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Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.
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CONTEXT: Long-term adherence to physical activity (PA) interventions is challenging. The Lifestyle-integrated Functional Exercise programmes were adapted Lifestyle-integrated Functional Exercise (aLiFE) to include more challenging activities and a behavioural change framework, and then enhanced Lifestyle-integrated Functional Exercise (eLiFE) to be delivered using smartphones and smartwatches. OBJECTIVES: To (1) compare adherence measures, (2) identify determinants of adherence and (3) assess the impact on outcome measures of a lifestyle-integrated programme. DESIGN, SETTING AND PARTICIPANTS: A multicentre, feasibility randomised controlled trial including participants aged 61-70 years conducted in three European cities. INTERVENTIONS: Six-month trainer-supported aLiFE or eLiFE compared with a control group, which received written PA advice. OUTCOME MEASURES: Self-reporting adherence per month using a single question and after 6-month intervention using the Exercise Adherence Rating Scale (EARS, score range 6-24). Treatment outcomes included function and disability scores (measured using the Late-Life Function and Disability Index) and sensor-derived physical behaviour complexity measure. Determinants of adherence (EARS score) were identified using linear multivariate analysis. Linear regression estimated the association of adherence on treatment outcome. RESULTS: We included 120 participants randomised to the intervention groups (aLiFE/eLiFE) (66.3±2.3 years, 53% women). The 106 participants reassessed after 6 months had a mean EARS score of 16.0±5.1. Better adherence was associated with lower number of medications taken, lower depression and lower risk of functional decline. We estimated adherence to significantly increase basic lower extremity function by 1.3 points (p<0.0001), advanced lower extremity function by 1.0 point (p<0.0001) and behavioural complexity by 0.008 per 1.0 point higher EARS score (F(3,91)=3.55, p=0.017) regardless of group allocation. CONCLUSION: PA adherence was associated with better lower extremity function and physical behavioural complexity. Barriers to adherence should be addressed preintervention to enhance intervention efficacy. Further research is needed to unravel the impact of behaviour change techniques embedded into technology-delivered activity interventions on adherence. TRIAL REGISTRATION NUMBER: NCT03065088.
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Exercício Físico , Estilo de Vida , Idoso , Terapia Comportamental , Análise Custo-Benefício , Feminino , Humanos , Masculino , Qualidade de Vida , Resultado do TratamentoRESUMO
BACKGROUND: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. METHODS/DESIGN: The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson's Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. DISCUSSION: The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. TRIAL REGISTRATION: ISRCTN12051706.
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Fragilidade , Doença de Parkinson , Doença Pulmonar Obstrutiva Crônica , Humanos , Monitorização Fisiológica , Estudos Observacionais como Assunto , Modalidades de FisioterapiaRESUMO
OBJECTIVE: To examine sensitivity to change and responsiveness of the Community Balance and Mobility Scale (CBM) and shortened CBM (s-CBM). DESIGN: Secondary analysis using data of a randomized controlled trial. SETTING: General community. PARTICIPANTS: Young community-dwelling seniors aged 61-70 years (N=134; mean age, 66.2±2.5y). INTERVENTIONS: Participants underwent 12 months of exercise intervention. MAIN OUTCOME MEASURES: CBM and s-CBM. Sensitivity to change was assessed using standardized response mean (SRM) and paired t tests as appropriate. Responsiveness was assessed using 2 minimal important difference (MID) estimates. Analyses were conducted for the full sample and for the subgroups "high-balance" and "low-balance," divided by median split. RESULTS: Inferential statistics revealed a significant CBM (P<.001) and s-CBM (P<.001) improvement within the full sample and the subgroups (high-balance: P=.001, P=.019; low-balance: P<.001, P<.001). CBM and s-CBM were moderately sensitive to change (SRM, 0.48 vs 0.38) within the full sample. In the high-balance subgroup, moderate SRM values (0.70) were found for the CBM and small values for the s-CBM (0.29). In the low-balance subgroup, moderate SRM values were found for the CBM (0.67) and high values for the s-CBM (0.80). For the full sample, CBM and s-CBM exceeded the lower but not the higher MID value. In the high-balance subgroup, the CBM exceeded both MID values, but the s-CBM exceeded only the lower. In the low-balance subgroup, CBM and s-CBM exceeded both MID values. CONCLUSIONS: The CBM is a suitable tool to detect intervention-related changes of balance and mobility in young, high-performing seniors. Both versions of the CBM scale show good sensitivity to change and responsiveness, particularly in young seniors with low balance.
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Avaliação Geriátrica/métodos , Modalidades de Fisioterapia/normas , Equilíbrio Postural/fisiologia , Fatores Etários , Idoso , Humanos , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Fatores Sexuais , Fatores SocioeconômicosRESUMO
The present article investigates the influence of center-of-mass movements on the variation of the structure in human postural sway. Twelve healthy younger persons performed 60s quiet standing, 60s relaxed standing, and 10 min relaxed standing on two force plates. Center-of-pressure (CoP) and gravitational line (GL) profiles were calculated from the ground reaction forces and moments. The temporal variation of CoP structure was calculated by the local scaling exponent h(t) and a Monte Carlo surrogate test was used to identify phase couplings between temporal scales. The range of variation of h(t) was significantly larger in relaxed standing compared to quiet standing (p<0.00001) and highly correlated with the range of GL movements (r>0.76, p<0.001). However, the variation in h(t) was not generated by the GL movements because the CoP-GL traces was close to identical variation in h(t) (r>0.95, p<0.00001). The Monte Carlo surrogate test indicated the presence of intermittent phase couplings between the temporal scales of both CoP traces and the CoP-GL residuals in the periods with GL movements. The present results suggest that human posture is controlled by intermittent phase coupling of the CoP and GL movements. Furthermore, the investigation of the variation in CoP structure might extend existing theories of changes in postural control for example older persons and patients with a neurodegenerative disease.