , which could be identified with prolonged/continuous observations 17 . These circadian disruptions could also alter drug responses in aging 18 .…”

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

“…However, the growing demand for the light, portable, and wireless measurement tools necessary for conducting field evaluations, as well as the development of portable smart devices, has led to the development of wearable untethered sensors and measurement tools [ 22 , 23 ]. Nowadays, technology innovations in sensor hardware fabrication along with advancements in signal processing and sensor fusion techniques have improved the measurement techniques for bio-signals that describe an individual’s gait biomechanics [ 24 , 25 , 26 , 27 , 28 , 29 ]. Like many other intelligent wearable devices, PAEs have significantly benefitted from such advancements.…”

Detecting Fall Risk and Frailty in Elders with Inertial Motion Sensors: A Survey of Significant Gait Parameters

“…Frailty is closely related to fall risk, so reviews that focused on fall risk in older people are also included in this table. Some reviews studied a large number of technologies [ 10 , 11 , 12 , 13 , 14 , 15 ], whereas [ 16 , 17 , 18 ] focused on the use of inertial sensors. These studies supported the use of gait analysis systems for the evaluation of frailty or fall risk in elderly patients; some of them identified a few gait parameters related to frailty status or fall risk, as the stride length, the double support time, the reduction of some parameters (cadence, gait velocity), or the gait variability, as well as the sensor locations, the lower trunk being the most common body location among the studies.…”

“…We detected some limitations in these reviews with respect to our goal. Most of them did not include studies with frail patients [ 8 , 9 , 11 , 12 , 16 , 17 , 19 , 20 ], and those focused on frailty did not emphasize the use of inertial sensors or, specifically, the significance of gait parameters to identify which are the most relevant gait parameters related to frailty [ 10 , 13 , 21 ]. For these reason and to give a response to this problem, in this work, we carried out a review of the state-of-the-art that highlights the significance of gait parameters that others studies have already quantified using inertial sensors and present them in an integrated way, so that an engineer can use it as a guide to design a gait analysis tool with IMUs by estimating in advance the most promising parameters from inertial measurements to identify the frailty status and fall risk.…”