The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults - a multicentric cross-sectional study.

BACKGROUND: The decline in everyday life physical activity reflects and contributes to the frailty syndrome. While especially self-reported frailty assessments have the advantage of reaching large groups at low costs, little is known about the relationship between the self-report and objective measured daily physical activity behavior. The main objective was to evaluate whether and to what extent a self-reported assessment of frailty is associated with daily physical activity patterns. METHODS: Daily activity data were obtained from 88 elderly participants (mean 80.6 ± 9.1 years) over up to 21 days. Acceleration data were collected via smartwatch. According to the results of a self-report frailty questionnaire, participants were retrospectively split up into three groups, F (frail, n = 43), P (pre-frail, n = 33), and R (robust, n = 12). Gait- and activity-related measures were derived from the built-in step detector and acceleration sensor and comprised, i.a., standard deviation of 5-s-mean amplitude deviation (MADstd), median MAD (MADmedian), and the 95th percentile of cadence (STEP95). Parameters were fed into a PCA and component scores were used to derive behavioral clusters. RESULTS: The PCA suggested two components, one describing gait and one upper limb activity. Mainly gait related parameters showed meaningful associations with the self-reported frailty score (STEP95: R2 = 0.25), while measures of upper limb activity had lower coefficients (MADmedian: R2 = 0.07). Cluster analysis revealed two clusters with low and relatively high activity in both dimensions (cluster 2 and 3). Interestingly, a third cluster (cluster 1) was characterized by high activity and low extent of ambulation. Comparisons between the clusters showed significant differences between activity, gait, age, sex, number of chronic diseases, health status, and walking aid. Particularly, cluster 1 contained a higher number of female participants, whose self-reports tended towards a low health status, the frequent use of a walking aid, and a higher score related to frailty questions. CONCLUSIONS: The results demonstrate that subjective frailty assessments may be a simple first screening approach. However, especially older women using walking aids may classify themselves as frail despite still being active. Therefore, the results of self-reports may be particularly biased in older women.

Step Detection and Parameterization for Gait Assessment Using a Single Waist-Worn Accelerometer.

One of the major reasons why the elderly lose their ability to live independently at home is the decline in gait performance. A measure to assess gait performance using accelerometers is step counting. The main problem with most step detection algorithms is the loss of accuracy at low speeds ( 0.8 m/s) which limits their use in frail elderly populations. In this paper, a step detection algorithm was developed and validated using data from 10 healthy adults and 21 institutionalized seniors, predominantly frail older adults. Data were recorded using a single waist-worn triaxial accelerometer as each of the subjects performed one 10-m-walk trial. The algorithm demonstrated high mean sensitivity (99 ± 1%) for gait speeds between 0.2-1.5 m/s. False positives were evaluated with a series of motion activities performed by one subject. These activities simulate acceleration patterns similar to those generated near the body's center of mass while walking in terms of amplitude signal and periodicity. Cycling was the activity which led to a higher number of false positives. By applying template matching, we reduced by 73% the number of false positives in the cycling activity and eliminated all false positives in the rest of activities. Using K-means clustering, we obtained two different characteristic step patterns, one for normal and one for frail walking, where particular gait events related to limb impacts and muscle flexions were recognized. The proposed system can help to identify seniors at high risk of functional decline and monitor the progress of patients undergoing exercise therapy interventions.

Progressive adaptation in physical activity and neuromuscular performance during 520d confinement.

To understand whether prolonged confinement results in reductions in physical activity and adaptation in the musculoskeletal system, six subjects were measured during 520 d isolation in the Mars500 study. We tested the hypothesis that physical activity reduces in prolonged confinement and that this would be associated with decrements of neuromuscular performance. Physical activity, as measured by average acceleration of the body's center of mass ("activity temperature") using the actibelt® device, decreased progressively over the course of isolation (p<0.00001). Concurrently, countermovement jump power and single-leg hop force decreased during isolation (p<0.001) whilst grip force did not change (p≥0.14). Similar to other models of inactivity, greater decrements of neuromuscular performance occurred in the lower-limb than in the upper-limb. Subject motivational state increased non-significantly (p = 0.20) during isolation, suggesting reductions in lower-limb neuromuscular performance were unrelated to motivation. Overall, we conclude that prolonged confinement is a form of physical inactivity and is associated with adaptation in the neuromuscular system.

A new method to estimate the real upper limit of the false alarm rate in a 3 accelerometry-based fall detector for the elderly.

Falls are a major concern for the elderly and their ability to remain healthy. Fall detection systems may notify emergency responders when no one apart from the injured is present. However, their real-world application is limited by a number of factors such as high false positive rates, low-compliance, poor-usability and short battery lifetime. In order to improve these aspects we have developed a miniaturized 3D accelerometer integrated in a belt buckle, the actibelt(®), and a fall detection algorithm. We have used a new evaluation method to assess the upper limit of the false alarm rate of our algorithm using a large set of long term standardized acceleration measurements recorded under real life conditions. Our algorithm has a false alarm rate of seventeen false alarms per month and has the potential to be reduced down to at most three false alarms per month when activities which require the sensor to be removed are eliminated. In laboratory settings, the algorithm has a sensitivity of 100%. The algorithm was sucessfully validated using data from a real-world fall.

Accuracy of the actibelt(®) accelerometer for measuring walking speed in a controlled environment among persons with multiple sclerosis.

BACKGROUND: Advances in portable sensor technology have opened an era for objective, real-life monitoring of walking speed in persons with multiple sclerosis (MS). PURPOSE: The present study examined the accuracy of the actibelt(®) accelerometer for measuring walking speed during a standard 6-min walk (6MW) and the possibility that disability status influenced the degree of accuracy among persons with MS. METHODS: On a single testing session, 51 persons with MS and Expanded Disability Status Scale scores between 2.0 and 6.5 performed a 6MW while wearing an actibelt(®) in the body's sagittal symmetry plane and close to the body's centre of mass. RESULTS: All 51 participants completed the 6MW without stopping, falling, or any adverse events, and the actibelt(®) provided walking speed data for each of the participants. The actibelt(®) significantly overestimated walking speed (actual minus actibelt(®)) by a mean±standard deviation of -0.12±0.17 m/s for the overall sample (p<0.0001). There was no significant overestimation in the sample with mild disability (-0.02±0.11 m/s), but there was in the samples with moderate (-0.10±0.16 m/s) and severe (-0.26±0.12 m/s) disability. CONCLUSION: The actibelt(®) is ready for real-life monitoring of walking speed in persons with mild MS, but caution is necessary when interpreting the accuracy of the walking speed data for those with MS who have moderate and severe disability.