17 research outputs found

    Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk

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    Asymmetry is a cardinal symptom of gait post-stroke that is targeted during rehabilitation. Technological developments have allowed accelerometers to be a feasible tool to provide digital gait variables. Many acceleration-derived variables are proposed to measure gait asymmetry. Despite a need for accurate calculation, no consensus exists for what is the most valid and reliable variable. Using an instrumented walkway (GaitRite) as the reference standard, this study compared the validity and reliability of multiple acceleration-derived asymmetry variables. Twenty-five post-stroke participants performed repeated walks over GaitRite whilst wearing a tri-axial accelerometer (Axivity AX3) on their lower back, on two occasions, one week apart. Harmonic ratio, autocorrelation, gait symmetry index, phase plots, acceleration, and jerk root mean square were calculated from the acceleration signals. Test–retest reliability was calculated, and concurrent validity was estimated by comparison with GaitRite. The strongest concurrent validity was obtained from step regularity from the vertical signal, which also recorded excellent test–retest reliability (Spearman’s rank correlation coefficients (rho) = 0.87 and Intraclass correlation coefficient (ICC21) = 0.98, respectively). Future research should test the responsiveness of this and other step asymmetry variables to quantify change during recovery and the effect of rehabilitative interventions for consideration as digital biomarkers to quantify gait asymmetry

    Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization

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    Wearable devices are used in movement analysis and physical activity research to extract clinically relevant information about an individual's mobility. Still, heterogeneity in protocols, sensor characteristics, data formats, and gold standards represent a barrier for data sharing, reproducibility, and external validation. In this study, we aim at providing an example of how movement data (from the real-world and the laboratory) recorded from different wearables and gold standard technologies can be organized, integrated, and stored. We leveraged on our experience from a large multi-centric study (Mobilise-D) to provide guidelines that can prove useful to access, understand, and re-use the data that will be made available from the study. These guidelines highlight the encountered challenges and the adopted solutions with the final aim of supporting standardization and integration of data in other studies and, in turn, to increase and facilitate comparison of data recorded in the scientific community. We also provide samples of standardized data, so that both the structure of the data and the procedure can be easily understood and reproduced

    Dual vs. Single Tasking During Circular Walking: What Better Reflects Progression in Parkinson's Disease?

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    Background and Aim: Reliable, valid and sensitive measures of dual-task-associated impairments in patients with Parkinson's disease (PD) may reveal progressive deficits unnoticed under single-task walking. The aim of this study was to quantitatively identify markers of progressive gait deficits in idiopathic PD while walking over a circular trajectory condition in single-task walking and in different dual-task conditions: (1) circular walking while checking boxes on a paper sheet as fast as possible and (2) circular walking while performing subtraction of 7 as fast as possible. In addition, we aimed to study the added value of dual-tasking assessment over single (circular) walking task assessment in the study of PD progression.Methods: The assessments were performed every 6 months over a (up to) 5 years period for 22 patients in early-stage PD, 27 patients in middle-stage PD and 25 healthy controls (HC). Longitudinal changes of 27 gait features extracted from accelerometry were compared between PD groups and HCs using generalized estimating equations analysis, accounting for gait speed, age, and levodopa medication state confounders when required. In addition, dual-task-interference with gait and cognitive performance was assessed, as well as their combination.Results: The results support the validity and robustness of some of the gait features already identified in our previous work as progression markers of the disease in single-task circular walking. However, fewer gait features from dual-task than from single-task assessments were identified as markers of progression in PD. Moreover, we did not clearly identify progressive worsening of dual-task-interference in patients with PD, although some group differences between early and middle stages of PD vs. the control group were observed for dual-task interference with the gait task and with the concurrent tasks.Conclusions: Overall, the results showed that dual-tasking did not have added value in the study of PD progression from circular gait assessments. Our analyses suggest that, while single-task walking might be sensitive enough, dual-tasking may introduce additional (error) variance to the data and may represent complex composite measures of cognitive and motor performance

    Potential Markers of Progression in Idiopathic Parkinson’s Disease Derived From Assessment of Circular Gait With a Single Body-Fixed-Sensor: A 5 Year Longitudinal Study

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    Background and Aim: Development of objective, reliable and easy-to-use methods to obtain progression markers of Parkinson’s disease (PD) is required to evaluate interventions and to advance research in PD. This study aimed to provide quantitative markers of progression in idiopathic PD from the assessment of circular gait (walking in circles) with a single body-fixed inertial sensor placed on the lower back.Methods: The assessments were performed every 6 months over a (up to) 5 years period for 22 patients in early-stage PD, 27 patients in middle-stage PD and 25 healthy controls (HC). Longitudinal changes of 24 gait features extracted from accelerometry were compared between PD groups and HCs with generalized estimating equations (GEE) analysis, accounting for gait speed, age and levodopa medication state confounders when required.Results: Five gait features indicated progressive worsening in early stages of PD: number of steps, total duration and harmonic ratios calculated from vertical (VT), medio-lateral (ML), and anterior-posterior (AP) accelerations. For middle stages of PD, three gait features were identified as potential progression markers: stride time variability, and stride regularity from VT and AP acceleration.Conclusion: Faster progressive worsening of gait features in early and middle stages of PD relative to healthy controls over 5 years confirmed the potential of accelerometry-based assessments as quantitative progression markers in early and middle stages of the disease. The difference in significant parameters between both PD groups suggests that distinct domains of gait deteriorate in these PD stages. We conclude that instrumented circular walking assessment is a practical and useful tool in the assessment of PD progression that may have relevant potential to be implemented in clinical trials and even clinical routine, particularly in a developing digital era

    Design and validation of a multi-task, multi-context protocol for real-world gait simulation

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    Background: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. Methods: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants’ strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson’s disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. Results: The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. Conclusions: The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. Trial registration: ISRCTN—12246987

    Technical validation of real-world monitoring of gait: a multicentric observational study

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    Introduction: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real- world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users’ perspective on the device. Methods and analysis: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs. After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson’s disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users’ perspective on the deployed technology and relevance of the mobility assessment. Ethics and dissemination: The study has been granted ethics approval by the centre’s committees (London—Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available

    A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

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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

    Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

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    Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. Methods: Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. Results: We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. Conclusions: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under Grant Agreement No. 820820. This JU receives support from the European Union’s Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). SDD, LR, AY were also supported by the Innovative Medicines Initiative 2 Joint Undertaking (IMI2 JU) project IDEA-FAST—Grant Agreement 853981. LA, LR, AY and SDD were also supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre (BRC) based at The Newcastle upon Tyne Hospital NHS Foundation Trust, Newcastle University and the Cumbria, Northumberland and Tyne and Wear (CNTW) NHS Foundation Trust. LA, LR, AY and SDD were also supported by the NIHR/Wellcome Trust Clinical Research Facility (CRF) infrastructure at Newcastle upon Tyne Hospitals NHS Foundation Trust. This study was also supported by the National Institute for Health Research (NIHR) through the Sheffield Biomedical Research Centre (BRC, Grant Number IS-BRC-1215–20017). ISGlobal acknowledges support from the Spanish Ministry of Science and Innovation through the “Centro de Excelencia Severo Ochoa 2019–2023” Program (CEX2018-000806-S), and from the Generalitat de Catalunya through the CERCA Program. All opinions are those of the authors and not the funders. The content in this publication reflects the authors’ view, and neither IMI nor the European Union, EFPIA, NHS, NIHR, DHSC, or any associated partners are responsible for any use that may be made of the information contained herein

    Dual vs. Single Tasking During Circular Walking:What Better Reflects Progression in Parkinson's Disease?

    No full text
    Background and Aim: Reliable, valid and sensitive measures of dual-task-associated impairments in patients with Parkinson's disease (PD) may reveal progressive deficits unnoticed under single-task walking. The aim of this study was to quantitatively identify markers of progressive gait deficits in idiopathic PD while walking over a circular trajectory condition in single-task walking and in different dual-task conditions: (1) circular walking while checking boxes on a paper sheet as fast as possible and (2) circular walking while performing subtraction of 7 as fast as possible. In addition, we aimed to study the added value of dual-tasking assessment over single (circular) walking task assessment in the study of PD progression. Methods: The assessments were performed every 6 months over a (up to) 5 years period for 22 patients in early-stage PD, 27 patients in middle-stage PD and 25 healthy controls (HC). Longitudinal changes of 27 gait features extracted from accelerometry were compared between PD groups and HCs using generalized estimating equations analysis, accounting for gait speed, age, and levodopa medication state confounders when required. In addition, dual-task-interference with gait and cognitive performance was assessed, as well as their combination. Results: The results support the validity and robustness of some of the gait features already identified in our previous work as progression markers of the disease in single-task circular walking. However, fewer gait features from dual-task than from single-task assessments were identified as markers of progression in PD. Moreover, we did not clearly identify progressive worsening of dual-task-interference in patients with PD, although some group differences between early and middle stages of PD vs. the control group were observed for dual-task interference with the gait task and with the concurrent tasks. Conclusions: Overall, the results showed that dual-tasking did not have added value in the study of PD progression from circular gait assessments. Our analyses suggest that, while single-task walking might be sensitive enough, dual-tasking may introduce additional (error) variance to the data and may represent complex composite measures of cognitive and motor performance

    Potential markers of progression in idiopathic Parkinson’s disease derived from assessment of circular gait with a single body-fixed-sensor: A 5 year longitudinal study

    No full text
    Background and Aim: Development of objective, reliable and easy-to-use methods to obtain progression markers of Parkinson’s disease (PD) is required to evaluate interventions and to advance research in PD. This study aimed to provide quantitative markers of progression in idiopathic PD from the assessment of circular gait (walking in circles) with a single body-fixed inertial sensor placed on the lower back. Methods: The assessments were performed every 6 months over a (up to) 5 years period for 22 patients in early-stage PD, 27 patients in middle-stage PD and 25 healthy controls (HC). Longitudinal changes of 24 gait features extracted from accelerometry were compared between PD groups and HCs with generalized estimating equations (GEE) analysis, accounting for gait speed, age and levodopa medication state confounders when required. Results: Five gait features indicated progressive worsening in early stages of PD: number of steps, total duration and harmonic ratios calculated from vertical (VT), medio-lateral (ML), and anterior-posterior (AP) accelerations. For middle stages of PD, three gait features were identified as potential progression markers: stride time variability, and stride regularity from VT and AP acceleration. Conclusion: Faster progressive worsening of gait features in early and middle stages of PD relative to healthy controls over 5 years confirmed the potential of accelerometry-based assessments as quantitative progression markers in early and middle stages of the disease. The difference in significant parameters between both PD groups suggests that distinct domains of gait deteriorate in these PD stages. We conclude that instrumented circular walking assessment is a practical and useful tool in the assessment of PD progression that may have relevant potential to be implemented in clinical trials and even clinical routine, particularly in a developing digital era
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