Emer P. Doheny

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.

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.

Frailty status can be accurately assessed using inertial sensors and the TUG test

BACKGROUND frailty is an important geriatric syndrome linked to increased mortality, morbidity and falls risk. METHODS a total of 399 community-dwelling older adults were assessed using Frieds frailty phenotype and the timed up and go (TUG) test. Tests were quantified using shank-mounted inertial sensors. We report a regression-based method for assessment of frailty using inertial sensor data obtained during TUG. For comparison, frailty was also assessed using the same method based on grip strength and manual TUG time. RESULTS using inertial sensor data, participants were classified as frail or non-frail with mean accuracy of 75.20% (stratified by gender). Using TUG time alone, frailty status was classified correctly with mean classification accuracy of 71.82%. Similarly, using grip strength alone, the frailty status was classified correctly with mean classification accuracy of 77.65%. Stratifying sensor data by gender yielded significantly (p<0.05) increased accuracy in classifying frailty when compared with equivalent manual TUG time-based models. CONCLUSION results suggest that a simple protocol involving assessment using a well-known mobility test (Timed Up and Go (TUG)) and inertial sensors can be a fast and effective means of automatic, non-expert assessment of frailty.

SHIMMER™: An extensible platform for physiological signal capture

Wireless sensor networks have become increasingly common in everyday applications due to decreasing technology costs and improved product performance, robustness and extensibility. Wearable physiological monitoring systems have been utilized in a variety of studies, particularly those investigating ECG or EMG during human movement or sleep monitoring. These systems require extensive validation to ensure accurate and repeatable functionality. Here we validate the physiological signals (EMG, ECG and GSR) of the SHIMMER (Sensing Health with Intelligence, Modularity, Mobility and Experimental Reusability) against known commercial systems. Signals recorded by the SHIMMER EMG, ECG and GSR daughter-boards were found to compare well to those obtained by commercial systems.

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.

A single gyroscope method for spatial gait analysis

Inertial sensors have become increasingly popular in gait analysis, due to their highly portable, low cost, and potentially wireless nature. However, accurate spatial gait analysis using few sensors remains a challenge. A gyroscope-based algorithm for spatial gait analysis is presented. This novel algorithm (SGA) uses data from a single gyroscope attached to each shank. The performance of the SGA was compared to that of an electronic walkway, GAITRite®. The two systems compared favorably, with a mean error in stride length of 0.09 ± 0.07 m, and a mean error in stride velocity of 0.11 ± 0.10 m/s. The error between the SGA and GAITRite was also similar to that reported by previous inertial sensor based algorithms. The relationship between stride length and stride velocity, as well as that of subject height and stride length was also examined. This new method provides an inexpensive, portable system for spatial or spatio-temporal gait analysis, which has potential for use in any location.

Effect of subcutaneous fat thickness and surface electrode configuration during neuromuscular electrical stimulation

The effect of subcutaneous fat thickness, electrode size and inter-electrode distance on the minimum stimulus current necessary for fiber excitation was examined in an attempt to improve the efficacy of neuromuscular electrical stimulation (NMES) in obese populations. A three-dimensional finite element model of the human thigh was developed and used to calculate the potential along a myelinated nerve fiber due to NMES. The activating function was used to examine alterations in the excitation of the fiber due to fat thickness, electrode size and inter-electrode distance. The finite element model was coupled to a neural model to examine the stimulus current required for action potential propagation. The stimulus current required to evoke 10% of the maximum M-wave amplitude was measured experimentally. Both experimental and modeling studies indicated that the stimulus current required to reach the threshold for muscle activation increased with fat thickness, electrode size, and inter-electrode distance. However, as fat thickness increased, the threshold for muscle activation became less sensitive to inter-electrode distance and electrode size. These results suggest that by using larger electrodes above regions of high subcutaneous fat thickness, the efficacy of NMES could be maintained while reducing the current density at the skin and the associated subject discomfort.

A standing posture is associated with increased susceptibility to the sound-induced flash illusion in fall-prone older adults

Recent research has provided evidence suggesting a link between inefficient processing of multisensory information and incidence of falling in older adults. Specifically, Setti et al. (Exp Brain Res 209:375–384, 2011) reported that older adults with a history of falling were more susceptible than their healthy, age-matched counterparts to the sound-induced flash illusion. Here, we investigated whether balance control in fall-prone older adults was directly associated with multisensory integration by testing susceptibility to the illusion under two postural conditions: sitting and standing. Whilst standing, fall-prone older adults had a greater body sway than the age-matched healthy older adults and their body sway increased when presented with the audio–visual illusory but not the audio–visual congruent conditions. We also found an increase in susceptibility to the sound-induced flash illusion during standing relative to sitting for fall-prone older adults only. Importantly, no performance differences were found across groups in either the unisensory or non-illusory multisensory conditions across the two postures. These results suggest an important link between multisensory integration and balance control in older adults and have important implications for understanding why some older adults are prone to falling.

Reduced vision selectively impairs spatial updating in fall-prone older adults

The current study examined the role of vision in spatial updating and its potential contribution to an increased risk of falls in older adults. Spatial updating was assessed using a path integration task in fall-prone and healthy older adults. Specifically, participants conducted a triangle completion task in which they were guided along two sides of a triangular route and were then required to return, unguided, to the starting point. During the task, participants could either clearly view their surroundings (full vision) or visuo-spatial information was reduced by means of translucent goggles (reduced vision). Path integration performance was measured by calculating the distance and angular deviation from the participants return point relative to the starting point. Gait parameters for the unguided walk were also recorded. We found equivalent performance across groups on all measures in the full vision condition. In contrast, in the reduced vision condition, where participants had to rely on interoceptive cues to spatially update their position, fall-prone older adults made significantly larger distance errors relative to healthy older adults. However, there were no other performance differences between fall-prone and healthy older adults. These findings suggest that fall-prone older adults, compared to healthy older adults, have greater difficulty in reweighting other sensory cues for spatial updating when visual information is unreliable.