Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

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.

Developing effective strategies to optimize physical activity and cardiorespiratory fitness in the long Covid population- The need for caution and objective assessment.

The Post Covid-19 Condition (commonly known as Long Covid) has been defined by the World Health Organisation as occurring in individuals with a history of probable or confirmed SARS CoV 2 infection, usually within 3 months from the onset of acute Covid-19 infection with symptoms that last for at least two months which cannot be explained by an alternative diagnosis. Long Covid is associated with over two hundred recognised symptoms and affects tens of millions of people worldwide. Widely reported reductions in quality of life(QoL) and functional status are caused by extremely sensitive and cyclical symptom profiles that are augmented following exposure to physical, emotional, orthostatic, and cognitive stimuli. This manifestation prevents millions of people from engaging in routine activities of daily living (ADLs) and has important health and well-being, social and economic impacts. Post-exertional symptom exacerbation (PESE) (also known as post-exertional malaise) is an exacerbation in the severity of fatigue and other symptoms following physical, emotional, orthostatic and cognitive tasks. Typically, this will occur 24-72 h after "over-exertion" and can persist for several days and even weeks. It is a hallmark symptom of Long Covid with a reported prevalence of 86%. The debilitating nature of PESE prevents patients from engaging in physical activity which impacts functional status and QoL. In this review, the authors present an update to the literature relating to PESE in Long Covid and make the case for evidence-based guidelines that support the design and implementation of safe rehabilitation approaches for people with Long Covid. This review also considers the role of objective monitoring to quantify a patient's response to external stimuli which can be used to support the safe management of Long Covid and inform decisions relating to engagement with any stimuli that could prompt an exacerbation of symptoms.

No sex differences in oxygen uptake or extraction kinetics in the moderate or heavy exercise intensity domains.

The integrative response to exercise differs between sexes, with oxidative energy contribution purported as a potential mechanism. The present study investigated whether this difference was evident in the kinetics of oxygen uptake (V̇o2) and extraction (HHb + Mb) during exercise. Sixteen adults (8 males, 8 females, age: 27 ± 5 yr) completed three experimental visits. Incremental exercise testing was performed to obtain lactate threshold and V̇o2peak. Subsequent visits involved three 6-min cycling bouts at 80% of lactate threshold and one 30-min bout at a work rate of 30% between the lactate threshold and power at V̇o2peak. Pulmonary gas exchange and near-infrared spectroscopy of the vastus lateralis were used to continuously sample V̇o2 and HHb + Mb, respectively. The phase II V̇o2 kinetics were quantified using monoexponential curves during moderate and heavy exercise. Slow component amplitudes were also quantified for the heavy-intensity domain. Relative V̇o2peak values were not different between sexes (P = 0.111). Males achieved ∼30% greater power outputs (P = 0.002). In the moderate- and heavy-intensity domains, the relative amplitude of the phase II transition was not different between sexes for V̇o2 (∼24 and ∼40% V̇o2peak, P ≥ 0.179) and HHb + Mb (∼20 and ∼32% ischemia, P ≥ 0.193). Similarly, there were no sex differences in the time constants for V̇o2 (∼28 s, P ≥ 0.385) or HHb + Mb (∼10 s, P ≥ 0.274). In the heavy-intensity domain, neither V̇o2 (P ≥ 0.686) or HHb + Mb (P ≥ 0.432) slow component amplitudes were different between sexes. The oxidative response to moderate- and heavy-intensity exercises did not differ between males and females, suggesting similar dynamic responses of oxidative metabolism during intensity-matched exercise.NEW & NOTEWORTHY This study demonstrated no sex differences in the oxidative response to moderate- and heavy-intensity cycling exercise. The change in oxygen uptake and deoxyhemoglobin were modeled with monoexponential curve fitting, which revealed no differences in the rate of oxidative energy provision between sexes. This provides insight into previously reported sex differences in the integrative response to exercise.

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.

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.

Cognitive behavioural therapy combined with physical activity behavioural modification strategies during pulmonary rehabilitation in patients with COPD.

Introduction: Patients with COPD who exhibit elevated levels of anxiety and/or depression are typically less able to improve symptoms and physical activity levels following a programme of pulmonary rehabilitation (PR). The objective of the present study was to provide proof of concept that offering an intervention comprising cognitive behavioural therapy (CBT) alongside physical activity behavioural modification strategies (BPA) during PR is more effective in improving physical activity outcomes compared to PR and CBT alone. Methods: 32 patients with COPD (mean±sd forced expiratory volume in 1 s 42±14% predicted) were assigned 1:1 to receive PR+CBT+BPA or PR+CBT. BPA comprised motivational interviews, step-count monitoring, feedback using a pedometer and goal setting. Assessments included accelerometer-derived steps per day, movement intensity, 6-min walk distance (6MWD) and Hospital Anxiety and Depression Scale (HADS) scores. Results: The magnitude of improvement across physical activity outcomes was greater for the PR+CBT+BPA compared to the PR+CBT intervention (by 829 steps per day (p=0.029) and by 80±39 vector magnitude units (p=0.042), respectively). Compared to PR and CBT alone, the PR+CBT+BPA intervention induced greater clinically meaningful improvements in HADS anxiety scores (by -2 units, 95% CI -4-1 units) and 6MWD (by 33±20 m). Conclusions: Providing anxious and/or depressed patients with COPD with a combined intervention of CBT and BPA during PR presents more favourable improvements in physical activity outcome measures compared to CBT alone during PR.

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.

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.

The effect of COVID rehabilitation for ongoing symptoms Post HOSPitalisation with COVID-19 (PHOSP-R): protocol for a randomised parallel group controlled trial on behalf of the PHOSP consortium.

INTRODUCTION: Many adults hospitalised with COVID-19 have persistent symptoms such as fatigue, breathlessness and brain fog that limit day-to-day activities. These symptoms can last over 2 years. Whilst there is limited controlled studies on interventions that can support those with ongoing symptoms, there has been some promise in rehabilitation interventions in improving function and symptoms either using face-to-face or digital methods, but evidence remains limited and these studies often lack a control group. METHODS AND ANALYSIS: This is a nested single-blind, parallel group, randomised control trial with embedded qualitative evaluation comparing rehabilitation (face-to-face or digital) to usual care and conducted within the PHOSP-COVID study. The aim of this study is to determine the effectiveness of rehabilitation interventions on exercise capacity, quality of life and symptoms such as breathlessness and fatigue. The primary outcome is the Incremental Shuttle Walking Test following the eight week intervention phase. Secondary outcomes include measures of function, strength and subjective assessment of symptoms. Blood inflammatory markers and muscle biopsies are an exploratory outcome. The interventions last eight weeks and combine symptom-titrated exercise therapy, symptom management and education delivered either in a face-to-face setting or through a digital platform ( www.yourcovidrecovery.nhs.uk ). The proposed sample size is 159 participants, and data will be intention-to-treat analyses comparing rehabilitation (face-to-face or digital) to usual care. ETHICS AND DISSEMINATION: Ethical approval was gained as part of the PHOSP-COVID study by Yorkshire and the Humber Leeds West Research NHS Ethics Committee, and the study was prospectively registered on the ISRCTN trial registry (ISRCTN13293865). Results will be disseminated to stakeholders, including patients and members of the public, and published in appropriate journals. Strengths and limitations of this study • This protocol utilises two interventions to support those with ongoing symptoms of COVID-19 • This is a two-centre parallel-group randomised controlled trial • The protocol has been supported by patient and public involvement groups who identified treatments of symptoms and activity limitation as a top priority.

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.

Feasibility and acceptability of a physical activity behavioural modification tele-coaching intervention in lung transplant recipients.

BACKGROUND: Despite improvements in pulmonary function following lung transplantation (LTx), physical activity levels remain significantly lower than the general population. To date, there is little research investigating interventions to improve daily physical activity in LTx recipients. This study assessed the feasibility and acceptability of a novel, 12-weeks physical activity tele-coaching (TC) intervention in LTx recipients. METHODS: Lung transplant recipients within 2 months of hospital discharge were recruited and randomised (1:1) to TC or usual care (UC). TC consists of a pedometer and smartphone app, allowing transmission of activity data to a platform that provides feedback, activity goals, education, and contact with the researcher as required. Recruitment and retention, occurrence of adverse events, intervention acceptability and usage were used to assess feasibility. RESULTS: Key criteria for progressing to a larger study were met. Of the 15 patients eligible, 14 were recruited and randomised to TC or UC and 12 completed (67% male; mean ± SD age; 58 ± 7 years; COPD n = 4, ILD n = 6, CF n = 1, PH n = 1): TC (n = 7) and UC (n = 5). TC was well accepted by patients, with 86% indicating that they enjoyed taking part. Usage of the pedometer was excellent, with all patients wearing it for over 90% of days and rating the pedometer and telephone contact as the most vital aspects. There were no adverse events related to the intervention. After 12 weeks, only TC displayed improvements in accelerometry steps/day (by 3475 ± 3422; p = .036) and movement intensity (by 153 ± 166 VMU; p = .019), whereas both TC and UC groups exhibited clinically important changes in physical SF-36 scores (by 11 ± 14 and 7 ± 9 points, respectively). CONCLUSION: TC appears to be a feasible, safe, and well-accepted intervention in LTx.

COVID-19 and the long-term cardio-respiratory and metabolic health complications.

Severe acute respiratory syndrome coronavirus type-2 (SARS-CoV-2) transmission continues to impact people globally. Whilst the acute symptoms and management strategies are well documented, millions of people globally are experiencing a prolonged and debilitating symptom profile that is reported to last months and even years. COVID-19 is a multi-system disease however the magnitude of the effects and its associated legacy is presently not well understood. Early reports indicate that multidisciplinary approaches between clinical and non-clinical entities are needed to provide effective and rehabilitative patient support pathways and restore pre-COVID-19 quality of life and functional status. Accordingly, this review provides a summary of the impact on cardiovascular, inflammatory, respiratory, and musculoskeletal function following an acute COVID-19 infection along with the prolonged effects of long-COVID.

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

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. TRIAL REGISTRATION NUMBER: ISRCTN (12246987).

Effect of interval compared to continuous exercise training on physiological responses in patients with chronic respiratory diseases: A systematic review and meta-analysis.

BackgroundCurrent evidence suggests that interval exercise training (IET) and continuous exercise training (CET) produce comparable benefits in exercise capacity, cardiorespiratory fitness and symptoms in patients with chronic obstructive pulmonary disease (COPD). However, the effects of these modalities have only been reviewed in patients with COPD. This meta-analysis compares the effectiveness of IET versus CET on exercise capacity, cardiorespiratory fitness and exertional symptoms in patients with chronic respiratory diseases (CRDs). Methods: PubMed, CINHAL, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL) and Nursing and Allied health were searched for randomised controlled trials from inception to September 2020. Eligible studies included the comparison between IET and CET, reporting measures of exercise capacity, cardiorespiratory fitness and symptoms in individuals with CRDs. Results: Thirteen randomised control trials (530 patients with CRDs) with fair to good quality on the PEDro scale were included. Eleven studies involved n = 446 patients with COPD, one involved n = 24 patients with cystic fibrosis (CF) and one n = 60 lung transplantation (LT) candidates. IET resulted in greater improvements in peak work rate (WRpeak) (2.40 W, 95% CI: 0.83 to 3.97 W; p = 0.003) and lower exercise-induced dyspnoea (-0.47, 95% CI: -0.86 to 0.09; p = 0.02) compared to CET; however, these improvements did not exceed the minimal important difference for these outcomes. No significant differences in peak values for oxygen uptake (VO2peak), heart rate (HRpeak), minute ventilation (VEpeak), lactate threshold (LAT) and leg discomfort were found between the interventions. Conclusions: IET is superior to CET in improving exercise capacity and exercise-induced dyspnoea sensations in patients with CRDs; however, the extent of the clinical benefit is not considered clinically meaningful.