Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.

BackgroundWearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a human-computer interface designed for interactive training.MethodsSenior living community residents (mean age 84.6) with confirmed fall risk were randomized to an intervention (IG, n = 17) or control group (CG, n = 16). The IG underwent 4 weeks (twice a week) of balance training including weight shifting and virtual obstacle crossing tasks with visual/auditory real-time joint movement feedback using wearable sensors. The CG received no intervention. Outcome measures included changes in center of mass (CoM) sway, ankle and hip joint sway measured during eyes open (EO) and eyes closed (EC) balance test at baseline and post-intervention. Ankle-hip postural coordination was quantified by a reciprocal compensatory index (RCI). Physical performance was quantified by the Alternate-Step-Test (AST), Timed-up-and-go (TUG), and gait assessment. User experience was measured by a standardized questionnaire.ResultsAfter the intervention sway of CoM, hip, and ankle were reduced in the IG compared to the CG during both EO and EC condition (p = .007-.042). Improvement was obtained for AST (p = .037), TUG (p = .024), fast gait speed (p = . 010), but not normal gait speed (p = .264). Effect sizes were moderate for all outcomes. RCI did not change significantly. Users expressed a positive training experience including fun, safety, and helpfulness of sensor-feedback.ConclusionsResults of this proof-of-concept study suggest that older adults at risk of falling can benefit from the balance training program. Study findings may help to inform future exercise interventions integrating wearable sensors for guided game-based training in home- and community environments. Future studies should evaluate the added value of the proposed sensor-based training paradigm compared to traditional balance training programs and commercial exergames.Trial registrationhttp://www.clinicaltrials.govNCT02043834.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-164) contains supplementary material, which is available to authorized users.

Background: New technologies for gait assessment are emerging and have provided new avenues for accurately measuring gait characteristics in home and clinic. However, potential meaningful clinical gait parameters beyond speed have received little attention in frailty research. Objective: To study gait characteristics in different frailty status groups for identifying the most useful parameters and assessment protocols for frailty diagnosis. Methods: We searched PubMed, Embase, PsycINFO, CINAHL, Web of Science, Cochrane Library, and Age Line. Articles were selected according to the following criteria: (1) population: individuals defined as frail, prefrail, or transitioning to frail, and (2) outcome measures: quantitative gait variables as obtained by biomechanical analysis. Effect sizes (d) were calculated for the ability of parameters to discriminate between different frailty status groups. Results: Eleven publications met inclusion criteria. Frailty definitions, gait protocols and parameters were inconsistent, which made comparison of outcomes difficult. Effect sizes were calculated only for the three studies which compared at least two different frailty status groups. Gait speed shows the highest effect size to discriminate between frailty subgroups, in particular during habitual walking (d = 0.76-6.17). Gait variability also discriminates between different frailty status groups in particular during fast walking. Prominent parameters related to prefrailty are reduced cadence (d = 1.43) and increased step width variability (d = 0.64), whereas frailty (vs. prefrail status) is characterized by reduced step length during habitual walking (d = 1.32) and increased double support during fast walking (d = 0.78). Interestingly, one study suggested that dual-task walking speed can be used to predict prospective frailty development. Conclusion: Gait characteristics in people with frailty are insufficiently analyzed in the literature and represent a major area for innovation. Despite the paucity of work, current results suggest that parameters beyond speed could be helpful in identifying different categories of frailty. Increased gait variability might reflect a multisystem reduction and may be useful in identifying frailty. In addition, a demanding task such as fast walking or adding a cognitive distractor might enhance the sensitivity and specificity of frailty risk prediction and classification, and is recommended for frailty assessment using gait analysis.

The suggested innovative upper extremity frailty assessment method integrates low-cost sensors, and the physical assessment is easily performed in less than 1 minute. The uniqueness of the proposed technology is its applicability in older nonambulatory individuals, such as those in emergency settings. Further improvement is warrant to make it suitable for routine clinical applications.

Advances in wearable technology allow for the objective assessment of motor performance in both in-home and in-clinic environments and were used to explore motor impairments in Parkinson’s disease (PD). The aims of this study were to: 1) assess differences between in-clinic and in-home gait speed, and sit-to-stand and stand-to-sit duration in PD patients (in comparison with healthy controls); and 2) determine the objective physical activity measures, including gait, postural balance, instrumented Timed-up-and-go (iTUG), and in-home spontaneous physical activity (SPA), with the highest correlation with subjective/semi-objective measures, including health survey, fall history (fallers vs. non-fallers), fear of falling, pain, Unified Parkinson's Disease Rating Scale, and PD stage (Hoehn and Yahr). Objective assessments of motor performance were made by measuring physical activities in the same sample of PD patients (n = 15, Age: 71.2±6.3 years) and age-matched healthy controls (n = 35, Age: 71.9±3.8 years). The association between in-clinic and in-home parameters, and between objective parameters and subjective/semi-objective evaluations in the PD group was assessed using linear regression-analysis of variance models and reported as Pearson correlations (R). Both in-home SPA and in-clinic assessments demonstrated strong discriminatory power in detecting impaired motor function in PD. However, mean effect size (0.94±0.37) for in-home measures was smaller compared to in-clinic assessments (1.30±0.34) for parameters that were significantly different between PD and healthy groups. No significant correlation was observed between identical in-clinic and in-home parameters in the PD group (R = 0.10–0.25; p>0.40), while the healthy showed stronger correlation in gait speed, sit-to-stand duration, and stand-to-sit duration (R = 0.36–0.56; p<0.03). This suggests a better correlation between supervised and unsupervised motor function assessments in healthy controls compared to PD group. In the PD group, parameters related to velocity and range-of-motion of lower extremity within gait assessment (R = 0.58–0.84), and turning duration and velocity within iTUG test (R = 0.62–0.77) demonstrated strong correlations with PD stage (p<0.01).

Abstract-Some individuals with mild cognitive impairment (MCI) experience not only cognitive deficits but also a decline in motor function, including postural balance. This pilot study sought to estimate the feasibility, user experience, and effects of a novel sensor-based balance training program. Patients with amnestic MCI (mean age 78.2 yr) were randomized to an intervention group (IG, n = 12) or control group (CG, n = 10). The IG underwent balance training (4 wk, twice a week) that included weight shifting and virtual obstacle crossing. Real-time visual/ audio lower-limb motion feedback was provided from wearable sensors. The CG received no training. User experience was measured by a questionnaire. Postintervention effects on balance (center of mass sway during standing with eyes open [EO] and eyes closed), gait (speed, variability), cognition, and fear of falling were measured. Eleven participants (92%) completed the training and expressed fun, safety, and helpfulness of sensor feedback. Sway (EO, p = 0.04) and fear of falling (p = 0.02) were reduced in the IG compared to the CG. Changes in other measures were nonsignificant. Results suggest that the sensorbased training paradigm is well accepted in the target population and beneficial for improving postural control. Future studies should evaluate the added value of the sensor-based training compared to traditional training. Clinical Trial Registration: ClinicalTrials.gov; "Virtual reality based balance training in people with mild cognitive impairment": NCT02214342; https://clinicaltrials.gov/ct2/ show/NCT02214342?term=NCT02214342&rank=1

Our new single triaxial accelerometer algorithm successfully tracked postural transition, allowing accurate identification of those at high risk of falling, and could be useful for intermittent or even continuous monitoring of older adults with diabetes. Other potential applications could include activity monitoring of the diabetes population with lower extremity disease and of patients undergoing surgical procedures or as an objective measure during rehabilitation.

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