Clodagh Cunningham

Evaluation of Falls Risk in Community-Dwelling Older Adults Using Body-Worn Sensors

Background: Falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. This study aimed to determine if a method based on body-worn sensor data can prospectively predict falls in community-dwelling older adults, and to compare its falls prediction performance to two standard methods on the same data set. Methods: Data were acquired using body-worn sensors, mounted on the left and right shanks, from 226 community-dwelling older adults (mean age 71.5 ± 6.7 years, 164 female) to quantify gait and lower limb movement while performing the ‘Timed Up and Go’ (TUG) test in a geriatric research clinic. Participants were contacted by telephone 2 years following their initial assessment to determine if they had fallen. These outcome data were used to create statistical models to predict falls. Results: Results obtained through cross-validation yielded a mean classification accuracy of 79.69% (mean 95% CI: 77.09–82.34) in prospectively identifying participants that fell during the follow-up period. Results were significantly (p < 0.0001) more accurate than those obtained for falls risk estimation using two standard measures of falls risk (manually timed TUG and the Berg balance score, which yielded mean classification accuracies of 59.43% (95% CI: 58.07–60.84) and 64.30% (95% CI: 62.56–66.09), respectively). Conclusion: Results suggest that the quantification of movement during the TUG test using body-worn sensors could lead to a robust method for assessing future falls risk.

Frailty, depression, and anxiety in later life.

BACKGROUND Anxiety and depression are common in older people but are often missed; to improve detection we must focus on those elderly people at risk. Frailty is a geriatric syndrome inferring increased risk of poor outcomes. Our objective was to explore the relationship between frailty and clinically significant anxiety and depression in later life. METHODS This study had a cross-sectional design and involved the assessment of 567 community-dwelling people aged ≥ 60 years recruited from the Technology Research for Independent Living (TRIL) Clinic, Dublin. Frailty was measured using the Fried biological syndrome model; depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale; and anxiety symptoms measured using the Hospital Anxiety and Depression Scale. RESULTS Higher depression and anxiety scores were identified in both pre-frail and frail groups compared to robust elders (three-way factorial ANOVA, p ≤ 0.0001). In a logistic regression model the odds ratio for frailty showed a significantly higher likelihood of clinically meaningful depressive and anxiety symptoms even controlling for age, gender and a history of depression or anxiety requiring pharmacotherapy (OR = 4.3; 95% CI 1.5, 11.9; p = 0.005; OR = 4.36; 95% CI 1.4, 13.8; p = 0.013 respectively). CONCLUSIONS Our findings suggest that even at the earliest stage of pre-frailty, there is an association with increased symptoms of emotional distress; once frailty develops there is a higher likelihood of clinically significant depression and anxiety. Frailty may be relevant in identifying older people at risk of deteriorating mental health.

Falls classification using tri-axial accelerometers during the five-times-sit-to-stand test

The five-times-sit-to-stand test (FTSS) is an established assessment of lower limb strength, balance dysfunction and falls risk. Clinically, the time taken to complete the task is recorded with longer times indicating increased falls risk. Quantifying the movement using tri-axial accelerometers may provide a more objective and potentially more accurate falls risk estimate. 39 older adults, 19 with a history of falls, performed four repetitions of the FTSS in their homes. A tri-axial accelerometer was attached to the lateral thigh and used to identify each sit-stand-sit phase and sit-stand and stand-sit transitions. A second tri-axial accelerometer, attached to the sternum, captured torso acceleration. The mean and variation of the root-mean-squared amplitude, jerk and spectral edge frequency of the acceleration during each section of the assessment were examined. The test-retest reliability of each feature was examined using intra-class correlation analysis, ICC(2,k). A model was developed to classify participants according to falls status. Only features with ICC>0.7 were considered during feature selection. Sequential forward feature selection within leave-one-out cross-validation resulted in a model including four reliable accelerometer-derived features, providing 74.4% classification accuracy, 80.0% specificity and 68.7% sensitivity. An alternative model using FTSS time alone resulted in significantly reduced classification performance. Results suggest that the described methodology could provide a robust and accurate falls risk assessment.

Displacement of centre of mass during quiet standing assessed using accelerometry in older fallers and non-fallers

Postural sway during quiet standing is associated with falls risk in older adults. The aim of this study was to investigate the utility of a range of accelerometer-derived parameters of centre of mass (COM) displacement in identifying older adults at risk of falling. A series of instrumented standing balance trials were performed to investigate postural control in a group of older adults, categorised as fallers or non-fallers. During each trial, participants were asked to stand as still as possible under two conditions: comfortable stance (six repetitions) and semi-tandem stance (three repetitions). A tri-axial accelerometer was secured to the lower back during the trials. Accelerometer data were twice integrated to estimate COM displacement during the trials, with numerical techniques used to reduce integration error. Anterior-posterior (AP) and medial-lateral (ML) sway range, sway length and sway velocity were examined, along with root mean squared (RMS) acceleration. All derived parameters significantly discriminated fallers from non-fallers during both comfortable and semi-tandem stance. Results indicate that these accelerometer-based estimates of COM displacement may improve the discriminative power of quiet standing falls risk assessments, with potential for use in unsupervised balance assessment.

An instrumented sit-to-stand test used to examine differences between older fallers and non-fallers

An instrumented version of the five-times-sit-to-stand test was performed in the homes of a group of older adults, categorised as fallers or non-fallers. Tri-axial accelerometers were secured to the sternum and anterior thigh of each participant during the assessment. Accelerometer data were then used to examine the timing of the movement, as well as the root mean squared amplitude, jerk and spectral edge frequency of the mediolateral (ML) acceleration during the total assessment, each sit-stand-sit component and each postural transition (sit-stand and stand-sit). Differences between fallers and non-fallers were examined for each parameter. Six parameters significantly discriminated between fallers and non-fallers: sit-stand time, ML acceleration for the total assessment, and the ML spectral edge frequency for the complete assessment, individual sit-stand-sit components, as well as sit-stand and stand-sit transitions. These results suggest that each of these derived parameters would provide improved discrimination of fallers from non-fallers, for the cohort examined, than the standard clinical measure — the total time to complete the assessment. These results indicate that accelerometry may enhance the utility of the five-times-sit-to-stand test when assessing falls risk.

Diurnal variations in the outcomes of instrumented gait and quiet standing balance assessments and their association with falls history

One in three adults aged over 65 falls every year, resulting in enormous costs to society. Incidents of falling vary with time of day, peaking in the early morning. The aim of this study was to determine if the ability of instrumented gait and balance assessments to discriminate between participants based on their falls history varies diurnally. Body-worn sensors were used during a 3 m gait assessment and a series of quiet standing balance tests. Each assessment was performed four times during a single day under supervised conditions in the participants homes. 40 adults aged over 60 years (19 fallers) participated in this study. A range of parameters were derived for each assessment, and the ability of each parameter to discriminate between fallers and non-fallers at each recording time was examined. The effect of falls history on single support time varied significantly with recording time, with a significantly reduced single support time observed at the first and last recording session of the day. Differences were observed between fallers and non-fallers for a range of other gait parameters; however, these effects did not vary with assessment time. The quiet standing assessments examined in this study revealed significant variations with falls history; however, the sensitivity of the examined quiet standing assessments to falls risk does not appear to be time dependent. These results indicate that, with the exception of single support time, the association of gait and quiet standing balance parameters with falls risk does not vary diurnally.

Quantitative falls risk estimation through multi-sensor assessment of standing balance

Falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. Measures of postural stability have been associated with the incidence of falls in older adults. The aim of this study was to develop a model that accurately classifies fallers and non-fallers using novel multi-sensor quantitative balance metrics that can be easily deployed into a home or clinic setting. We compared the classification accuracy of our model with an established method for falls risk assessment, the Berg balance scale. Data were acquired using two sensor modalities--a pressure sensitive platform sensor and a body-worn inertial sensor, mounted on the lower back--from 120 community dwelling older adults (65 with a history of falls, 55 without, mean age 73.7 ± 5.8 years, 63 female) while performing a number of standing balance tasks in a geriatric research clinic. Results obtained using a support vector machine yielded a mean classification accuracy of 71.52% (95% CI: 68.82-74.28) in classifying falls history, obtained using one model classifying all data points. Considering male and female participant data separately yielded classification accuracies of 72.80% (95% CI: 68.85-77.17) and 73.33% (95% CI: 69.88-76.81) respectively, leading to a mean classification accuracy of 73.07% in identifying participants with a history of falls. Results compare favourably to those obtained using the Berg balance scale (mean classification accuracy: 59.42% (95% CI: 56.96-61.88)). Results from the present study could lead to a robust method for assessing falls risk in both supervised and unsupervised environments.

Depression: a modifiable factor in fearful older fallers transitioning to frailty?

Fear of falling is one of the most common fears among community‐dwelling older people and is as serious a health problem as falls themselves. Understanding fear of falling in fallers transitioning to frailty may help us identify effective strategies to reduce it in this already vulnerable group of older people. Our aim was to evaluate the psychological factors associated with fear of falling in a group of fallers transitioning to frailty when compared with robust or non‐frail fallers.

Taking balance measurement out of the laboratory and into the home: Discriminatory capability of novel centre of pressure measurement in fallers and non-fallers

We investigated three methods for estimating centre of pressure excursions, as measured using a portable pressure sensor matrix, in order to deploy similar technology into the homes of older adults for longitudinal monitoring of postural control and falls risk. We explored the utility of these three methods as markers of falls risk in a cohort of 120 community dwelling older adults with and without a history of falls (65 fallers, 55 non-fallers). A number of standard quantitative balance parameters were derived using each centre of pressure estimation method. Rank sum tests were used to test for significant differences between fallers and non-fallers while intra-class correlation coefficients were also calculated to determine the reliability of each method. A method based on estimating the changes in the magnitude of pressure exerted on the pressure sensor matrix was found to be the most reliable and discriminative. Our future work will implement this method for home-based balance measurement.

Clinical gait assessment of older adults using open platform tools

Gait impairment is associated with increased falls risk. The gait of 321 community dwelling elderly adults was assessed using the TRIL Gait Analysis Platform (GAP), which was specially designed for ease of use in a research clinic setting by non-experts. The GAP featured body-worn kinematic sensors, a pressure sensitive electronic walkway, and two orthogonally mounted web cameras, and was developed using open platform tools. This flexible platform was applied to objectively measure gait parameters in different gait assessments. The results from the 6 meter walk assessment are presented here. In this assessment, participants were categorized by clinical falls history as ‘fallers’ or ‘non-fallers’. Temporal and spatial gait parameters were examined. Significant differences in spatial parameters were observed when fallers and non-fallers were compared. Temporal parameters were found to differ, though not significantly.