Classification of Frailty among Community Dwelling Older Adults Using Parameters of Physical Activity Obtained Independently and Unsupervised

The global population is ageing at an unprecedented rate, with the percentage of those aged over 65 years expected to double and those aged over 80 years expected to treble by the year 2050. With ageing comes biological and physiological changes that affect functional capacity. Frailty is a potentially avoidable, reversible biopsychosocial condition associated with biological but not chronological age, affecting a quarter of all community-dwelling older adults. Frailty results in disability, increased dependency and institutionalisation. Screening for frailty could help reduce its prevalence and mitigate the adverse outcomes however, traditional screening tools are time-consuming to perform, require clinician input and by their subjective nature are flawed. The use of wearable sensors has been proposed as a means of screening for frailty and parameters of mobility and physical activity have been identified as being associated with frailty. The goal of this thesis was to examine if community-dwelling older adults could capture parameters of mobility and physical activity independently in their own home and if these parameters could discriminate between frail and non-frail status. This work provides evidence that a single parameter of mobility and physical activity obtained from a single body-worn sensor correlates with frailty. It also provides evidence that community-dwelling older adults can independently capture parameters of mobility and physical activity, unsupervised in their own home using a consumer-grade wearable device, and that these data can predict pre-frailty and frailty with acceptable accuracy. Thresholds for parameters of physical activity predictive of frailty have been identified. The results of this thesis will guide future work to focus community-dwelling older adults on the importance of frailty screening and guide the development of a user-friendly device or sensor system suitable for use by older adults for continuous data collection relevant to frailty

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