Concurrent validation of activity monitors in patients with rheumatoid arthritis

Person-Specific Template Matching Using a Dynamic Time Warping Step-Count Algorithm for Multiple Walking Activities

This study aimed to develop and evaluate a new step-count algorithm, StepMatchDTWBA, for the accurate measurement of physical activity using wearable devices in both healthy and pathological populations. We conducted a study with 30 healthy volunteers wearing a wrist-worn MOX accelerometer (Maastricht Instruments, NL). The StepMatchDTWBA algorithm used dynamic time warping (DTW) barycentre averaging to create personalised templates for representative steps, accounting for individual walking variations. DTW was then used to measure the similarity between the template and accelerometer epoch. The StepMatchDTWBA algorithm had an average root-mean-square error of 2 steps for healthy gaits and 12 steps for simulated pathological gaits over a distance of about 10 m (GAITRite walkway) and one flight of stairs. It outperformed benchmark algorithms for the simulated pathological population, showcasing the potential for improved accuracy in personalised step counting for pathological populations. The StepMatchDTWBA algorithm represents a significant advancement in accurate step counting for both healthy and pathological populations. This development holds promise for creating more precise and personalised activity monitoring systems, benefiting various health and wellness applications.

Smartphone Pedometer Sensor Application for Evaluating Disease Activity and Predicting Comorbidities in Patients with Rheumatoid Arthritis: A Validation Study

Smartphone-based pedometer sensor telemedicine applications could be useful for measuring disease activity and predicting the risk of developing comorbidities, such as pulmonary or cardiovascular disease, in patients with rheumatoid arthritis (RA), but the sensors have not been validated in this patient population. The aim of this study was to validate step counting with an activity-tracking application running the inbuilt Android smartphone pedometer virtual sensor in patients with RA. Two Android-based smartphones were tested in a treadmill test-bed setup at six walking speeds and compared to manual step counting as the gold standard. Guided by a facilitator, the participants walked 100 steps at each test speed, from 2.5 km/h to 5 km/h, wearing both devices simultaneously in a stomach pouch. A computer automatically recorded both the manually observed and the sensor step count. The overall difference in device step counts versus the observed was 5.9% mean absolute percentage error. Highest mean error was at the 2.5 km/h speed tests, where the mean error of the two devices was 18.5%. Both speed and cadence were negatively correlated to the absolute percentage error, which indicates that the greater the speed and cadence, the lower the resulting step counting error rate. There was no correlation between clinical parameters and absolute percentage error. In conclusion, the activity-tracking application using the inbuilt Android smartphone pedometer virtual sensor is valid for step counting in patients with RA. However, walking at very low speed and cadence may represent a challenge.

Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies

BACKGROUND

Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data.

CONCLUSION

If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a 'bring your own device'-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.

Reliability of activity monitors for physical activity assessment in patients with musculoskeletal disorders: A systematic review

BACKGROUND

Activity monitors have been introduced in the last years to objectively measure physical activity to help physicians in the management of musculoskeletal patients.

OBJECTIVE

This systematic review aimed at describing the assessment of physical activity by commercially available portable activity monitors in patients with musculoskeletal disorders.

METHODS

PubMed, Embase, PEDro, Web of Science, Scopus and CENTRAL databases were systematically searched from inception to June 11th, 2020. We considered as eligible observational studies with: musculoskeletal patients; physical activity measured by wearable sensors based on inertial measurement units; comparisons performed with other tools; outcomes consisting of number of steps/day, activity/inactivity time, or activity counts/day.

RESULTS

Out of 595 records, after removing duplicates, title/abstract and full text screening, 10 articles were included. We noticed a wide heterogeneity in the wearable devices, that resulted to be 10 different types. Patients included suffered from rheumatoid arthritis, osteoarthritis, juvenile idiopathic arthritis, polymyalgia rheumatica, and fibromyalgia. Only 3 studies compared portable activity trackers with objective measurement tools.

CONCLUSIONS

Taken together, this systematic review showed that activity monitors might be considered as useful to assess physical activity in patients with musculoskeletal disorders, albeit, to date, the high device heterogeneity and the different algorithms still prevent their standardization.

Capturing accelerometer outputs in healthy volunteers under normal and simulated-pathological conditions using ML classifiers

Wearable devices offer a possible solution for acquiring objective measurements of physical activity. Most current algorithms are derived using data from healthy volunteers. It is unclear whether such algorithms are suitable in specific clinical scenarios, such as when an individual has altered gait. We hypothesized that algorithms trained on healthy population will result in less accurate results when tested in individuals with altered gait. We further hypothesized that algorithms trained on simulated-pathological gait would prove better at classifying abnormal activity. We studied healthy volunteers to assess whether activity classification accuracy differed for those with healthy and simulated-pathological conditions. Healthy participants (n=30) were recruited from the University of Leeds to perform nine predefined activities under healthy and simulated-pathological conditions. Activities were captured using a wrist-worn MOX accelerometer (Maastricht Instruments, NL). Data were analyzed based on the Activity-Recognition-Chain process. We trained a Neural-Network, Random-Forests, k-Nearest-Neighbors (k-NN), Support-Vector-Machines (SVM) and Naive Bayes models to classify activity. Algorithms were trained four times; once with `healthy' data, and once with `simulated-pathological data' for each of activity-type and activity-task classification. In activity-type instances, the SVM provided the best results; the accuracy was 98.4% when the algorithm was trained and then tested with unseen data from the same group of healthy individuals. Accuracy dropped to 52.8% when tested on simulated-pathological data. When the model was retrained with simulated-pathological data, prediction accuracy for the corresponding test set was 96.7%. Algorithms developed on healthy data are less accurate for pathological conditions. When evaluating pathological conditions, classifier algorithms developed using data from a target sub-population can restore accuracy to above 95%.

Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis

BACKGROUND

Inertial measurement units (IMUs) offer the ability to measure walking gait through a variety of biomechanical outcomes (e.g., spatiotemporal, kinematics, other). Although many studies have assessed their validity and reliability, there remains no quantitive summary of this vast body of literature. Therefore, we aimed to conduct a systematic review and meta-analysis to determine the i) concurrent validity and ii) test-retest reliability of IMUs for measuring biomechanical gait outcomes during level walking in healthy adults.

METHODS

Five electronic databases were searched for journal articles assessing the validity or reliability of IMUs during healthy adult walking. Two reviewers screened titles, abstracts, and full texts for studies to be included, before two reviewers examined the methodological quality of all included studies. When sufficient data were present for a given biomechanical outcome, data were meta-analyzed on Pearson correlation coefficients (r) or intraclass correlation coefficients (ICC) for validity and reliability, respectively. Alternatively, qualitative summaries of outcomes were conducted on those that could not be meta-analyzed.

RESULTS

A total of 82 articles, assessing the validity or reliability of over 100 outcomes, were included in this review. Seventeen biomechanical outcomes, primarily spatiotemporal parameters, were meta-analyzed. The validity and reliability of step and stride times were found to be excellent. Similarly, the validity and reliability of step and stride length, as well as swing and stance time, were found to be good to excellent. Alternatively, spatiotemporal parameter variability and symmetry displayed poor to moderate validity and reliability. IMUs were also found to display moderate reliability for the assessment of local dynamic stability during walking. The remaining biomechanical outcomes were qualitatively summarized to provide a variety of recommendations for future IMU research.

CONCLUSIONS

The findings of this review demonstrate the excellent validity and reliability of IMUs for mean spatiotemporal parameters during walking, but caution the use of spatiotemporal variability and symmetry metrics without strict protocol. Further, this work tentatively supports the use of IMUs for joint angle measurement and other biomechanical outcomes such as stability, regularity, and segmental accelerations. Unfortunately, the strength of these recommendations are limited based on the lack of high-quality studies for each outcome, with underpowered and/or unjustified sample sizes (sample size median 12; range: 2-95) being the primary limitation.

Engagement and Participant Experiences With Consumer Smartwatches for Health Research: Longitudinal, Observational Feasibility Study

BACKGROUND

Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated.

OBJECTIVE

This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA).

METHODS

For the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis.

RESULTS

A total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day.

CONCLUSIONS

This study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/10238.

Reliability and validity of the Kinect V2 for the assessment of lower extremity rehabilitation exercises

BACKGROUND

Besides its initial use as a video gaming system the Kinect might also be suitable to capture human movements in the clinical context. However, the system's reliability and validity to capture rehabilitation exercises is unclear.

RESEARCH QUESTION

The purpose of this study was to evaluate the test-retest reliability of lower extremity kinematics during squat, hip abduction and lunge exercises captured by the Kinect and to evaluate the agreement to a reference 3D camera-based motion system.

METHODS

Twenty-one healthy individuals performed five repetitions of each lower limb exercise on two different days. Movements were simultaneously assessed by the Kinect and the reference 3D motion system. Joint angles and positions of the lower limb were calculated for sagittal and frontal plane. For the inter-session reliability and the agreement between the two systems standard error of measurement (SEM), bias with limits of agreement (LoA) and Pearson Correlation Coefficient (r) were calculated.

RESULTS

Parameters indicated varying reliability for the assessed joint angles and positions and decreasing reliability with increasing task complexity. Across all exercises, measurement deviations were shown especially for small movement amplitudes. Variability was acceptable for joint angles and positions during the squat, partially acceptable during the hip abduction and predominately inacceptable during the lunge. The agreement between systems was characterized by systematic errors. Overestimations by the Kinect were apparent for hip flexion during the squat and hip abduction/adduction during the hip abduction exercise as well as for the knee positions during the lunge. Knee and hip flexion during hip abduction and lunge were underestimated by the Kinect.

SIGNIFICANCE

The Kinect system can reliably assess lower limb joint angles and positions during simple exercises. The validity of the system is however restricted. An application in the field of early orthopedic rehabilitation without further development of post-processing techniques seems so far limited.

Inertial sensors versus standard systems in gait analysis: a systematic review and meta-analysis

INTRODUCTION

The increasing popularity of inertial sensors in clinical practice is not supported by precise information on their reliability or guidelines for their use in rehabilitation. The authors investigated the state of the literature concerning the use of inertial sensors for gait analysis in both healthy and pathological adults comparing traditional systems. Furthermore, trying to define directions for clinicians.

EVIDENCE ACQUISITION

In accordance with the PRISMA statement, authors searched in PubMed, Web of Science and Scopus all paper published from January 1st, 2005 until December 31st, 2017. They included both healthy and pathological adults' subjects as population, wearable or inertial sensors used for gait analysis and compared with classical gait analysis performed in a Motion Lab as intervention and comparison, gait parameters as outcomes. Considering the methodological quality, authors focused on: sample; description of the study; type of gait analysis used for comparison; type of sensor; sensor placement on the body; gait task requested.

EVIDENCE SYNTHESIS

From a total of 888 articles, 16 manuscripts were selected and 7 of them were considered for meta-analysis for different gait parameters. Demographic data, tested devices, reference systems, test procedures and outcomes were analyzed.

CONCLUSIONS

Our results show a good agreement between inertial sensors and classical gait analysis for some gait parameters, supporting their use as a solution for capturing kinematic information over an extended space and time and even outside a laboratory in real-life conditions. Authors can support the use of portable inertial sensors for a practical gait analysis in clinical setting with good reliability. It will then be the experience of the clinician to direct the decision-making process.

Use of Physical Activity Monitors in Rheumatic Populations

PURPOSE OF REVIEW

The purpose of this review paper is to provide an overview of the recent research using physical activity monitors in rheumatic populations including those with osteoarthritis, rheumatoid arthritis, systemic lupus erythematosus, and fibromyalgia.

RECENT FINDINGS

Recent research demonstrates increased use of physical activity monitors in these populations, especially in those with osteoarthritis. Results from cross-sectional, longitudinal, and intervention studies highlight that physical activity levels are below recommended guidelines, yet evidence suggests benefits such as improving pain, fatigue, function, and overall well-being. While the use of physical activity monitors in rheumatic populations is increasing, more research is needed to better understand physical activity levels in these populations, the effects of activity on relevant clinical outcomes, and how monitors can be used to help more individuals reach physical activity guidelines.

Preliminary concurrent validity of the Fitbit-Zip and ActiGraph activity monitors for measuring steps in people with polymyalgia rheumatica

BACKGROUND

Activity monitors provide objective measurements of physical activity, however, the accuracy of these devices in people with polymyalgia rheumatica (PMR) is unknown. Therefore, this study aimed to obtain preliminary evidence of the accuracy of two activity monitors and explore if clinical and gait-related factors altered device accuracy in people with PMR.

METHODS

The ActiGraph with low frequency extension (+LFE) and standard (-LFE) algorithms, Fitbit-Zip (waist) and Fitbit-Zip (shirt) were concurrently tested using a two-minute walk test (2MWT) and stairs test in 27 people with PMR currently treated with prednisolone. To determine accuracy, activity monitor step-count was compared to a gold-standard step-count (GSSC; calculated from video recording) using Bland-Altman plots.

RESULTS

The Fitbit-Zip (waist) achieved closest agreement to the GSSC for the 2MWT (mean bias (95%CI): 10 (-3, 23); 95%LOA: -55, 74). The ActiGraph (+LFE) achieved closest agreement to the GSSC for the stairs test (mean bias (95%CI): 0 (-1, 1); 95%LOA: -5, 5). The ActiGraph (-LFE) performed poorly in both tests. All devices demonstrated reduced accuracy in participants with lower gait velocity, reduced stride length, longer double-limb support phase and greater self-reported functional impairment.

CONCLUSION

Our preliminary results suggest that in controlled conditions, the Fitbit-Zip fairly accurately measures step-count during walking in people with PMR receiving treatment. However, device error was greater than data published in healthy people. The ActiGraph may not be recommended without activation of the LFE. We identified clinical and gait-related factors associated with higher levels of functional impairment that reduced device accuracy. Further work is required to evaluate the validity of the activity monitors in field conditions.

Clinical Gait Evaluation of Patients with Lumbar Spine Stenosis

OBJECTIVE

The third generation Intelligent Device for Energy Expenditure and Activity (IDEEA3, MiniSun, CA) has been developed for clinical gait evaluation, and this study was designed to evaluate the accuracy and reliability of IDEEA3 for the gait measurement of lumbar spinal stenosis (LSS) patients.

METHODS

Twelve healthy volunteers were recruited to compare gait cycle, cadence, step length, velocity, and number of steps between a motion analysis system and a high-speed video camera. Twenty hospitalized LSS patients were recruited for the comparison of the five parameters between the IDEEA3 and GoPro camera. Paired t-test, intraclass correlation coefficient, concordance correlation coefficient, and Bland-Altman plots were used for the data analysis.

RESULTS

The ratios of GoPro camera results to motion analysis system results, and the ratios of IDEEA3 results to GoPro camera results were all around 1.00. All P-values of paired t-tests for gait cycle, cadence, step length, and velocity were greater than 0.05, while all the ICC and CCC results were above 0.950 with P < 0.001.

CONCLUSIONS

The measurements for gait cycle, cadence, step length, velocity, and number of steps with the GoPro camera are highly consistent with the measurements with the motion analysis system. The measurements for IDEEA3 are consistent with those for the GoPro camera. IDEEA3 can be effectively used in the gait measurement of LSS patients.

Clinical gait evaluation of patients with knee osteoarthritis

Knee osteoarthritis (KOA) is the most common osteoarthritis in lower limbs, and gait measurement is important to evaluate walking function of KOA patients before and after treatment. The third generation Intelligent Device for Energy Expenditure and Activity (IDEEA3) is a portable gait analysis system to evaluate gaits. This study is to evaluate the accuracy and reliability of IDEEA3 for gait measurement of KOA patients. Meanwhile, gait differences between KOA patients and healthy subjects are examined. Twelve healthy volunteers were recruited for measurement comparison of gait cycle (GC), cadence, step length, velocity and step counts between a motion analysis system and a high-speed camera (GoPro Hero3). Twenty-three KOA patients were recruited for measurement comparison of former five parameters between GoPro Hero3 and IDEEA3. Paired t-test, Concordance Correlation Coefficient (CCC) and Intraclass Correlation Coefficient (ICC) were used for data analysis. All p-values of paired t-tests for GC, cadence, step length and velocity were greater than 0.05 while all CCC and ICC results were above 0.95. The measurements of GC, cadence, step length, velocity and step counts by motion analysis system are highly consistent with the measurements by GoPro Hero3. The measurements of former parameters by GoPro Hero3 are not statistically different from the measurements by IDEEA3. IDEEA3 can be effectively used for the measurement of GC, cadence, step length, velocity and step counts in KOA patients. The KOA patients walk with longer GC, lower cadence, shorter step length and slower speed compared with healthy subjects in natural speed with flat shoes.

Polestriding Intervention Improves Gait and Axial Symptoms in Mild to Moderate Parkinson Disease

OBJECTIVE

To evaluate the effects of 12-week polestriding intervention on gait and disease severity in people with mild to moderate Parkinson disease (PD).

DESIGN

A-B-A withdrawal study design.

SETTING

Outpatient movement disorder center and community facility.

PARTICIPANTS

Individuals (N=17; 9 women [53%] and 8 men [47%]; mean age, 63.7±4.9y; range, 53-72y) with mild to moderate PD according to United Kingdom brain bank criteria with Hoehn & Yahr score ranging from 2.5 to 3.0 with a stable medication regimen and ability to tolerate "off" medication state.

INTERVENTIONS

Twelve-week polestriding intervention with 12-week follow-up.

MAIN OUTCOME MEASURES

Gait was evaluated using several quantitative temporal, spatial, and variability measures. In addition, disease severity was assessed using clinical scales such as Unified Parkinson's Disease Rating Scale (UPDRS), Hoehn & Yahr scale, and Parkinson's Disease Questionnaire-39.

RESULTS

Step and stride lengths, gait speed, and step-time variability were improved significantly (P<.05) because of 12-week polestriding intervention. Also, the UPDRS motor score, the UPDRS axial score, and the scores of UPDRS subscales on walking and balance improved significantly after the intervention.

CONCLUSIONS

Because increased step-time variability and decreased step and stride lengths are associated with PD severity and an increased risk of falls in PD, the observed improvements suggest that regular practice of polestriding may reduce the risk of falls and improve mobility in people with PD.

Using Commercial Activity Monitors to Measure Gait in Patients with Suspected iNPH: Implications for Ambulatory Monitoring

Objectives: This study seeks to validate the use of activity monitors to detect and record gait abnormalities, potentially identifying patients with idiopathic normal pressure hydrocephalus (iNPH) prior to the onset of cognitive or urinary symptoms.

Methods: This study compared the step counts of four common activity monitors (Omron Step Counter HJ-113, New Lifestyles 2000, Nike Fuelband, and Fitbit Ultra) to an observed step count in 17 patients with confirmed iNPH.

Results: Of the four devices, the Fitbit Ultra (Fitbit, Inc., San Francisco, CA) provided the most accurate step count. The correlation with the observed step count was significantly higher (p<0.009) for the Fitbit Ultra than for any of the other three devices.

Conclusions: These preliminary findings suggest that existing activity monitors have variable efficacy in the iNPH patient population and that the MEMS tri-axial accelerometer and algorithm of the Fitbit Ultra provides the most accurate gait measurements of the four devices tested.

Subjective and objective levels of physical activity and their association with cardiorespiratory fitness in rheumatoid arthritis patients

Introduction

The aims of the present study were: (a) to examine the agreement between subjective (assessed via the International Physical Activity Questionnaire; IPAQ) and objective (accelerometry; GT3X) physical activity (PA) levels in patients with rheumatoid arthritis (RA), and (b) to evaluate the associations of RA patients’ subjective and objective PA to their scores on the maximal oxygen uptake test (VO2max).

Methods

The participants wore the GT3X for seven days before completing the IPAQ and VO2max test. The Bland-Altman plot was used to illustrate the agreement between the objective and subjective PA data, and the Wilcoxon test was employed to examine the differences. The association between the PA measurement and VO2max test was examined via the correlations and the magnitude was presented by the Steiger’s Z value.

Results

Sixty-eight RA patients (age = 55 ± 13 years, body mass index: 27.8 ± 5.4 kg/m2, median of disease duration = 5 (2–8) yrs) were recruited. Smaller differences between the subjective and objective measures were found when PA was assessed at the moderate level. Wilcoxon tests revealed that patients reported less time spent engaged in sedentary behaviours (Z = −6.80, P < 0.01) and light PA (Z = −6.89, P < 0.01) and more moderate PA (Z = −6.26, P < 0.01) than was objectively indicated. Significant positive correlations were revealed between VO2max with all PA levels derived from accelerometry (light PA rho = .35, P < .01; moderate PA rho = .34, P = .01; moderate and vigorous PA, (MVPA) rho = .33, P = .01), and a negative association to sedentary time (ST) emerged (rho = −.27, P = .04). IPAQ-reported moderate PA and MVPA positively correlated with maxV02 (rho = .25, P = .01, rho = .27, P = .01, respectively). Differences between the magnitude of correlations between the IPAQ-VO2 max and GT3X-VO2 max were only significant for ST (Z = 3.43, P < .01).

Conclusions

Via responses to the IPAQ, RA patients reported that they were less sedentary and engaged in more higher intensity PA than what was objectively assessed. Accelerometry data correlated with VO2max at all PA levels. Only subjective moderate and MPVA correlated with VO2max. Findings suggest that self-reported PA and ST should be interpreted with caution in people with RA and complemented with accelerometry when possible.

Trial registration

Trial registration: ClinicalTrials.gov ISRCTN04121489. Registered 5 September 2012.

Diurnal variation of gait in patients with rheumatoid arthritis: The DIVIGN study

BACKGROUND

Circadian variation of joint stiffness (morning stiffness) and its impact on functional ability are widely recognised in rheumatoid arthritis. Subsequent within-day variation of walking ability is important due to the increased availability of instrumented gait analysis. This study aimed to quantify diurnal variation of gait in patients with rheumatoid arthritis, and explore associations with disease characteristics.

METHODS

Thirty one inpatients with rheumatoid arthritis walked at a self-selected speed along a GAITRite instrumented walkway 5 times during a single day.

FINDINGS

Participants showed marked diurnal variation in gait, leading to a systematic variation throughout the day (F=19.56, P=<0.001). Gait velocity and stride length both increased, whereas the proportion of each gait cycle spent in stance phase or double support decreased, consistent with improving function throughout the day. Although absolute gait velocity correlated with disease characteristics, the magnitude of diurnal variation appeared to be independent of disease activity (rho=0.26, P=0.15), disease duration (rho=-0.19, P=0.324), and underlying functional ability (rho=0.09, P=0.65).

INTERPRETATION

Although morning stiffness is well recognised in rheumatoid arthritis, this is the first time that its effect on gait has been quantified. Patients with rheumatoid arthritis exhibited a systematic change in walking ability throughout the day, which was independent of disease characteristics. These findings have important implications for the interpretation of existing data and the design of future studies. Repeat measures should be conducted at the same time of day to exclude the effects of diurnal variation.