Constanze Lenoble-Hoskovec

Predictors of Functional Recovery in Patients Admitted to Geriatric Postacute Rehabilitation

OBJECTIVE To examine characteristics associated with functional recovery in older patients undergoing postacute rehabilitation. DESIGN Observational study. SETTING Postacute rehabilitation facility. PARTICIPANTS Patients (N=2754) aged ≥65 years admitted over a 4-year period. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURE Functional status was assessed at admission and again at discharge. Functional recovery was defined as achieving at least 30% improvement on the Barthel Index score from admission compared with the maximum possible room for improvement. RESULTS Patients who achieved functional recovery (70.3%) were younger and were more likely to be women, live alone, and be without any formal home care before admission, and they had fewer chronic diseases (all P<.01). They also had better cognitive status and a higher Barthel Index score both at admission (mean ± SD, 63.3±18.0 vs 59.6±24.7) and at discharge (mean ± SD, 86.8±10.4 vs 62.2±22.9) (all P<.001). In multivariate analysis, patients <75 years of age (adjusted odds ratio [OR]=1.51; 95% confidence interval [CI], 1.16-1.98; P=.003), women (adjusted OR=1.24; 95% CI, 1.01-1.52; P=.045), patients living alone (adjusted OR=1.61; 95% CI, 1.31-1.98; P<.001), and patients without in-home help prior to admission (adjusted OR=1.39; 95% CI, 1.15-1.69; P=.001) remained at increased odds of functional recovery. In addition, compared with those with moderate-to-severe cognitive impairment (Mini-Mental State Examination score <18), patients with mild-to-moderate impairment (Mini-Mental State Examination score 19-23) and those cognitively intact also had increased odds of functional recovery (adjusted OR=1.56; 95% CI, 1.13-2.15; P=.007; adjusted OR=2.21; 95% CI, 1.67-2.93; P<.001, respectively). CONCLUSIONS Apart from sociodemographic characteristics, cognition is the strongest factor that identifies older patients more likely to improve during postacute rehabilitation. Further study needs to determine how to best adapt rehabilitation processes to better meet the specific needs of this population and optimize their outcome.

Instrumented shoes for activity classification in the elderly

Quantifying daily physical activity in older adults can provide relevant monitoring and diagnostic information about risk of fall and frailty. In this study, we introduce instrumented shoes capable of recording movement and foot loading data unobtrusively throughout the day. Recorded data were used to devise an activity classification algorithm. Ten elderly persons wore the instrumented shoe system consisting of insoles inside the shoes and inertial measurement units on the shoes, and performed a series of activities of daily life as part of a semi-structured protocol. We hypothesized that foot loading, orientation, and elevation can be used to classify postural transitions, locomotion, and walking type. Additional sensors worn at the right thigh and the trunk were used as reference, along with an event marker. An activity classification algorithm was built based on a decision tree that incorporates rules inspired from movement biomechanics. The algorithm revealed excellent performance with respect to the reference system with an overall accuracy of 97% across all activities. The algorithm was also capable of recognizing all postural transitions and locomotion periods with elevation changes. Furthermore, the algorithm proved to be robust against small changes of tuning parameters. This instrumented shoe system is suitable for daily activity monitoring in elderly persons and can additionally provide gait parameters, which, combined with activity parameters, can supply useful clinical information regarding the mobility of elderly persons.

Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes.

Activity level and gait parameters during daily life are important indicators for clinicians because they can provide critical insights into modifications of mobility and function over time. Wearable activity monitoring has been gaining momentum in daily life health assessment. Consequently, this study seeks to validate an algorithm for the classification of daily life activities and to provide a detailed gait analysis in older adults. A system consisting of an inertial sensor combined with a pressure sensing insole has been developed. Using an algorithm that we previously validated during a semi structured protocol, activities in 10 healthy elderly participants were recorded and compared to a wearable reference system over a 4 h recording period at home. Detailed gait parameters were calculated from inertial sensors. Dynamics of physical behavior were characterized using barcodes that express the measure of behavioral complexity. Activity classification based on the algorithm led to a 93% accuracy in classifying basic activities of daily life, i.e., sitting, standing, and walking. Gait analysis emphasizes the importance of metrics such as foot clearance in daily life assessment. Results also underline that measures of physical behavior and gait performance are complementary, especially since gait parameters were not correlated to complexity. Participants gave positive feedback regarding the use of the instrumented shoes. These results extend previous observations in showing the concurrent validity of the instrumented shoes compared to a body-worn reference system for daily-life physical behavior monitoring in older adults.

Gait analysis using shoe-worn inertial sensors: how is foot clearance related to walking speed?

Spatiotemporal gait analysis with body worn inertial sensors improves diagnosis in clinical practice. Most of the gait performance measures are affected by walking speed. However, it has not been investigated that how much information foot clearance parameters share with the key parameters of gait performance domains. Using shoe-worn inertial sensors and previously validated algorithm we measured spatiotemporal as well as clearance gait parameters in a cohort of able-bodied adults over the age of 65 (N=879). Principal components analysis showed that variability of foot clearance parameters contribute to the main variability in gait data. Moreover, only weak to moderate correlation of gait speed and stride length with some clearance parameters has been observed. We recommend the assessment of clearance parameters during gait analysis in addition to parameters such as gait speed, bearing in mind the importance of foot clearance measures in obstacle negotiation, slipping and tripping related falls.

Concern about Falling and Complexity of Free-Living Physical Activity Patterns in Well-Functioning Older Adults

Background: Fall-related psychological concerns are common among older adults, potentially contributing to functional decline as well as to restriction of activities and social participation. To effectively prevent such negative consequences, it is important to understand how even very low concern about falling could affect physical activity behavior in everyday life. We hypothesized that concern about falling is associated with a reduction in diversity, dynamics, and performance of daily activities, and that these features can be comprehensively quantified in terms of complexity of physical activity patterns. Methods: A sample of 40 community-dwelling older adults were assessed for concern about falling using the Falls Efficacy Scale-International (FES-I). Free-living physical activity was assessed using a set of metrics derived from data recorded with a chest-worn tri-axial accelerometer. The devised metrics characterized physical activity behavior in terms of endurance (total locomotion time, longest locomotion period, usual walking cadence), performance (cadence of longest locomotion period, locomotion periods with at least 30 steps and 100 steps/min), and complexity of physical activity patterns. Complexity was quantified according to variations in type, intensity, and duration of activities, and was considered as an adaptive response to environmental exigencies over the course of the day. Results: Based on FES-I score, participants were classified into two groups: not concerned at all/fully confident (n = 25) and concerned/less confident (n = 15). Demographic and health-related variables did not differ significantly between groups. Comparison of physical activity behavior indicated no significant differences for endurance-related metrics. In contrast, performance and complexity metrics were significantly lower in the less confident group compared to the fully confident group. Among all metrics, complexity of physical activity patterns appeared as the most discriminative feature between fully confident and less confident participants (p = 0.001, non-parametric Cliff’s delta effect size = 0.63). Conclusions: These results extend our understanding of the interplay between low concern about falling and physical activity behavior of community-dwelling older persons in their everyday life context. This information could serve to better design and evaluate personalized intervention programs in future prospective studies.

Instrumented Shoes for Real-Time Activity Monitoring Applications

Activity monitoring in daily life is gaining momentum as a health assessment tool, especially in older adults and at-risk populations. Several research-based and commercial systems have been proposed with varying performances in classification accuracy. Configurations with many sensors are generally accurate but cumbersome, whereas single sensors tend to have lower accuracies. To this end, we propose an instrumented shoes system capable of accurate activity classification and gait analysis that contains sensors located entirely at the level of the shoes. One challenge in daily activity monitoring is providing punctual and subject-tailored feedback to improve mobility. Therefore, the instrumented shoe system was equipped with a Bluetooth® module to transmit data to a smartphone and perform detailed activity profiling of the monitored subjects. The potential applications of such a system are numerous in mobility and fall risk-assessment as well as in fall prevention.