Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Measuring Disease Progression in Multiple Sclerosis Clinical Drug Trials and Impact on Future Patient Care

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system characterised by inflammation, demyelination and neurodegeneration. Although several drugs are approved for MS, their efficacy in progressive disease is modest. Addressing disease progression as a treatment goal in MS is challenging due to several factors. These include a lack of complete understanding of the pathophysiological mechanisms driving MS and the absence of sensitive markers of disease progression in the short-term of clinical trials. MS usually begins at a young age and lasts for decades, whereas clinical research often spans only 1-3 years. Additionally, there is no unifying definition of disease progression. Several drugs are currently being investigated for progressive MS. In addition to new medications, the rise of new technologies and of adaptive trial designs is enabling larger and more integrated data collection. Remote assessments and decentralised clinical trials are becoming feasible. These will allow more efficient and large studies at a lower cost and with less burden on study participants. As new drugs are developed and research evolves, we anticipate a concurrent change in patient care at various levels in the foreseeable future. We conducted a narrative review to discuss the challenges of accurately measuring disease progression in contemporary MS drug trials, some new research trends and their implications for patient care.

Predicting executive functioning from walking features in Parkinson's disease using machine learning

Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and executive functioning in patients with Parkinson's disease using state-of-the-art machine learning approaches. A dataset of 103 geriatric Parkinson inpatients, who performed four walking conditions with varying difficulty levels depending on single task walking and additional motor and cognitive demands, was analyzed. Walking features were quantified using an inertial measurement unit (IMU) system positioned at the patient's lower back. The analyses included five imputation methods and four regression approaches to predict executive functioning, as measured using the Trail-Making Test (TMT). Multiple imputation by chained equations (MICE) in combination with support vector regression (SVR) reduce the mean absolute error by about 4.95% compared to baseline. Importantly, predictions solely based on walking features obtained with support vector regression mildly but significantly correlated with Δ-TMT values. Specifically, this effect was primarily driven by step time variability, double limb support time variability, and gait speed in the dual task condition with cognitive demands. Taken together, our data provide direct evidence for a link between executive functioning and specific walking features in Parkinson's disease.

Inertial measurement units to evaluate the efficacity of Equino Varus Foot surgery in post stroke hemiparetic patients: a feasibility study

INTRODUCTION

This study evaluates the gait analysis obtained by Inetial Measurement Units (IMU) before and after surgical management of Spastic Equino Varus Foot (SEVF) in hemiplegic post-stroke patients and to compare it with the functional results obtained in a monocentric prospective cohort.

METHODS

Patients with post-stroke SEVF, who underwent surgery in a single hospital between November 2019 and December 2021 were included. The follow-up duration was 6 months and included a functional analysis using Goal Attainment Scaling (GAS) and a Gait analysis using an innovative Multidimensional Gait Evaluation using IMU: the semiogram.

RESULTS

20 patients had a gait analysis preoperatively and at 6 months postoperatively. 90% (18/20) patients had a functional improvement (GAS T score ≥ 50) and 50% (10/20) had an improvement in walking technique as evidenced by the cessation of the use of a walking aid (WA). In patients with functional improvement and modification of WA the change in the semiogram area was + 9.5%, sd = 27.5%, and it was + 15.4%, sd = 28%. In the group with functional improvement without change of WA. For the 3 experiences (two patients) with unfavorable results, the area under the curve changed by + 2.3%, -10.2% and - 9.5%. The measurement of the semiogram area weighted by average speed demonstrated very good reproducibility (ICC(1, 3) = 0.80).

DISCUSSION

IMUs appear to be a promising solution for the assessment of post-stroke hemiplegic patients who have undergone SEVF surgery. They can provide a quantified, objective, reliable in individual longitudinal follow up automated gait analysis solution for routine clinical use. Combined with a functional scale such as the GAS, they can provide a global analysis of the effect of surgery.

Complexities and challenges of translating intervention success to real world gait in people with Parkinson's disease

Background

Unstable gait leading to falls negatively impacts the quality of life in many people with Parkinson's disease (PD). Systematic review evidence provides moderate to strong evidence of efficacy for a wide range of physiotherapy-based interventions to reduce gait impairment. However, outcomes have often focused on gait assessments conducted in controlled laboratory or clinical environments.

Objective

This perspective investigates the complexities and challenges of conducting real-world gait assessments in people with PD and the factors that may influence the translation from improved lab-assessed gait to improved real-world gait.

Methods

Through a thorough review of current literature, we present an in-depth analysis of current methodological approaches to real-world gait assessments and the challenges that may influence the translation of an intervention's success from lab-based outcomes to improved walking during daily life.

Results

We identified six key factors that may influence the translation of intervention success into real-world environments at different stages of the process. These factors comprise the gait intervention, parameters analyzed, sensor setup, assessment protocols, characteristics of walking bouts, and medication status. We provide recommendations for each factor based on our synthesis of current literature.

Conclusion

This perspective emphasizes the importance of measuring intervention success outside of the laboratory environment using real-world gait assessments. Our findings support the need for future studies to bridge the gap between proven efficacy for gait as assessed in controlled laboratory environments and real-world impact for people with PD.

The Short Physical Performance Battery does not correlate with daily life gait quality and quantity in community-dwelling older adults with an increased fall risk

BACKGROUND

Both the Short Physical Performance Battery (SPPB) and daily life gait quality and quantity obtained from wearable sensors are used to measure functional status in older adults. It is generally assumed that they are interrelated and exchangeable, but this has not yet been established. Interchangeability of these measures would pave the way for remote monitoring of functional status.

RESEARCH QUESTION

Are the SPPB and daily life gait quality and quantity measures correlated in community-dwelling older adults?

METHODS

The SPPB and gait quality and quantity data of 229 community-dwelling adults of 65 years or older were collected. The SPPB is a combined score of the Three Stage Balance test, Four Meter Walk test, and Five Times Sit to Stand test and ranges from 0 to 12. Participants wore a tri-axial inertial sensor for one week to assess gait quality (e.g. gait stability and smoothness) and quantity (e.g. number of strides). Correlation coefficients between SPPB scores and gait quality and quantity measures were assessed using Spearman's correlation.

RESULTS

The median age of the study population was 76.2 years (IQR 72.6-81.0), and 76 % were women (n=175). The median SPPB score was 10 (IQR 8-11). Spearman's correlation coefficients between the SPPB and gait quality and quantity measures were all below 0.3.

SIGNIFICANCE

A possible explanation for the observed weak correlations is that the SPPB reflects one's maximal capacity, while gait quality and quantity reflect the submaximal performance in daily life. The SPPB and gait quality and quantity seem therefore distinct constructs with complementary value, rather than interchangeable. A more comprehensive understanding of functional status might be achieved by combining the SPPB assessment of standardized activities with the evaluation of inertial sensor measurements obtained during daily life activities.

Clinical and device-based predictors of improved experience of activities of daily living after a multidisciplinary inpatient treatment for people with Parkinson's disease: a cohort study

Background

The inpatient Parkinson's Disease Multimodal Complex Treatment (PD-MCT) is an important therapeutical approach to improving gait and activities of daily living (ADL) of people with PD (PwP). Wearable device-based parameters (DBP) are new options for specific gait analyses toward individualized treatments.

Objectives

We sought to identify predictors of perceived ADL benefit taking clinical scores and DBP into account. Additionally, we analyzed DBP and clinical scores before and after PD-MCT.

Design

Exploratory observational cohort study.

Methods

Clinical scores and DBP of 56 PwP (mean age: 66.3 years, median Hoehn and Yahr (H&Y) stage: 2.5) were examined at the start and the end of a 14-day inpatient PD-MCT in a German University Medical Center. Participants performed four straight walking tasks under single- and dual-task conditions for gait analyses. Additionally, clinical scores of motor and nonmotor functions and quality of life (QoL) were assessed. Using dichotomized data of change in Movement Disorders Society Unified Parkinson's Disease Rating Scale Part II (MDS-UPDRS II) as a dependent variable and clinical and DBP as independent variables, a binomial logistic regression model was implemented.

Results

Young age, high perceived ADL impairment at baseline, high dexterity skills, and a steady gait were significant predictors of ADL benefit after PD-MCT. DBP like gait speed, number of steps, step time, stance time, and double limb support time were improved after PD-MCT. In addition, motor functions (e.g., MDS-UPDRS III and IV), QoL, perceived ADL (MDS-UPDRS II), and experience of nonmotor functions (MDS-UPDRS I) improved significantly.

Conclusion

The logistic regression model identified a group of PwP who had the most probable perceived ADL benefit after PD-MCT. Additionally, gait improved toward a faster and more dynamic gait. Using wearable technology in context of PD-MCT is promising to offer more personalized therapeutical concepts.

Trial registration

German Clinical Trial Register, https://drks.de; DRKS00020948 number, 30 March 2020, retrospectively registered.

The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review

Wearable health devices are becoming vital in chronic disease management because they offer real-time monitoring and personalized care. This review explores their effectiveness and challenges across medical fields, including cardiology, respiratory health, neurology, endocrinology, orthopedics, oncology, and mental health. A thorough literature search identified studies focusing on wearable devices' impact on patient outcomes. In cardiology, wearables have proven effective for monitoring hypertension, detecting arrhythmias, and aiding cardiac rehabilitation. In respiratory health, these devices enhance asthma management and continuous monitoring of critical parameters. Neurological applications include seizure detection and Parkinson's disease management, with wearables showing promising results in improving patient outcomes. In endocrinology, wearable technology advances thyroid dysfunction monitoring, fertility tracking, and diabetes management. Orthopedic applications include improved postsurgical recovery and rehabilitation, while wearables help in early complication detection in oncology. Mental health benefits include anxiety detection, post-traumatic stress disorder management, and stress reduction through wearable biofeedback. In conclusion, wearable health devices offer transformative potential for managing chronic illnesses by enhancing real-time monitoring and patient engagement. Despite significant improvements in adherence and outcomes, challenges with data accuracy and privacy persist. However, with ongoing innovation and collaboration, we can all be part of the solution to maximize the benefits of wearable technologies in healthcare.

Risk of unfavorable pain prognosis impacts walking physiomechanical parameters and psychophysiological workload in sufferers of chronic low back pain

BACKGROUND

Tolerating physical tasks depends not only on task-specific characteristics but also on an individual's psychophysiological capacity to respond to the imposed load. People suffering from chronic low back pain (CLBP) may experience reduced psychophysiological capacity and are at risk for poor pain prognosis, which could lead to an increased walking workload.

AIM

To investigate how the risk of unfavorable pain prognosis in CLBP can impact walking physiomechanical parameters and psychophysiological workload.

METHODS

A cross-sectional observational study. The study classified 74 volunteers into four groups based on their prognosis for pain: pain-free control (CG/n = 20), low (LrG/n = 21), medium (MrG/n = 22), and high (HrG/n = 11) risk of poor prognosis for CLBP. The ground assessments identified the self-selected (SSW) and optimal (OWS) walking speeds, as well as the locomotor rehabilitation index (LRI). Treadmill assessments were conducted at two different speeds (0.83 and 1.11 m s-1, SSW and OWS) to record physiomechanical parameters. Psychophysiological workloads during walking were measured via workload impulse for the session (TRIMP), determined by variations in heart rate.

RESULTS

CLBP groups exhibited slower SSW and lower LRI compared to the CG. The TRIMP was lower in the LrG. However, both MrG and HrG exhibited a comparable overload to the CG, even while walking at a lower intensity with a psychophysical demand. SSW and OWS displayed an increased TRIMP compared to fixed speeds.

CONCLUSION

Psychosocial factors may affect SSW in people with CLBP but not among the risk strata. An unfavorable prognosis for pain could jeopardize the psychophysiological capacity to withstand walking demands.

The global patient-reported outcomes for multiple sclerosis initiative: bridging the gap between clinical research and care - updates at the 2023 plenary event

Significant advancements have been achieved in delineating the progress of the Global PROMS (PROMS) Initiative. The PROMS Initiative, a collaborative endeavor by the European Charcot Foundation and the Multiple Sclerosis International Federation, strives to amplify the influence of patient input on MS care and establish a cohesive perspective on Patient-Reported Outcomes (PROs) for diverse stakeholders. This initiative has established an expansive, participatory governance framework launching four dedicated working groups that have made substantive contributions to research, clinical management, eHealth, and healthcare system reform. The initiative prioritizes the global integration of patient (For the purposes of the Global PROMS Initiative, the term "patient" refers to the people with the disease (aka People with Multiple Sclerosis - pwMS): any individual with lived experience of the disease. People affected by the disease/Multiple Sclerosis: any individual or group that is affected by the disease: E.g., family members, caregivers will be also engaged as the other stakeholders in the initiative). insights into the management of MS care. It merges subjective PROs with objective clinical metrics, thereby addressing the complex variability of disease presentation and progression. Following the completion of its second phase, the initiative aims to help increasing the uptake of eHealth tools and passive PROs within research and clinical settings, affirming its unwavering dedication to the progressive refinement of MS care. Looking forward, the initiative is poised to continue enhancing global surveys, rethinking to the relevant statistical approaches in clinical trials, and cultivating a unified stance among 'industry', regulatory bodies and health policy making regarding the application of PROs in MS healthcare strategies.

Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study over 12 months

Digital measures may provide objective, sensitive, real-world measures of disease progression in Parkinson's disease (PD). However, multicenter longitudinal assessments of such measures are few. We recently demonstrated that baseline assessments of gait, tremor, finger tapping, and speech from a commercially available smartwatch, smartphone, and research-grade wearable sensors differed significantly between 82 individuals with early, untreated PD and 50 age-matched controls. Here, we evaluated the longitudinal change in these assessments over 12 months in a multicenter observational study using a generalized additive model, which permitted flexible modeling of at-home data. All measurements were included until participants started medications for PD. Over one year, individuals with early PD experienced significant declines in several measures of gait, an increase in the proportion of day with tremor, modest changes in speech, and few changes in psychomotor function. As measured by the smartwatch, the average (SD) arm swing in-clinic decreased from 25.9 (15.3) degrees at baseline to 19.9 degrees (13.7) at month 12 (P = 0.004). The proportion of awake time an individual with early PD had tremor increased from 19.3% (18.0%) to 25.6% (21.4%; P < 0.001). Activity, as measured by the number of steps taken per day, decreased from 3052 (1306) steps per day to 2331 (2010; P = 0.16), but this analysis was restricted to 10 participants due to the exclusion of those that had started PD medications and lost the data. The change of these digital measures over 12 months was generally larger than the corresponding change in individual items on the Movement Disorder Society-Unified Parkinson's Disease Rating Scale but not greater than the change in the overall scale. Successful implementation of digital measures in future clinical trials will require improvements in study conduct, especially data capture. Nonetheless, gait and tremor measures derived from a commercially available smartwatch and smartphone hold promise for assessing the efficacy of therapeutics in early PD.

Characterizing Walking Behaviors in Aged Residential Care Using Accelerometry, With Comparison Across Care Levels, Cognitive Status, and Physical Function: Cross-Sectional Study

Background

Walking is important for maintaining physical and mental well-being in aged residential care (ARC). Walking behaviors are not well characterized in ARC due to inconsistencies in assessment methods and metrics as well as limited research regarding the impact of care environment, cognition, or physical function on these behaviors. It is recommended that walking behaviors in ARC are assessed using validated digital methods that can capture low volumes of walking activity.

Objective

This study aims to characterize and compare accelerometry-derived walking behaviors in ARC residents across different care levels, cognitive abilities, and physical capacities.

Methods

A total of 306 ARC residents were recruited from the Staying UpRight randomized controlled trial from 3 care levels: rest home (n=164), hospital (n=117), and dementia care (n=25). Participants' cognitive status was classified as mild (n=87), moderate (n=128), or severe impairment (n=61); physical function was classified as high-moderate (n=74) and low-very low (n=222) using the Montreal Cognitive Assessment and the Short Physical Performance Battery cutoff scores, respectively. To assess walking, participants wore an accelerometer (Axivity AX3; dimensions: 23×32.5×7.6 mm; weight: 11 g; sampling rate: 100 Hz; range: ±8 g; and memory: 512 MB) on their lower back for 7 days. Outcomes included volume (ie, daily time spent walking, steps, and bouts), pattern (ie, mean walking bout duration and alpha), and variability (of bout length) of walking. Analysis of covariance was used to assess differences in walking behaviors between groups categorized by level of care, cognition, or physical function while controlling for age and sex. Tukey honest significant difference tests for multiple comparisons were used to determine where significant differences occurred. The effect sizes of group differences were calculated using Hedges g (0.2-0.4: small, 0.5-0.7: medium, and 0.8: large).

Results

Dementia care residents showed greater volumes of walking (P<.001; Hedges g=1.0-2.0), with longer (P<.001; Hedges g=0.7-0.8), more variable (P=.008 vs hospital; P<.001 vs rest home; Hedges g=0.6-0.9) bouts compared to other care levels with a lower alpha score (vs hospital: P<.001; Hedges g=0.9, vs rest home: P=.004; Hedges g=0.8). Residents with severe cognitive impairment took longer (P<.001; Hedges g=0.5-0.6), more variable (P<.001; Hedges g=0.4-0.6) bouts, compared to those with mild and moderate cognitive impairment. Residents with low-very low physical function had lower walking volumes (total walk time and bouts per day: P<.001; steps per day: P=.005; Hedges g=0.4-0.5) and higher variability (P=.04; Hedges g=0.2) compared to those with high-moderate capacity.

Conclusions

ARC residents across different levels of care, cognition, and physical function demonstrate different walking behaviors. However, ARC residents often present with varying levels of both cognitive and physical abilities, reflecting their complex multimorbid nature, which should be considered in further work. This work has demonstrated the importance of considering a nuanced framework of digital outcomes relating to volume, pattern, and variability of walking behaviors among ARC residents.

Gait differences between COPD and healthy controls: systematic review and meta-analysis

BACKGROUND

Despite the importance of gait as a determinant of falls, disability and mortality in older people, understanding of gait impairment in COPD is limited. This study aimed to identify differences in gait characteristics during supervised walking tests between people with COPD and healthy controls.

METHODS

We searched 11 electronic databases, supplemented by Google Scholar searches and manual collation of references, in November 2019 and updated the search in July 2021. Record screening and information extraction were performed independently by one reviewer and checked for accuracy by a second. Meta-analyses were performed in studies not considered at a high risk of bias.

RESULTS

Searches yielded 21 085 unique records, of which 25 were included in the systematic review (including 1015 people with COPD and 2229 healthy controls). Gait speed was assessed in 17 studies (usual speed: 12; fast speed: three; both speeds: two), step length in nine, step duration in seven, cadence in six, and step width in five. Five studies were considered at a high risk of bias. Low-quality evidence indicated that people with COPD walk more slowly than healthy controls at their usual speed (mean difference (MD) -19 cm·s-1, 95% CI -28 to -11 cm·s-1) and at a fast speed (MD -30 cm·s-1, 95% CI -47 to -13 cm·s-1). Alterations in other gait characteristics were not statistically significant.

CONCLUSION

Low-quality evidence shows that people with COPD walk more slowly than healthy controls, which could contribute to an increased falls risk. The evidence for alterations in spatial and temporal components of gait was inconclusive. Gait impairment appears to be an important but understudied area in COPD.

The Analytical Validity of Stride Detection and Gait Parameters Reconstruction Using the Ankle-Mounted Inertial Measurement Unit Syde®

The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subjects (age: 23.17 ± 2.04, height: 174.17 ± 6.46 cm) participated in a controlled environment data collection and performed a series of gait tasks with both systems attached to each ankle. A total of 2820 strides were analyzed. The results show a median absolute stride length error of 1.86 cm between the IMU-based wearable device reconstruction and the motion capture ground truth, with the 75th percentile at 3.24 cm. The median absolute stride horizontal velocity error was 1.56 cm/s, with the 75th percentile at 2.63 cm/s. With a measurement error to the reference system of less than 3 cm, we conclude that there is a valid physical recovery of stride length and horizontal velocity from data collected with the IMU-based wearable Syde® device.

Improved measurement of disease progression in people living with early Parkinson's disease using digital health technologies

BACKGROUND

Digital health technologies show promise for improving the measurement of Parkinson's disease in clinical research and trials. However, it is not clear whether digital measures demonstrate enhanced sensitivity to disease progression compared to traditional measurement approaches.

METHODS

To this end, we develop a wearable sensor-based digital algorithm for deriving features of upper and lower-body bradykinesia and evaluate the sensitivity of digital measures to 1-year longitudinal progression using data from the WATCH-PD study, a multicenter, observational digital assessment study in participants with early, untreated Parkinson's disease. In total, 82 early, untreated Parkinson's disease participants and 50 age-matched controls were recruited and took part in a variety of motor tasks over the course of a 12-month period while wearing body-worn inertial sensors. We establish clinical validity of sensor-based digital measures by investigating convergent validity with appropriate clinical constructs, known groups validity by distinguishing patients from healthy volunteers, and test-retest reliability by comparing measurements between visits.

RESULTS

We demonstrate clinical validity of the digital measures, and importantly, superior sensitivity of digital measures for distinguishing 1-year longitudinal change in early-stage PD relative to corresponding clinical constructs.

CONCLUSIONS

Our results demonstrate the potential of digital health technologies to enhance sensitivity to disease progression relative to existing measurement standards and may constitute the basis for use as drug development tools in clinical research.

Real-world walking cadence in people with COPD

Introduction

The clinical validity of real-world walking cadence in people with COPD is unsettled. Our objective was to assess the levels, variability and association with clinically relevant COPD characteristics and outcomes of real-world walking cadence.

Methods

We assessed walking cadence (steps per minute during walking bouts longer than 10 s) from 7 days' accelerometer data in 593 individuals with COPD from five European countries, and clinical and functional characteristics from validated questionnaires and standardised tests. Severe exacerbations during a 12-month follow-up were recorded from patient reports and medical registries.

Results

Participants were mostly male (80%) and had mean±sd age of 68±8 years, post-bronchodilator forced expiratory volume in 1 s (FEV1) of 57±19% predicted and walked 6880±3926 steps·day-1. Mean walking cadence was 88±9 steps·min-1, followed a normal distribution and was highly stable within-person (intraclass correlation coefficient 0.92, 95% CI 0.90-0.93). After adjusting for age, sex, height and number of walking bouts in fractional polynomial or linear regressions, walking cadence was positively associated with FEV1, 6-min walk distance, physical activity (steps·day-1, time in moderate-to-vigorous physical activity, vector magnitude units, walking time, intensity during locomotion), physical activity experience and health-related quality of life and negatively associated with breathlessness and depression (all p<0.05). These associations remained after further adjustment for daily steps. In negative binomial regression adjusted for multiple confounders, walking cadence related to lower number of severe exacerbations during follow-up (incidence rate ratio 0.94 per step·min-1, 95% CI 0.91-0.99, p=0.009).

Conclusions

Higher real-world walking cadence is associated with better COPD status and lower severe exacerbations risk, which makes it attractive as a future prognostic marker and clinical outcome.

On Gait Consistency Quantification Through ARX Residual Modeling and Kernel Two-Sample Testing

OBJECTIVE

The quantification of the way an individual walks is key to the understanding of diseases affecting the neuromuscular system. More specifically, to improve diagnostics and treatment plans, there is a continuous interest in quantifying gait consistency, allowing clinicians to distinguish natural variability of the gait patterns from disease progression or treatment effects. To this end, the current article presents a novel objective method for assessing the consistency of an individual's gait, consisting of two major components.

METHODS

Firstly, inertial sensor accelerometer data from both shanks and the lower back is used to fit an AutoRegressive with eXogenous input model. The model residuals are then used as a key feature for gait consistency monitoring. Secondly, the non-parametric maximum mean discrepancy hypothesis test is introduced to measure differences in the distributions of the residuals as a measure of gait consistency. As a paradigmatic case, gait consistency was evaluated both in a single walking test and between tests at different time points in healthy individuals and those affected by multiple sclerosis (MS).

RESULTS

It was found that MS patients experienced difficulties maintaining a consistent gait, even when the retest was performed one-hour apart and all external factors were controlled. When the retest was performed one-week apart, both healthy and MS individuals displayed inconsistent gait patterns.

CONCLUSION

Gait consistency has been successfully quantified for both healthy and MS individuals.

SIGNIFICANCE

This newly proposed approach revealed the detrimental effects of varying assessment conditions on gait pattern consistency, indicating potential masking effects at follow-up assessments.

Evaluation of mobility recovery after hip fracture: a scoping review of randomized controlled studies

Few older adults regain their pre-fracture mobility after a hip fracture. Intervention studies evaluating effects on gait typically use short clinical tests or in-lab parameters that are often limited to gait speed only. Measurements of mobility in daily life settings exist and should be considered to a greater extent than today. Less than half of hip fracture patients regain their pre-fracture mobility. Mobility recovery is closely linked to health status and quality of life, but there is no comprehensive overview of how gait has been evaluated in intervention studies on hip fracture patients. The purpose was to identify what gait parameters have been used in randomized controlled trials to assess intervention effects on older people's mobility recovery after hip fracture. This scoping review is a secondary paper that identified relevant peer-reviewed and grey literature from 11 databases. After abstract and full-text screening, 24 papers from the original review and 8 from an updated search and manual screening were included. Records were eligible if they included gait parameters in RCTs on hip fracture patients. We included 32 papers from 29 trials (2754 unique participants). Gait parameters were primary endpoint in six studies only. Gait was predominantly evaluated as short walking, with gait speed being most frequently studied. Only five studies reported gait parameters from wearable sensors. Evidence on mobility improvement after interventions in hip fracture patients is largely limited to gait speed as assessed in a controlled setting. The transition from traditional clinical and in-lab to out-of-lab gait assessment is needed to assess effects of interventions on mobility recovery after hip fracture at higher granularity in all aspects of patients' lives, so that optimal care pathways can be defined.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Digital measurement of mobility in pulmonary arterial hypertension: A structured review of an emerging area

This review examined literature that has examined mobility in pulmonary arterial hypertension (PAH) using digital technology. Specifically, the review focussed on: (a) digital mobility measurement in PAH; (b) commonly reported mobility outcomes in PAH; (c) PAH specific impact on mobility outcomes; and (d) recommendations concerning protocols for mobility measurement in PAH. PubMed, Scopus, and Medline databases were searched. Two independent reviewers screened articles that described objective measurement of mobility in PAH using digital technology. Twenty-one articles were screened, and 16 articles met the inclusion/exclusion criteria and were reviewed. Current methodologies for mobility measurement in PAH with digital technologies are discussed. In brief, the reviewed evidence demonstrated that there is a lack of standardisation across studies for instrumentation, outcomes, and interpretation in PAH. The validity and reliability of digital approaches were insufficiently reported in all studies. Future research is required to standardise digital mobility measurement and characterise mobility impairments in PAH across clinical and real-world settings. The reviewed evidence suggests that digital mobility outcomes may be useful clinical measures and may be impaired in PAH, but further research is required to accurately and robustly establish findings. Recommendations are provided for future studies that encompass comprehensive reporting, validation, and measurement.

Investigating the prognostic value of digital mobility outcomes in patients with chronic obstructive pulmonary disease: a systematic literature review and meta-analysis

BACKGROUND

Reduced mobility is a central feature of COPD. Assessment of mobility outcomes that can be measured digitally (digital mobility outcomes (DMOs)) in daily life such as gait speed and steps per day is increasingly possible using devices such as pedometers and accelerometers, but the predictive value of these measures remains unclear in relation to key outcomes such as hospital admission and survival.

METHODS

We conducted a systematic review, nested within a larger scoping review by the MOBILISE-D consortium, addressing DMOs in a range of chronic conditions. Qualitative and quantitative analysis considering steps per day and gait speed and their association with clinical outcomes in COPD patients was performed.

RESULTS

21 studies (6076 participants) were included. Nine studies evaluated steps per day and 11 evaluated a measure reflecting gait speed in daily life. Negative associations were demonstrated between mortality risk and steps per day (per 1000 steps) (hazard ratio (HR) 0.81, 95% CI 0.75-0.88, p<0.001), gait speed (<0.80 m·s-1) (HR 3.55, 95% CI 1.72-7.36, p<0.001) and gait speed (per 1.0 m·s-1) (HR 7.55, 95% CI 1.11-51.3, p=0.04). Fewer steps per day (per 1000) and slow gait speed (<0.80 m·s-1) were also associated with increased healthcare utilisation (HR 0.80, 95% CI 0.72-0.88, p<0.001; OR 3.36, 95% CI 1.42-7.94, p=0.01, respectively). Available evidence was of low-moderate quality with few studies eligible for meta-analysis.

CONCLUSION

Daily step count and gait speed are negatively associated with mortality risk and other important outcomes in people with COPD and therefore may have value as prognostic indicators in clinical trials, but the quantity and quality of evidence is limited. Larger studies with consistent methodologies are called for.

Physical activity among adults with chronic obstructive pulmonary disease in Spain (2014-2020): Temporal trends, sex differences, and associated factors

OBJECTIVES

To evaluate trends in the prevalence of physical activity (PA) from 2014 to 2020; to identify sex differences and sociodemographic and health-related factors associated with PA in individuals with chronic obstructive pulmonary disease (COPD); and to compare PA between individuals with and without COPD.

METHODS

Cross-sectional and case-control study.

SOURCE

European Health Interview Surveys for Spain (EHISS) conducted in 2014 and 2020. We included sociodemographic and health-related covariates. We compared individuals with and without COPD after matching for age and sex.

RESULTS

The number of adults with COPD was 1086 and 910 in EHISS2014 and EHISS2020, respectively. In this population, self-reported "Medium or high frequency of PA" remained stable (42.9% in 2014 and 43.5% in 2020; p = 0.779). However, the percentage who walked on two or more days per week rose significantly over time (63.4%-69.9%; p = 0.004). Men with COPD reported more PA than women with COPD in both surveys. After matching, significantly lower levels of PA were recorded in COPD patients than in adults without COPD. Multivariable logistic regression confirmed this trend in COPD patients and showed that male sex, younger age, higher educational level, very good/good self-perceived health, and absence of comorbidities, obesity, and smoking were associated with more frequent PA.

CONCLUSIONS

The temporal trend in PA among Spanish adults with COPD is favorable, although there is much room for improvement. Insufficient PA is more prevalent in these patients than in the general population. Sex differences were found, with significantly more frequent PA among males with COPD.

Walking Bout Detection for People Living in Long Residential Care: A Computationally Efficient Algorithm for a 3-Axis Accelerometer on the Lower Back

Accurate and reliable measurement of real-world walking activity is clinically relevant, particularly for people with mobility difficulties. Insights on walking can help understand mobility function, disease progression, and fall risks. People living in long-term residential care environments have heterogeneous and often pathological walking patterns, making it difficult for conventional algorithms paired with wearable sensors to detect their walking activity. We designed two walking bout detection algorithms for people living in long-term residential care. Both algorithms used thresholds on the magnitude of acceleration from a 3-axis accelerometer on the lower back to classify data as "walking" or "non-walking". One algorithm had generic thresholds, whereas the other used personalized thresholds. To validate and evaluate the algorithms, we compared the classifications of walking/non-walking from our algorithms to the real-time research assistant annotated labels and the classification output from an algorithm validated on a healthy population. Both the generic and personalized algorithms had acceptable accuracy (0.83 and 0.82, respectively). The personalized algorithm showed the highest specificity (0.84) of all tested algorithms, meaning it was the best suited to determine input data for gait characteristic extraction. The developed algorithms were almost 60% quicker than the previously developed algorithms, suggesting they are adaptable for real-time processing.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Introduction

The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings.

Methods

Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data.

Results and discussion

The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of -0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, -0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases.

Laboratory and free-living gait performance in adults with COPD and healthy controls

Background

Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised).

Methods

This case-control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately.

Results

Slower walking speed (-11 cm·s-1, 95% CI: -20 to -3) and lower cadence (-6.6 steps·min-1, 95% CI: -12.3 to -0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups.

Conclusion

Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD.

Effects of pharmacological and non-pharmacological interventions on physical activity outcomes in COPD: a systematic review and meta-analysis

Rationale

The effect of pharmacological and non-pharmacological interventions on physical activity (PA) outcomes is not fully elucidated in patients with COPD. The objectives of the present study were to provide estimation of treatment effects of all available interventions on PA outcomes in patients with COPD and to provide recommendations regarding the future role of PA outcomes in pharmacological trials.

Materials and methods

This review was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and reported in line with PRISMA. Records were identified through searches of 12 scientific databases; the most updated search was performed in January 2023.

Results

74 studies published from 2000 to 2021 were included, with a total of 8140 COPD patients. Forced expiratory volume in 1 s % predicted ranged between 31% and 74%, with a mean of 55%. Steps/day constituted the most frequently assessed PA outcome in interventional studies. Compared to usual care, PA behavioural modification interventions resulted in improvements in the mean (95% CI) steps/day when implemented alone (by 1035 (576-1493); p<0.00001) or alongside exercise training (by 679 (93-1266); p=0.02). Moreover, bronchodilator therapy yielded a favourable difference of 396 (125-668; p=0.004) steps/day, compared to placebo.

Conclusions

PA behavioural modification and pharmacological interventions lead to significant improvements in steps/day, compared to control and placebo groups, respectively. Compared to bronchodilator therapy, PA behavioural modification interventions were associated with a 2-fold greater improvement in steps/day. Large-scale pharmacological studies are needed to establish an intervention-specific minimal clinically important difference for PA outcomes as well as their convergent validity to accelerate qualification as potential biomarkers and efficacy end-points for regulatory approval.

Trends in public interest in shopping and point-of-sales of JUUL and Puff Bar 2019-2021

INTRODUCTION

We investigated public interest in shopping and point-of-sales (POS) of JUUL and Puff Bar products in the context of five regulatory, company sales policy and other events of interest that may have influenced the trajectory of these products during 2019-2021.

METHODS

Outcome variables included relative search volume (RSV) from Google search queries indicative of shopping interest in and aggregate dollar sales from Nielsen POS for JUUL and Puff Bar in the USA from March 2019 to May 2021. Adjusted autoregressive integrated moving average assessed the observed and predicted trends and adjusted linear regression analysis measured the relative rate of change in the outcome variables for each time period of interest.

RESULTS

After the Trump administration announced its plans to ban flavoured e-cigarettes and JUUL Labs, Inc.'s decided to suspend the sales of its sweet and fruity flavoured products, JUUL's shopping interest RSV and sales declined while Puff Bar's shopping interest RSV peaked, and its sales increased. From the period following FDA's announcement of its enforcement guidance policy on unauthorised flavoured cartridge-based e-cigarettes until May 2021, JUUL's shopping interest RSV and sales continued to decline. Puff Bar's shopping interest RSV increased, and its sales peaked until the House approved the flavoured e-cigarette ban bill. Puff Bar's sales steeply declined following suspension of its sales in February 2020. The decline, however, slowed after Puff Bar products were relaunched as 'synthetic nicotine' e-cigarettes.

CONCLUSIONS

Puff Bar's unprecedented peak in the shopping interest and sales of Puff Bar warrants continued surveillance.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

A Single-Sensor Approach to Quantify Gait in Patients with Hereditary Spastic Paraplegia

Hereditary spastic paraplegia (HSP) is characterised by progressive lower-limb spasticity and weakness resulting in ambulation difficulties. During clinical practice, walking is observed and/or assessed by timed 10-metre walk tests; time, feasibility, and methodological reliability are barriers to detailed characterisation of patients' walking abilities when instrumenting this test. Wearable sensors have the potential to overcome such drawbacks once a validated approach is available for patients with HSP. Therefore, while limiting patients' and assessors' burdens, this study aims to validate the adoption of a single lower-back wearable inertial sensor approach for step detection in HSP patients; this is the first essential algorithmic step in quantifying most gait temporal metrics. After filtering the 3D acceleration signal based on its smoothness and enhancing the step-related peaks, initial contacts (ICs) were identified as positive zero-crossings of the processed signal. The proposed approach was validated on thirteen individuals with HSP while they performed three 10-metre tests and wore pressure insoles used as a gold standard. Overall, the single-sensor approach detected 794 ICs (87% correctly identified) with high accuracy (median absolute errors (mae): 0.05 s) and excellent reliability (ICC = 1.00). Although about 12% of the ICs were missed and the use of walking aids introduced extra ICs, a minor impact was observed on the step time quantifications (mae 0.03 s (5.1%), ICC = 0.89); the use of walking aids caused no significant differences in the average step time quantifications. Therefore, the proposed single-sensor approach provides a reliable methodology for step identification in HSP, augmenting the gait information that can be accurately and objectively extracted from patients with HSP during their clinical assessment.

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

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.

Using Digital Technology to Quantify Habitual Physical Activity in Community Dwellers With Cognitive Impairment: Systematic Review

BACKGROUND

Participating in habitual physical activity (HPA) can support people with dementia and mild cognitive impairment (MCI) to maintain functional independence. Digital technology can continuously measure HPA objectively, capturing nuanced measures relating to its volume, intensity, pattern, and variability.

OBJECTIVE

To understand HPA participation in people with cognitive impairment, this systematic review aims to (1) identify digital methods and protocols; (2) identify metrics used to assess HPA; (3) describe differences in HPA between people with dementia, MCI, and controls; and (4) make recommendations for measuring and reporting HPA in people with cognitive impairment.

METHODS

Key search terms were input into 6 databases: Scopus, Web of Science, Psych Articles, PsychInfo, MEDLINE, and Embase. Articles were included if they included community dwellers with dementia or MCI, reported HPA metrics derived from digital technology, were published in English, and were peer reviewed. Articles were excluded if they considered populations without dementia or MCI diagnoses, were based in aged care settings, did not concern digitally derived HPA metrics, or were only concerned with physical activity interventions. Key outcomes extracted included the methods and metrics used to assess HPA and differences in HPA outcomes across the cognitive spectrum. Data were synthesized narratively. An adapted version of the National Institute of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was used to assess the quality of articles. Due to significant heterogeneity, a meta-analysis was not feasible.

RESULTS

A total of 3394 titles were identified, with 33 articles included following the systematic review. The quality assessment suggested that studies were moderate-to-good quality. Accelerometers worn on the wrist or lower back were the most prevalent methods, while metrics relating to volume (eg, daily steps) were most common for measuring HPA. People with dementia had lower volumes, intensities, and variability with different daytime patterns of HPA than controls. Findings in people with MCI varied, but they demonstrated different patterns of HPA compared to controls.

CONCLUSIONS

This review highlights limitations in the current literature, including lack of standardization in methods, protocols, and metrics; limited information on validity and acceptability of methods; lack of longitudinal research; and limited associations between HPA metrics and clinically meaningful outcomes. Limitations of this review include the exclusion of functional physical activity metrics (eg, sitting/standing) and non-English articles. Recommendations from this review include suggestions for measuring and reporting HPA in people with cognitive impairment and for future research including validation of methods, development of a core set of clinically meaningful HPA outcomes, and further investigation of socioecological factors that may influence HPA participation.

TRIAL REGISTRATION

PROSPERO CRD42020216744; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216744  .

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

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.

Listening to the patients' voice: a conceptual framework of the walking experience

BACKGROUND

walking is crucial for an active and healthy ageing, but the perspectives of individuals living with walking impairment are still poorly understood.

OBJECTIVES

to identify and synthesise evidence describing walking as experienced by adults living with mobility-impairing health conditions and to propose an empirical conceptual framework of walking experience.

METHODS

we performed a systematic review and meta-ethnography of qualitative evidence, searching seven electronic databases for records that explored personal experiences of walking in individuals living with conditions of diverse aetiology. Conditions included Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture, heart failure, frailty and sarcopenia. Data were extracted, critically appraised using the NICE quality checklist and synthesised using standardised best practices.

RESULTS

from 2,552 unique records, 117 were eligible. Walking experience was similar across conditions and described by seven themes: (i) becoming aware of the personal walking experience, (ii) the walking experience as a link between individuals' activities and sense of self, (iii) the physical walking experience, (iv) the mental and emotional walking experience, (v) the social walking experience, (vi) the context of the walking experience and (vii) behavioural and attitudinal adaptations resulting from the walking experience. We propose a novel conceptual framework that visually represents the walking experience, informed by the interplay between these themes.

CONCLUSION

a multi-faceted and dynamic experience of walking was common across health conditions. Our conceptual framework of the walking experience provides a novel theoretical structure for patient-centred clinical practice, research and public health.

Predicting hospitalization from real-world measures in patients with chronic kidney disease: A proof-of-principle study

Objective

To investigate if in-clinic measures of physical function and real-world measures of physical behavior and mobility effort are associated with one another and to determine if they predict future hospitalization in participants with chronic kidney disease (CKD).

Methods

In this secondary analysis, novel real-world measures of physical behavior and mobility effort, including the best 6-minute step count (B6SC), were derived from passively collected data from a thigh worn actigraphy sensor and compared to traditional in-clinic measures of physical function (e.g. 6-minute walk test (6MWT). Hospitalization status during 2 years of follow-up was determined from electronic health records. Correlation analyses were used to compare measures and Cox Regression analysis was used to compare measures with hospitalization.

Results

One hundred and six participants were studied (69  ±  13 years, 43% women). Mean  ±  SD baseline measures for 6MWT was 386  ±  66 m and B6SC was 524  ±  125 steps. Forty-four hospitalization events over 224 years of total follow-up occurred. Good separation was achieved for tertiles of 6MWT, B6SC and steps/day for hospitalization events. This pattern persisted in models adjusted for demographics (6MWT: HR  =  0.63 95% CI 0.43-0.93, B6SC: HR  =  0.75, 95% CI 0.56-1.02 and steps/day: HR  =  0.75, 95% CI 0.50-1.13) and further adjusted for morbidities (6MWT: HR  =  0.54, 95% CI 0.35-0.84, B6SC: HR  =  0.70, 95% CI 0.49-1.00 and steps/day: HR  =  0.69, 95% CI 0.43-1.09).

Conclusion

Digital health technologies can be deployed remotely, passively, and continuously to collect real-world measures of physical behavior and mobility effort that differentiate risk of hospitalization in patients with CKD.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

Can Digital Mobility Assessment Enhance the Clinical Assessment of Disease Severity in Parkinson's Disease?

BACKGROUND

Real-world walking speed (RWS) measured using wearable devices has the potential to complement the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) for motor assessment in Parkinson's disease (PD).

OBJECTIVE

Explore cross-sectional and longitudinal differences in RWS between PD and older adults (OAs), and whether RWS was related to motor disease severity cross-sectionally, and if MDS-UPDRS III was related to RWS, longitudinally.

METHODS

88 PD and 111 OA participants from ICICLE-GAIT (UK) were included. RWS was evaluated using an accelerometer at four time points. RWS was aggregated within walking bout (WB) duration thresholds. Between-group-comparisons in RWS between PD and OAs were conducted cross-sectionally, and longitudinally with mixed effects models (MEMs). Cross-sectional association between RWS and MDS-UPDRS III was explored using linear regression, and longitudinal association explored with MEMs.

RESULTS

RWS was significantly lower in PD (1.04 m/s) in comparison to OAs (1.10 m/s) cross-sectionally. RWS significantly decreased over time for both cohorts and decline was more rapid in PD by 0.02 m/s per year. Significant negative relationship between RWS and the MDS-UPDRS III only existed at a specific WB threshold (30 to 60 s, β= - 3.94 points, p = 0.047). MDS-UPDRS III increased significantly by 1.84 points per year, which was not related to change in RWS.

CONCLUSION

Digital mobility assessment of gait may add unique information to quantify disease progression remotely, but further validation in research and clinical settings is needed.

Daily-Living Freezing of Gait as Quantified Using Wearables in People With Parkinson Disease: Comparison With Self-Report and Provocation Tests

OBJECTIVE

Freezing of gait (FOG) is an episodic, debilitating phenomenon that is common among people with Parkinson disease. Multiple approaches have been used to quantify FOG, but the relationships among them have not been well studied. In this cross-sectional study, we evaluated the associations among FOG measured during unsupervised daily-living monitoring, structured in-home FOG-provoking tests, and self-report.

METHODS

Twenty-eight people with Parkinson disease and FOG were assessed using self-report questionnaires, percentage of time spent frozen (%TF) during supervised FOG-provoking tasks in the home while off and on dopaminergic medication, and %TF evaluated using wearable sensors during 1 week of unsupervised daily-living monitoring. Correlations between those 3 assessment approaches were analyzed to quantify associations. Further, based on the %TF difference between in-home off-medication testing and in-home on-medication testing, the participants were divided into those responding to Parkinson disease medication (responders) and those not responding to Parkinson disease medication (nonresponders) in order to evaluate the differences in the other FOG measures.

RESULTS

The %TF during unsupervised daily living was mild to moderately correlated with the %TF during a subset of the tasks of the in-home off-medication testing but not the on-medication testing or self-report. Responders and nonresponders differed in the %TF during the personal "hot spot" task of the provoking protocol while off medication (but not while on medication) but not in the total scores of the self-report questionnaires or the measures of FOG evaluated during unsupervised daily living.

CONCLUSION

The %TF during daily living was moderately related to FOG during certain in-home FOG-provoking tests in the off-medication state. However, this measure of FOG was not associated with self-report or FOG provoked in the on-medication state. These findings suggest that to fully capture FOG severity, it is best to assess FOG using a combination of all 3 approaches.

IMPACT

These findings suggest that several complementary approaches are needed to provide a complete assessment of FOG severity.

Parkinson's disease multimodal complex treatment improves gait performance: an exploratory wearable digital device-supported study

BACKGROUND

Wearable device-based parameters (DBP) objectively describe gait and balance impairment in Parkinson's disease (PD). We sought to investigate correlations between DBP of gait and balance and clinical scores, their respective changes throughout the inpatient multidisciplinary Parkinson's Disease Multimodal Complex Treatment (PD-MCT), and correlations between their changes.

METHODS

This exploratory observational study assessed 10 DBP and clinical scores at the start (T1) and end (T2) of a two-week PD-MCT of 25 PD in patients (mean age: 66.9 years, median HY stage: 2.5). Subjects performed four straight walking tasks under single- and dual-task conditions, and four balance tasks.

RESULTS

At T1, reduced gait velocity and larger sway area correlated with motor severity. Shorter strides during motor-motor dual-tasking correlated with motor complications. From T1 to T2, gait velocity improved, especially under dual-task conditions, stride length increased for motor-motor dual-tasking, and clinical scores measuring motor severity, balance, dexterity, executive functions, and motor complications changed favorably. Other gait parameters did not change significantly. Changes in motor complications, motor severity, and fear of falling correlated with changes in stride length, sway area, and measures of gait stability, respectively.

CONCLUSION

DBP of gait and balance reflect clinical scores, e.g., those of motor severity. PD-MCT significantly improves gait velocity and stride length and favorably affects additional DBP. Motor complications and fear of falling are factors that may influence the response to PD-MCT. A DBP-based assessment on admission to PD inpatient treatment could allow for more individualized therapy that can improve outcomes.

TRIAL REGISTRATION NUMBER AND DATE

DRKS00020948 number, 30-Mar-2020, retrospectively registered.

Association of clinical outcome assessments of mobility capacity and incident disability in community-dwelling older adults - a systematic review and meta-analysis

The objective of the present review is to synthesize all available research on the association between mobility capacity and incident disability in non-disabled older adults. MEDLINE, EMBASE and CINAHL databases were searched without any limits or restrictions until February 2021. Published reports of longitudinal cohort studies that estimated a direct association between baseline mobility capacity, assessed with a standardized outcome assessment, and subsequent development of disability, including initially non-disabled older adults were included. The risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool. Random-effect models were used to explore the objective. The certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. The main outcome measures were the pooled relative risks (RR) per one conventional unit per mobility assessment for incident disability. A total of 40 reports (85,515 participants at baseline) were included. For usual and fast gait speed, the RR per -0.1 m/s was 1.23 (95% CI: 1.18-1.28; 26,638 participants) and 1.28 (95% CI: 1.19-1.38; 8161 participants), respectively. Each point decrease in Short Physical Performance Battery score increased the risk of incident disability by 30% (RR = 1.30, 95% CI: 1.23-1.38; 9183 participants). The RR of incident disability by each second increase in Timed Up and Go test and Chair Rise Test performance was 1.15 (95% CI: 1.09-1.21; 30,426 participants) and 1.07 (95% CI: 1.04-1.10; 9450 participants), respectively. The review concludes that among community-dwelling non-disabled older adults, poor mobility capacity is a potent modifiable risk factor for incident disability. Mobility impairment should be mandated as a quality indicator of health for older people.

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement-the Mobilise-D study protocol

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.

On the use of wearable sensors as mobility biomarkers in the marketing authorization of new drugs: A regulatory perspective

The loss of mobility is a common trait in multiple health conditions (e.g., Parkinson's disease) and is associated with reduced quality of life. In this context, being able to monitor mobility in the real world, is important. Until recently, the technology was not mature enough for this; but today, miniaturized sensors and novel algorithms promise to monitor mobility accurately and continuously in the real world, also in pathological populations. However, before any such methodology can be employed to support the development and testing of new drugs in clinical trials, they need to be qualified by the competent regulatory agencies (e.g., European Medicines Agency). Nonetheless, to date, only very narrow scoped requests for regulatory qualification were successful. In this work, the Mobilise-D Consortium shares its positive experience with the European regulator, summarizing the two requests for Qualification Advice for the Mobilise-D methodologies submitted in October 2019 and June 2020, as well as the feedback received, which resulted in two Letters of Support publicly available for consultation on the website of the European Medicines Agency. Leveraging on this experience, we hereby propose a refined qualification strategy for the use of digital mobility outcome (DMO) measures as monitoring biomarkers for mobility in drug trials.

Mapping the global research landscape and hotspot of exercise therapy and chronic obstructive pulmonary disease: A bibliometric study based on the web of science database from 2011 to 2020

Background: The application of exercise therapy (ET) in chronic obstructive pulmonary disease (COPD) is generating increasing clinical efficacy and social-economic value. In this study, research trends, evolutionary processes and hot topics in this field are detailed, as well as predictions of future development directions.

Methods: Search for literature in the field of COPD and ET and analyze data to generate knowledge graphs using VOSiewer and CiteSpace software. The time frame for the search was from 2011 to January 2021. Then we extracted full-text key information (such as title, journal category, publication date, author, country and institution, abstract, and keyword) and obtained the co-citation analysis. Use hierarchal clustering analysis software developed by VOSviewer to map common citations, and use Citespace software to plot trend networks.

Results: The United States topped the list with 27.91% of the number of articles posted, followed by the UK at 25.44%. Imperial College London was the highest number of article publications in institutions, followed by Maastricht University and the University of Toronto. The Royal Brompton Harefield NHS Foundation Trust was one of many research institutions and currently holds the highest average citations per item (ACI) value, followed by Imperial College London and the University of Leuven. Judging from the number of publications related to ET and COPD, it is mainly published in cell biology, respiratory pulmonary diseases, and rehabilitation experiments study medicine. The European Respiration Journal is the most widely published in this field, followed by the International Journal of Chronic Obstructive Pulmonary Disease and Respiratory Medicine.

Conclusion: COPD combined with ET is widely used in clinical practice and is on the rise. A distinctive feature of the field is multidisciplinary integration. Rehabilitation research for COPD involves multidisciplinary collaboration, tissue engineering, and molecular biology mechanism studies to help patients remodel healthy breathing. Multidisciplinary rehabilitation measures provide a solid foundation for advancing clinical efficacy in the field of COPD.

Telemedicine for outpatient palliative care during COVID-19 pandemics: a longitudinal study

Objectives

During the COVID-19 pandemic, telemedicine (TM) emerged as an important mean to reduce risks of transmission, yet delivering the necessary care to patients. Our aim was to evaluate feasibility, characteristics and satisfaction for a TM service based on phone/video consultations for patients with cancer attending an outpatient palliative care clinic during COVID-19 pandemics.

Methods

A longitudinal observational study was conducted from April to December 2020. Consecutive patients were screened for video consultations feasibility. Either patients or their caregivers received video/phone consultations registering reason and intervention performed. Those contacted at least twice were eligible for experience of care assessment.

Results

Video consultations were feasible in 282 of 572 screened patients (49%, 95% CI 45% to 52%); 112 patients among the 572 had at least two phone/video consultations and 12 of them had one or more video consultations. Consultations were carried out with patients (56%), caregivers (30%) or both (14%). 63% of the consultations were requested by the patients/caregivers. Reasons for consultation included uncontrolled (66%) or new symptom onset (20%), therapy clarifications (37%) and updates on diagnostic tests (28%). Most interventions were therapy modifications (70%) and appointments’ rescheduling (51%). 49 patients and 19 caregivers were interviewed, reporting good care experience (average of 1–5 satisfaction score of 3.9 and 4.2, respectively). The majority (83% and 84%) declared they would use TM after the pandemics.

Conclusions

Although feasibility is still limited for some patients, TM can be a satisfactory alternative to in-person visits for palliative care patients in need of limiting access to the hospital.

Smartphone-Based Body Location-Independent Functional Mobility Analysis in Patients with Parkinson’s Disease: A Step towards Precise Medicine

Ecological evaluation of gait using mobile technologies provides crucial information regarding the evolution of symptoms in Parkinson’s disease (PD). However, the reliability and validity of such information may be influenced by the smartphone’s location on the body. This study analyzed how the smartphone location affects the assessment of PD patients’ gait in a free-living environment. Twenty PD patients (mean ± SD age, 64.3 ± 10.6 years; 9 women (45%) performed 3 trials of a 250 m outdoor walk using smartphones in 5 different body locations (pants pocket, belt, hand, shirt pocket, and a shoulder bag). A method to derive gait-related metrics from smartphone sensors is presented, and its reliability is evaluated between different trials as well as its concurrent validity against optoelectronic and smartphone criteria. Excellent relative reliability was found with all intraclass correlation coefficient values above or equal to 0.85. High absolute reliability was observed in 21 out of 30 comparisons. Bland-Altman analysis revealed a high level of agreement (LoA between 4.4 and 17.5%), supporting the use of the presented method. This study advances the use of mobile technology to accurately and reliably quantify gait-related metrics from PD patients in free-living walking regardless of the smartphone’s location on the body.

Automated Analysis of Drawing Process to Estimate Global Cognition in Older Adults: Preliminary International Validation on the US and Japan Data Sets

BACKGROUND

With the aging of populations worldwide, early detection of cognitive impairments has become a research and clinical priority, particularly to enable preventive intervention for dementia. Automated analysis of the drawing process has been studied as a promising means for lightweight, self-administered cognitive assessment. However, this approach has not been sufficiently tested for its applicability across populations.

OBJECTIVE

The aim of this study was to evaluate the applicability of automated analysis of the drawing process for estimating global cognition in community-dwelling older adults across populations in different nations.

METHODS

We collected drawing data with a digital tablet, along with Montreal Cognitive Assessment (MoCA) scores for assessment of global cognition, from 92 community-dwelling older adults in the United States and Japan. We automatically extracted 6 drawing features that characterize the drawing process in terms of the drawing speed, pauses between drawings, pen pressure, and pen inclinations. We then investigated the association between the drawing features and MoCA scores through correlation and machine learning-based regression analyses.

RESULTS

We found that, with low MoCA scores, there tended to be higher variability in the drawing speed, a higher pause:drawing duration ratio, and lower variability in the pen's horizontal inclination in both the US and Japan data sets. A machine learning model that used drawing features to estimate MoCA scores demonstrated its capability to generalize from the US dataset to the Japan dataset (R2=0.35; permutation test, P<.001).

CONCLUSIONS

This study presents initial empirical evidence of the capability of automated analysis of the drawing process as an estimator of global cognition that is applicable across populations. Our results suggest that such automated analysis may enable the development of a practical tool for international use in self-administered, automated cognitive assessment.

Responsibility, second opinions and peer-disagreement: ethical and epistemological challenges of using AI in clinical diagnostic contexts

In this paper, we first classify different types of second opinions and evaluate the ethical and epistemological implications of providing those in a clinical context. Second, we discuss the issue of how artificial intelligent (AI) could replace the human cognitive labour of providing such second opinion and find that several AI reach the levels of accuracy and efficiency needed to clarify their use an urgent ethical issue. Third, we outline the normative conditions of how AI may be used as second opinion in clinical processes, weighing the benefits of its efficiency against concerns of responsibility attribution. Fourth, we provide a 'rule of disagreement' that fulfils these conditions while retaining some of the benefits of expanding the use of AI-based decision support systems (AI-DSS) in clinical contexts. This is because the rule of disagreement proposes to use AI as much as possible, but retain the ability to use human second opinions to resolve disagreements between AI and physician-in-charge. Fifth, we discuss some counterarguments.

Mobility endpoints in marketing authorisation of drugs: what gets the European medicines agency moving?

BACKGROUND

Mobility is defined as the ability to independently move around the environment and is a key contributor to quality of life, especially in older age. The aim of this study was to evaluate the use of mobility as a decisive outcome for the marketing authorisation of drugs by the European Medicines Agency (EMA).

METHODS

Fifteen therapeutic areas which commonly lead to relevant mobility impairments and alter the quantity and/or the quality of walking were selected: two systemic neurological diseases, four conditions primarily affecting exercise capacity, seven musculoskeletal diseases and two conditions representing sensory impairments. European Public Assessment Reports (EPARs) published by the EMA until September 2020 were examined for mobility endpoints included in their 'main studies'. Clinical study registries and primary scientific publications for these studies were also reviewed.

RESULTS

Four hundred and eighty-four EPARs yielded 186 relevant documents with 402 'main studies'. The EPARs reported 153 primary and 584 secondary endpoints which considered mobility; 70 different assessment tools (38 patient-reported outcomes, 13 clinician-reported outcomes, 8 performance outcomes and 13 composite endpoints) were used. Only 15.7% of those tools distinctly informed on patients' mobility status. Out of 402, 105 (26.1%) of the 'main studies' did not have any mobility assessment. Furthermore, none of these studies included a digital mobility outcome.

CONCLUSIONS

For conditions with a high impact on mobility, mobility assessment was given little consideration in the marketing authorisation of drugs by the EMA. Where mobility impairment was considered to be a relevant outcome, questionnaires or composite scores susceptible to reporting biases were predominantly used.