Is every-day walking in older adults more analogous to dual-task walking or to usual walking? Elucidating the gaps between gait performance in the lab and during 24/7 monitoring

Development and psychometric properties of the Balance in Daily Life (BDL) scale in a population of frail older people

BACKGROUND

Balance disorders in older people cause falls, which can have serious functional and economic consequences. No existing scale relates fall risk to daily life situations. This study describes the development, psychometric properties and construct validity of the Balance in Daily Life (BDL) scale, comprising seven routine tasks including answering a phone, carrying a heavy bag, and sitting down and getting up from a chair.

METHODS

Frail patients aged 65 years or more were prospectively recruited from the geriatric rehabilitation department of a French university hospital. Inclusion criteria included autonomous walking over 20 m and modified Short Emergency Geriatric Assessment score 8-11. Patients with motor skills disorders and comprehension or major memory difficulties were excluded. Patients were assessed on Day 3 and Day 30 with the Balance in Daily Life scale, Timed Up and Go, one-leg stance time, sternal nudge and walking-while-talking tests. The scale was assessed for acceptability, quality, unidimensionality, internal consistency, reliability, temporal stability, responsiveness and construct validity.

RESULTS

140 patients (83 ± 6 years) were recruited, of whom 139 were assessed at Day 0 and 133 at Day 30. Acceptability was satisfactory (134/139 patients completed the test), quality assessment showed a slight floor effect (6 % of patients with minimal score) and evaluation of item redundancy found no strong correlation (Spearman <0.7). Unidimensionality was verified (Loevinger H coefficient > 0.5 for all items except item 6 = 0.4728). Internal consistency was good (Cronbach alpha = 0.86). Reliability and temporal stability were excellent (ICC = 0.97 and ICC = 0.92). Responsiveness was verified by significant score change p < 0.0001 between Day 0 and Day 30 (decreased by 1 [0; 2] point), in line with other score changes. Construct validity revealed that the Balance in Daily Life scale was convergent with results of the timed up-and-go and one-leg stance time (p < 0.0001 for both) and tended to be higher for participants who had not fallen in the previous 6 months (p = 0.0528). The new questionnaire was divergent to sternal nudge tests (p = 0.0002) and not related to the walking-while-talking test (p = 0.5969).

CONCLUSION

The Balance in Daily Life scale has good psychometric properties for this population. Its simplicity and innovative nature mean that it can be applied in institutions while being easily modifiable to domestic settings. Study registration on clinicaltrials.gov: NCT0334382.

Dual-task gait has prognostic value for cognitive decline in Parkinson's disease

INTRODUCTION

Cognitive decline frequently occurs in individuals with Parkinson's disease (PD), but the clinical methods to predict the onset of cognitive changes are limited. Given preliminary evidence of the link between gait and cognition, the purpose of this study was to determine if dual task (DT) gait was related to declines in cognition over two years in PD.

METHODS

A retrospective two-year longitudinal study of 48 individuals with PD using data from the Parkinson's Progression Markers Initiative of the Michael J. Fox Foundation. The following data were extracted at baseline: spatiotemporal gait (during single and DT), demographics (age, sex), PD disease duration (time since diagnosis), motor function (Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS)), and cognition (Montreal Cognitive Assessment (MoCA)), with MoCA scores also extracted after two years.

RESULTS

A binomial logistic regression was conducted, with all covariates (above) in block 1 and DT effect (DTE) of gait characteristics in block 2 entered in a stepwise fashion. The final model was statistically significant (χ2(6) = 23.20, p < 0.001) and correctly classified 78.7 % of participants by cognitive status after two years. Only DTE of arm swing asymmetry (ASA) (p = 0.030) was included in block 2 such that a 1 % decline in DTE resulted in 1.6 % increased odds of cognitive decline.

CONCLUSIONS

Individuals with greater change in arm swing asymmetry from single to DT gait may be more likely to experience a decline in cognition within two years. These results suggested that reduced automaticity or poor utilization of attentional resources may be indicative of subtle changes in cognition and indicate that DT paradigms may hold promise as a marker of future cognitive decline.

Understanding the influence of context on real-world walking energetics

Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in a variety of contexts that can elicit different walking strategies, and may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N=17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Gross and net cost of transport were calculated for each participant, and were used to identify energetically optimal walking speed ranges for each participant. The proportion of real-world steady-state stride speeds within these ranges (gross and net) were identified for all data and for each context. We found that energetically optimal speeds predicted by gross cost of transport were more predictive of walking speeds used during daily life than speeds that would minimize net cost of transport. On average, 82.2% of all steady-state stride speeds were energetically optimal for gross cost of transport for all contexts and participants, while only 45.6% were energetically optimal for net cost of transport. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.

Information processing speed and disease severity predict real-world ambulation in persons with multiple sclerosis

BACKGROUND

Impairments in real-world gait quality and quantity are multifaceted for individuals with multiple sclerosis (MS), encompassing mobility, cognition, and fear of falling. However, these factors are often examined independently, limiting insights into the combined contributions they make to real-world ambulation.

RESEARCH QUESTION

How do mobility, cognition, and fear of falling contribute to real-world gait quality and quantity in individuals with MS?

METHODS

Twenty individuals with MS underwent a series of cognitive assessments, including the Paced Auditory Serial Addition Test (PASAT), Symbol Digits Modalities Test (SDMT), Stroop Test, and the Selective Reminding Test (SRT). Participants also completed the Falls Efficacy Scale - International (FES-I) and walking impairment using the Patient Determined Disease Steps (PDDS). Following the in-lab session, participants wore an inertial sensor on their lower back and asked to go about their typical daily routines for three days. Metrics of gait speed, stride regularity, time spent walking, and total bouts were extracted from the real-world data.

RESULTS

Significant correlations were found between both real-world gait speed and stride regularity and the SDMT, FES-I, and PDDS. Backward linear regression analysis was conducted for gait speed and stride regularity, with PDDS and SDMT included in the final model for both metrics. These variables explained 63% of the variance in gait speed and 69% of the variance in stride regularity. Results were not significant for gait quantity after adjusting for age and sex.

SIGNIFICANCE

The study's results provide insight regarding the roles of cognition, walking impairment, and fear of falling on real-world ambulation. Deeper understanding of these contributions can inform the development of targeted interventions that aim to improve walking. Additionally, the absence of significant correlations between gait metrics, cognition, and fear of falling with gait quantity underscores the need for further research to identify factors that increased walking in this population.

Factors influencing gait performance in older adults in a dual-task paradigm

The aim of this study was to determine the effect of cognitive interference through a dual-task (DT) paradigm on gait parameters by sex or other predictive variables, such as physical fitness, health status, and cognition. A total of 125 older adults joined in this study (age, 72.42 ± 5.56 years old; 28 men and 97 women). The DT paradigm was evaluated through Comfortable Linear Gait (CLG) and Complex Gait Test (CGT). The gait parameters between single task (ST) vs. DT condition in men showed a significant reduction in speed (p < 0.001), cadence (p < 0.001), and step length (p = 0.049) and increased time to execute the CGT (p < 0.001), while women showed a decreased speed (p = 0.014), cadence (p < 0.001), and double support coefficient variation (CV) (p = 0.024) and increased single support time (p < 0.001) and CV step length (p < 0.05). In addition, women increased CGT time (p < 0.001). Furthermore, correlations between DT cost (DTC) cadence vs. Physical Activity for Elderly questionnaire (PASE) (r =  - 0.399; p = 0.008), DTC single support vs. 30 s Sit to Stand Test (r = - 0.356; 0.016), DTC single support vs. Rey Auditory Verbal Learning Test-Learning curve (r =  - 0.335; p = 0.023), DTC double support vs. 30 s Sit to Stand Test (r =  - 0.590; p < 0.001), DTC CV step length vs. 30 s Sit to Stand (r =  - 0.545; p = 0.003), and DTC CGT vs. 30 s Sit to Stand Test (r =  - 0.377; p = 0.048) were found. The results of our study indicate that the gait parameters within the DT condition decreased speed and cadence, while increasing CV step length and CGT time, causing slower gait with shortened steps in men and women.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson's disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.

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.

Accuracy, concurrent validity, and test-retest reliability of pressure-based insoles for gait measurement in chronic stroke patients

Introduction

Wearables are potentially valuable tools for understanding mobility behavior in individuals with neurological disorders and how it changes depending on health status, such as after rehabilitation. However, the accurate detection of gait events, which are crucial for the evaluation of gait performance and quality, is challenging due to highly individual-specific patterns that also vary greatly in movement and speed, especially after stroke. Therefore, the purpose of this study was to assess the accuracy, concurrent validity, and test-retest reliability of a commercially available insole system in the detection of gait events and the calculation of stance duration in individuals with chronic stroke.

Methods

Pressure insole data were collected from 17 individuals with chronic stroke during two measurement blocks, each comprising three 10-min walking tests conducted in a clinical setting. The gait assessments were recorded with a video camera that served as a ground truth, and pressure insoles as an experimental system. We compared the number of gait events and stance durations between systems.

Results and discussion

Over all 3,820 gait events, 90.86% were correctly identified by the insole system. Recall values ranged from 0.994 to 1, with a precision of 1 for all measurements. The F1 score ranged from 0.997 to 1. Excellent absolute agreement (Intraclass correlation coefficient, ICC = 0.874) was observed for the calculation of the stance duration, with a slightly longer stance duration recorded by the insole system (difference of -0.01 s). Bland-Altmann analysis indicated limits of agreement of 0.33 s that were robust to changes in walking speed. This consistency makes the system well-suited for individuals post-stroke. The test-retest reliability between measurement timepoints T1 and T2 was excellent (ICC = 0.928). The mean difference in stance duration between T1 and T2 was 0.03 s. We conclude that the insole system is valid for use in a clinical setting to quantitatively assess continuous walking in individuals with stroke.

Analyzing population-level trials as N-of-1 trials: An application to gait

Studying individual causal effects of health interventions is important whenever intervention effects are heterogeneous between study participants. Conducting N-of-1 trials, which are single-person randomized controlled trials, is the gold standard for their analysis. As an alternative method, we propose to re-analyze existing population-level studies as N-of-1 trials, and use gait as a use case for illustration. Gait data were collected from 16 young and healthy participants under fatigued and non-fatigued, as well as under single-task (only walking) and dual-task (walking while performing a cognitive task) conditions. As a reference to the N-of-1 trials approach, we first computed standard population-level ANOVA models to evaluate differences in gait parameters (stride length and stride time) across conditions. Then, we estimated the effect of the interventions on gait parameters on the individual level through Bayesian repeated-measures models, viewing each participant as their own trial, and compared the results. The results illustrated that while few overall population-level effects were visible, individual-level analyses revealed differences between participants. Baseline values of the gait parameters varied largely among all participants, and the effects of fatigue and cognitive task were also heterogeneous, with some individuals showing effects in opposite directions. These differences between population-level and individual-level analyses were more pronounced for the fatigue intervention compared to the cognitive task intervention. Following our empirical analysis, we discuss re-analyzing population studies through the lens of N-of-1 trials more generally and highlight important considerations and requirements. Our work encourages future studies to investigate individual effects using population-level data.

Influence of Sex on Cognitive and Motor Dual-Task Performance Among Young Adults: A Cross-Sectional Study

OBJECTIVE

To investigate the sex-related differences in single-task performance through motor torque, cognitive tasks and walking speed, and the combined dual-task costs (DTCs) considering both motor and cognitive performance in young adults.

METHODS

Sixty-seven non-athletic subjects 37 females and 30 males were enrolled. The study measured their knee extension muscle torque using an isokinetic strength dynamometer and their walking speed using the one step app. these assessments were performed both with and without a cognitive task, and the DTCs were calculated.

RESULTS

The females exhibited significantly larger motor performance dual task effect through (torque-DTC, speed-DTC) compared with males while exhibiting smaller cognitive dual task effect with muscle torque and speed.

CONCLUSION

Deterioration in motor performance during muscle force production and speed during dual tasks was large in females compared to males, whereas males experience a decline in cognitive ability when performing dual tasks compared with females.

Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist-Worn Accelerometer Data: Development and Validation of ElderNet

Progressive gait impairment is common in aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1,000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p < 0.05). In an initial evaluation of construct validity, ElderNet identified differences in estimated daily walking durations across cohorts with different clinical characteristics, such as mobility disability (p < 0.001) and parkinsonism (p < 0.001). The proposed self-supervised gait detection method has the potential to serve as a valuable tool for remote phenotyping of gait function during daily living in aging adults.

Numerosity estimation of virtual humans as a digital-robotic marker for hallucinations in Parkinson's disease

Hallucinations are frequent non-motor symptoms in Parkinson's disease (PD) associated with dementia and higher mortality. Despite their high clinical relevance, current assessments of hallucinations are based on verbal self-reports and interviews that are limited by important biases. Here, we used virtual reality (VR), robotics, and digital online technology to quantify presence hallucination (vivid sensations that another person is nearby when no one is actually present and can neither be seen nor heard) in laboratory and home-based settings. We establish that elevated numerosity estimation of virtual human agents in VR is a digital marker for experimentally induced presence hallucinations in healthy participants, as confirmed across several control conditions and analyses. We translated the digital marker (numerosity estimation) to an online procedure that 170 PD patients carried out remotely at their homes, revealing that PD patients with disease-related presence hallucinations (but not control PD patients) showed higher numerosity estimation. Numerosity estimation enables quantitative monitoring of hallucinations, is an easy-to-use unobtrusive online method, reaching people far away from medical centers, translating neuroscientific findings using robotics and VR, to patients' homes without specific equipment or trained staff.

Long-term continuous instrumented insole-based gait analyses in daily life have advantages over longitudinal gait analyses in the lab to monitor healing of tibial fractures

Introduction: Monitoring changes in gait during rehabilitation allows early detection of complications. Laboratory-based gait analyses proved valuable for longitudinal monitoring of lower leg fracture healing. However, continuous gait data recorded in the daily life may be superior due to a higher temporal resolution and differences in behavior. In this study, ground reaction force-based gait data of instrumented insoles from longitudinal intermittent laboratory assessments were compared to monitoring in daily life. Methods: Straight walking data of patients were collected during clinical visits and in between those visits the instrumented insoles recorded all stepping activities of the patients during daily life. Results: Out of 16 patients, due to technical and compliance issues, only six delivered sufficient datasets of about 12 weeks. Stance duration was longer (p = 0.004) and gait was more asymmetric during daily life (asymmetry of maximal force p < 0.001, loading slope p = 0.001, unloading slope p < 0.001, stance duration p < 0.001). Discussion: The differences between the laboratory assessments and the daily-life monitoring could be caused by a different and more diverse behavior during daily life. The daily life gait parameters significantly improved over time with union. One of the patients developed an infected non-union and showed worsening of force-related gait parameters, which was earlier detectable in the continuous daily life gait data compared to the lab data. Therefore, continuous gait monitoring in the daily life has potential to detect healing problems early on. Continuous monitoring with instrumented insoles has advantages once technical and compliance problems are solved.

The role of ankle and knee muscle characteristics in spatiotemporal gait parameters at different walking speeds: A cross-sectional study

BACKGROUND

Understanding the intricate interplay between ankle and knee muscle characteristics and their impact on gait parameters is crucial for enhancing our comprehension of human locomotion, particularly in the context of varying walking speeds among healthy young adults.

RESEARCH QUESTION

The study aimed to identify the relative importance of ankle and knee flexor and extensor muscle characteristics (e.g., strength estimated by peak torque [PT] and rate of torque development [RTD]) in the spatiotemporal gait parameters and variability in self-selected (SSWS) and fast walking speeds (FWS) in healthy young adults.

METHODS

One hundred and thirty-nine adults (75 men - 54% and 64 women - 46%; 29.04 ± 9.55 years) were assessed about their muscle characteristics (PT and RTD by an isokinetic dynamometer) and spatiotemporal gait parameters at different walking speeds (SSWS and FWS by an instrumented walkway).

RESULTS

Data analysis indicated a weak relationship between the PT and RTD of the ankle and knee and spatiotemporal gait parameters and variability in both walking conditions (SSWS: R2 0.14-0.05; FWS: R2 0.40-0.05). The strength of the knee muscles was more relevant when walking at a self-selected speed, while the strength of the ankle muscles played a more prominent role when walking at a fast pace.

SIGNIFICANCE

The findings underscore the critical role of ankle muscles (plantar and dorsiflexors) at fast walking speeds. Therefore, targeted interventions for strength and optimization of these muscles are paramount.

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.

Feasibility and Safety of Sequential Transcranial Direct Current Stimulation and Physical Therapy in Older Adults at Risk of Falling: A Randomized Pilot Study

Objective

To establish the feasibility and safety of administering transcranial direct current stimulation (tDCS) immediately prior to physical therapy (PT) sessions in older adults at risk of falls.

Design

A pilot randomized controlled study.

Setting

Outpatient geriatric physical therapy clinic.

Participants

Ten older adults living within supportive housing facilities (86.8±7.9 y/o, 8F) were enrolled in the study.

Interventions

Participants received tDCS or sham stimulation targeting the left dorsal lateral prefrontal cortex for 20 minutes, immediately prior to up to 10 of their PT visits.

Main Outcome Measures

Feasibility, safety, and functional outcomes were reported to inform the design of a larger and more definitive trial.

Results

Six fallers (88.8±5.0 y/o, 5F) completed the study and received 82.3% of the possible stimulation sessions, suggesting adding a 20-minute session of stimulation immediately prior to PT training sessions, along with pre- and post-assessments is feasible. The blinding strategy was successful and all reported side effects were expected and transient. While feasible and safe, the trial was met with numerous challenges, including selection bias, time and energy commitment, and large variation in functional performance, that must be considered when designing and implementing larger more definitive trials.

Conclusion

This study provides preliminary evidence about the feasibility, safety, and challenges to combine PT and tDCS in very frail older adults.

Monitoring Gait and Physical Activity of Elderly Frail Individuals in Free-Living Environment: A Feasibility Study

INTRODUCTION

Frailty is conventionally diagnosed using clinical tests and self-reported assessments. However, digital health technologies (DHTs), such as wearable accelerometers, can capture physical activity and gait during daily life, enabling more objective assessments. In this study, we assess the feasibility of deploying DHTs in community-dwelling older individuals, and investigate the relationship between digital measurements of physical activity and gait in naturalistic environments and participants' frailty status, as measured by conventional assessments.

METHODS

Fried Frailty Score (FFS) was used to classify fifty healthy individuals as non-frail (FFS = 0, n/female = 21/11, mean ± SD age: 71.10 ± 3.59 years), pre-frail (FFS = 1-2, n/female = 23/9, age: 73.74 ± 5.52 years), or frail (FFS = 3+, n/female = 6/6, age: 70.70 ± 6.53 years). Participants wore wrist-worn and lumbar-worn GENEActiv accelerometers (Activinsights Ltd., Kimbolton, UK) during three in-laboratory visits, and at-home for 2 weeks, to measure physical activity and gait. After this period, they completed a comfort and usability questionnaire. Compliant days at-home were defined as follows: those with ≥18 h of wear time, for the wrist-worn accelerometer, and those with ≥1 detected walking bout, for the lumbar-worn accelerometer. For each at-home measurement, a group analysis was performed using a linear regression model followed by ANOVA, to investigate the effect of frailty on physical activity and gait. Correlation between at-home digital measurements and conventional in-laboratory assessments was also investigated.

RESULTS

Participants were highly compliant in wearing the accelerometers, as 94% indicated willingness to wear the wrist device, and 66% the lumbar device, for at least 1 week. Time spent in sedentary activity and time spent in moderate activity as measured from the wrist device, as well as average gait speed and its 95th percentile from the lumbar device were significantly different between frailty groups. Moderate correlations between digital measurements and self-reported physical activity were found.

CONCLUSIONS

This work highlights the feasibility of deploying DHTs in studies involving older individuals. The potential of digital measurements in distinguishing frailty phenotypes, while unobtrusively collecting unbiased data, thus minimizing participants' travels to sites, will be further assessed in a follow-up study.

Reliability of waveforms and gait metrics from multiple outdoor wearable inertial sensors collections in adults with knee osteoarthritis

Wearable sensors may allow research to move outside of controlled laboratory settings to be able to collect real-world data in clinical populations, such as older adults with osteoarthritis. However, the reliability of these sensors must be established across multiple out-of-lab data collections. Nine older adults with symptomatic knee arthritis wore wearable inertial sensors on their proximal tibias during an outdoor 6-minute walk test outside of a controlled laboratory setting as part of a pilot study. Reliability of the underlying waveforms, discrete peak outcomes, and spatiotemporal outcomes were assessed over four separate data collections, each approximately 1 week apart. Reliability at a different number of included strides was also assessed at 10, 20, 50, and 100 strides. The underlying waveforms and discrete peak outcome measures had good-to-excellent reliability for all axes, with lower reliability in frontal plane angular velocity axis. Spatiotemporal outcomes demonstrated excellent reliability. The inclusion of additional strides had little to no effect on reliability in most axes, but the confidence intervals generally became smaller across all axes. However, there was improvement in axes with lower (i.e., good) reliability. These data were collected in an out-of-lab setting, and the results are generally consistent with previous in-lab data collections, likely due to its semi-controlled nature. Additional out-of-laboratory research is required to investigate if these trends continue during truly free-living collections. This study provides support for increasing research conducted in out-of-lab data collections, as demonstrated by the good-to-excellent reliability of all axes.

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.

Free-Living Peak Cadence in Multiple Sclerosis: A New Measure of Real-World Walking?

BACKGROUND

Physical function and walking performance have become important outcomes in clinical trials and rehabilitation involving persons with multiple sclerosis (MS). However, assessments conducted in controlled settings may not reflect real-world capacity and movement in a natural environment. Peak cadence via accelerometry might represent a novel measure of walking intensity and prolonged natural effort under free-living conditions.

OBJECTIVE

We compared peak 30-minute cadence, peak 1-minute cadence, and time spent in incremental cadence bands between persons with MS and healthy controls, and examined the associations between peak cadence and laboratory-assessed physical function and walking performance.

METHODS

Participants (147 MS and 54 healthy controls) completed questionnaires on disability status and self-reported physical activity, underwent the Short Physical Performance Battery, Timed 25-Foot Walk, Timed Up and Go, and 6-Minute Walk, and wore an accelerometer for 7 days. We performed independent samples t-tests and Spearman bivariate and partial correlations adjusting for daily steps.

RESULTS

The MS sample demonstrated lower physical function and walking performance scores, daily steps, and peak cadence (P < .001), and spent less time in purposeful steps and slow-to-brisk walking (40-119 steps/minutes), but accumulated more incidental movement (1-19 steps/minutes) than healthy controls. The associations between peak cadence and performance outcomes were strong in MS (|rs| = 0.59-0.68) and remained significant after controlling for daily steps (|prs| = 0.22-0.44), P-values < .01. Peak cadence was inversely correlated with age and disability, regardless of daily steps (P < .01).

CONCLUSIONS

Our findings provide preliminary evidence for the potential use of peak cadence with step-based metrics for comprehensively evaluating free-living walking performance in MS.

Association of Sit-to-Stand Capacity and Free-Living Performance Using Thigh-Worn Accelerometers among 60- to 90-Yr-Old Adults

PURPOSE

Five times sit-to-stand (STS) test is commonly used as a clinical assessment of lower-extremity functional ability, but its association with free-living performance has not been studied. Therefore, we investigated the association between laboratory-based STS capacity and free-living STS performance using accelerometry. The results were stratified according to age and functional ability groups.

METHODS

This cross-sectional study included 497 participants (63% women) 60-90 yr old from three independent studies. A thigh-worn triaxial accelerometer was used to estimate angular velocity in maximal laboratory-based STS capacity and in free-living STS transitions over 3-7 d of continuous monitoring. Functional ability was assessed with short physical performance battery.

RESULTS

Laboratory-based STS capacity was moderately associated with the free-living mean and maximal STS performance ( r = 0.52-0.65, P < 0.01). Angular velocity was lower in older compared with younger and in low- versus high-functioning groups, in both capacity and free-living STS variables (all P < 0.05). Overall, angular velocity was higher in capacity compared with free-living STS performance. The STS reserve (test capacity - free-living maximal performance) was larger in younger and in high-functioning groups compared with older and low-functioning groups (all P < 0.05).

CONCLUSIONS

Laboratory-based STS capacity and free-living performance were found to be associated. However, capacity and performance are not interchangeable but rather provide complementary information. Older and low-functioning individuals seemed to perform free-living STS movements at a higher percentage of their maximal capacity compared with younger and high-functioning individuals. Therefore, we postulate that low capacity may limit free-living performance.

Uneven surface and cognitive dual-task independently affect gait quality in older adults

BACKGROUND

Real-world mobility involves walking in challenging conditions. Assessing gait during simultaneous physical and cognitive challenges provides insights on cognitive health.

RESEARCH QUESTION

How does uneven surface, cognitive task, and their combination affect gait quality and does this gait performance relate to cognitive functioning?

METHODS

Community-dwelling older adults (N = 104, age=75 ± 6 years, 60 % females) performed dual-task walking paradigms (even and uneven surface; with and without alphabeting cognitive task (ABC)) to mimic real-world demands. Gait quality measures [speed(m/s), rhythmicity(steps/minute), stride time variability (%), adaptability (m/s2), similarity, smoothness, power (Hz) and regularity] were calculated from an accelerometer worn on the lower back. Linear-mixed modelling and Tukey analysis were used to analyze independent effects of surface and cognitive task and their interaction on gait quality. Partial Spearman correlations compared gait quality with global cognition and executive function.

RESULTS

No interaction effects between surface and cognitive task were found. Uneven surface reduced gait speed(m/s) (β = -0.07). Adjusted for speed, uneven surface reduced gait smoothness (β = -0.27) and increased regularity (β = 0.09), Tukey p < .05, for even vs uneven and even-ABC vs uneven-ABC. Cognitive task reduced gait speed(m/s) (β = -0.12). Adjusted for speed, cognitive task increased variability (β = 7.60), reduced rhythmicity (β = -6.68) and increased regularity (β = 0.05), Tukey p < .05, for even vs even-ABC and uneven vs uneven-ABC. With demographics as covariates, gait speed was not associated with cognition. Gait quality [lower variability during even-ABC (ρp =-.31) and uneven-ABC (ρp =-.28); greater rhythmicity (ρp between.22 and.29) and greater signal-adaptability AP (ρp between.22 and.26) during all walking tasks] was associated with better global cognition. Gait adaptability during even (ρp =-0.21, p = 0.03) and uneven(ρp =-0.19, p = 0.04) walking was associated with executive function.

SIGNIFICANCE

Surface and cognitive walking tasks independently affected gait quality. Our study with high-functioning older adults suggests that task-related changes in gait quality are related to subtle changes in cognitive functioning.

Smartphone- and Paper-Based Delivery of Balance Intervention for Older Adults Are Equally Effective, Enjoyable, and of High Fidelity: A Randomized Controlled Trial

Home-based rehabilitation programs for older adults have demonstrated effectiveness, desirability, and reduced burden. However, the feasibility and effectiveness of balance-intervention training delivered through traditional paper-versus novel smartphone-based methods is unknown. Therefore, the purpose of this study was to evaluate if a home-based balance-intervention program could equally improve balance performance when delivered via smartphone or paper among adults over the age of 65. A total of 31 older adults were randomized into either a paper or phone group and completed a 4-week asynchronous self-guided balance intervention across 12 sessions for approximately 30 min per session. Baseline, 4-week, and 8-week walking and standing balance evaluations were performed, with exercise duration and adherence recorded. Additional self-reported measures were collected regarding the enjoyment, usability, difficulty, and length of the exercise program. Twenty-nine participants completed the balance program and three assessments, with no group differences found for any outcome measure. Older adults demonstrated an approximately 0.06 m/s faster gait velocity and modified balance strategies during walking and standing conditions following the intervention protocol. Participants further self-reported similar enjoyment, difficulty, and exercise effectiveness. Results of this study demonstrated the potential to safely deliver home-based interventions as well as the feasibility and effectiveness of delivering balance intervention through a smartphone-based application.

A Comparison of Walking Behavior during the Instrumented TUG and Habitual Gait

The timed up and go test (TUG) is a common clinical functional balance test often used to complement findings on sensorimotor changes due to aging or sensory/motor dysfunction. The instrumented TUG can be used to obtain objective postural and gait measures that are more sensitive to mobility changes. We investigated whether gait and body coordination during TUG is representative of walking. We examined the walking phase of the TUG and compared gait metrics (stride duration and length, walking speed, and step frequency) and head/trunk accelerations to normal walking. The latter is a key aspect of postural control and can also reveal changes in sensory and motor function. Forty participants were recruited into three groups: young adults, older adults, and older adults with visual impairment. All performed the TUG and a short walking task wearing ultra-lightweight wireless IMUs on the head, chest, and right ankle. Gait and head/trunk acceleration metrics were comparable across tasks. Further, stride length and walking speed were correlated with the participants' age. Those with visual impairment walked significantly slower than sighted older adults. We suggest that the TUG can be a valuable tool for examining gait and stability during walking without the added time or space constraints.

Ecological Fall Prediction Sensitivity, Specificity, and Accuracy in Patients with Mild Cognitive Impairment at a High Risk of Falls

While falls among patients with mild cognitive impairment (MCI) have been closely associated with an increased postural sway during ecological activities of daily living, there is a dearth of postural sway detection (PSD) research in ecological environments. The present study aimed to investigate the fall sensitivity, specificity, and accuracy of our PSD system. Forty healthy young and older adults with MCI at a high risk of falls underwent the sensitivity, specificity, and accuracy tests for PSD by simultaneously recording the Berg Balance Scale and Timed Up and Go in ecological environments, and the data were analyzed using the receiver operating characteristic curve and area under the curve. The fall prediction sensitivity ranged from 0.82 to 0.99, specificity ranged from 0.69 to 0.90, and accuracy ranged from 0.53 to 0.81. The PSD system's fall prediction sensitivity, specificity, and accuracy data suggest a reasonable discriminative capacity for distinguishing between fallers and non-fallers as well as predicting falls in older adults with MCI in ecological testing environments.

Walking speed differentially affects lower extremity biomechanics in individuals with anterior cruciate ligament reconstruction compared to uninjured controls

BACKGROUND

Walking biomechanics are commonly affected after anterior cruciate ligament reconstruction and differ compared to uninjured controls. Manipulating task difficulty has been shown to affect the magnitude of walking impairments in those early after knee surgery but it is unclear if patients in later phases post-op are similarly affected by differing task demands. Here, we evaluated the effects of manipulating walking speed on between-limb differences in ground reaction force and knee biomechanics in those with and without anterior cruciate ligament reconstruction.

METHODS

We recruited 28 individuals with anterior cruciate ligament reconstruction and 20 uninjured control participants to undergo walking assessments at three speeds (self-selected, 120%, and 80% self-selected speed). Main outcomes included sagittal plane knee moments, angles, excursions, and ground reaction forces (vertical and anterior-posterior).

FINDINGS

We observed walking speed differentially impacted force and knee-outcomes in those with anterior cruciate ligament reconstruction. Between-limb differences increased at fast and decreased at slow speeds in those with anterior cruciate ligament reconstruction while uninjured participants maintained between-limb differences regardless of speed (partial η2 = 0.13-0.33, p < 0.05). Anterior cruciate ligament reconstruction patients underloaded the surgical limb relative to both the contralateral, and uninjured controls in GRFs and sagittal plane knee moments (partial η2 range = 0.13-0.25, p < 0.05).

INTERPRETATION

Overall, our findings highlight the persistence of walking impairments in those with anterior cruciate ligament reconstruction despite completing formal rehabilitation. Further research should consider determining if those displaying larger changes in gait asymmetries in response to fast walking also exhibit poorer strength and/or joint health outcomes.

EarGait: Estimation of Temporal Gait Parameters from Hearing Aid Integrated Inertial Sensors

Wearable sensors are able to monitor physical health in a home environment and detect changes in gait patterns over time. To ensure long-term user engagement, wearable sensors need to be seamlessly integrated into the user's daily life, such as hearing aids or earbuds. Therefore, we present EarGait, an open-source Python toolbox for gait analysis using inertial sensors integrated into hearing aids. This work contributes a validation for gait event detection algorithms and the estimation of temporal parameters using ear-worn sensors. We perform a comparative analysis of two algorithms based on acceleration data and propose a modified version of one of the algorithms. We conducted a study with healthy young and elderly participants to record walking data using the hearing aid's integrated sensors and an optical motion capture system as a reference. All algorithms were able to detect gait events (initial and terminal contacts), and the improved algorithm performed best, detecting 99.8% of initial contacts and obtaining a mean stride time error of 12 ± 32 ms. The existing algorithms faced challenges in determining the laterality of gait events. To address this limitation, we propose modifications that enhance the determination of the step laterality (ipsi- or contralateral), resulting in a 50% reduction in stride time error. Moreover, the improved version is shown to be robust to different study populations and sampling frequencies but is sensitive to walking speed. This work establishes a solid foundation for a comprehensive gait analysis system integrated into hearing aids that will facilitate continuous and long-term home monitoring.

The Analytical and Clinical Validity of the pfSTEP Digital Biomarker of the Susceptibility/Risk of Declining Physical Function in Community-Dwelling Older Adults

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83-0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53-0.68 and 0.55, 95% CI 0.46-0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32-0.74). We have validated a digital susceptibility/risk biomarker-pfSTEP-that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.

Unsupervised Gait Event Identification with a Single Wearable Accelerometer and/or Gyroscope: A Comparison of Methods across Running Speeds, Surfaces, and Foot Strike Patterns

We evaluated 18 methods capable of identifying initial contact (IC) and terminal contact (TC) gait events during human running using data from a single wearable sensor on the shank or sacrum. We adapted or created code to automatically execute each method, then applied it to identify gait events from 74 runners across different foot strike angles, surfaces, and speeds. To quantify error, estimated gait events were compared to ground truth events from a time-synchronized force plate. Based on our findings, to identify gait events with a wearable on the shank, we recommend the Purcell or Fadillioglu method for IC (biases +17.4 and -24.3 ms; LOAs -96.8 to +131.6 and -137.0 to +88.4 ms) and the Purcell method for TC (bias +3.5 ms; LOAs -143.9 to +150.9 ms). To identify gait events with a wearable on the sacrum, we recommend the Auvinet or Reenalda method for IC (biases -30.4 and +29.0 ms; LOAs -149.2 to +88.5 and -83.3 to +141.3 ms) and the Auvinet method for TC (bias -2.8 ms; LOAs -152.7 to +147.2 ms). Finally, to identify the foot in contact with the ground when using a wearable on the sacrum, we recommend the Lee method (81.9% accuracy).

Dual-task changes in gait and brain activity measured in a healthy young adult population

BACKGROUND

Dual Task (DT) walking in everyday life is the norm rather than the exception. Complex cognitive-motor strategies are employed during DT and it is necessary to coordinate and regulate neural resources to ensure adequate performance. However, the underlying neurophysiology involved is not fully understood. Therefore, the aim of this study was to examine the neurophysiology and gait kinematics during DT gait.

RESEARCH QUESTION

Our main research question was whether gait kinematics changed during DT walking for healthy young adults and whether this is reflected in brain activity.

METHODS

Ten healthy young adults walked on a treadmill, performed a Flanker test while standing and performed the Flanker test while walking on a treadmill. Electroencephalography (EEG), spatial temporal, and kinematic data was recorded and analyzed.

RESULTS

Average alpha and beta activities were modulated during DT walking compared to single task (ST) walking while ERPs during the Flanker test showed larger P300 amplitudes and longer latencies for DT compared to standing. Cadence reduced and cadence variability increased during DT compared to ST whilst kinematic results showed that hip and knee flexions decreased, and the center of mass moved slightly back in the sagittal plane.

SIGNIFICANCE

It was found that healthy young adults employed a cognitive-motor strategy that included directing more neural resources to the cognitive task while adopting a more upright posture during DT walking.

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.

Validation of Commercial Activity Trackers in Everyday Life of People with Parkinson's Disease

Maintaining physical activity is an important clinical goal for people with Parkinson's disease (PwPD). We investigated the validity of two commercial activity trackers (ATs) to measure daily step counts. We compared a wrist- and a hip-worn commercial AT against the research-grade Dynaport Movemonitor (DAM) during 14 days of daily use. Criterion validity was assessed in 28 PwPD and 30 healthy controls (HCs) by a 2 × 3 ANOVA and intraclass correlation coefficients (ICC_2,1). The ability to measure daily step fluctuations compared to the DAM was studied by a 2 × 3 ANOVA and Kendall correlations. We also explored compliance and user-friendliness. Both the ATs and the DAM measured significantly fewer steps/day in PwPD compared to HCs (p < 0.01). Step counts derived from the ATs showed good to excellent agreement with the DAM in both groups (ICC_2,1 > 0.83). Daily fluctuations were detected adequately by the ATs, showing moderate associations with DAM-rankings. While compliance was high overall, 22% of PwPD were disinclined to use the ATs after the study. Overall, we conclude that the ATs had sufficient agreement with the DAM for the purpose of promoting physical activity in mildly affected PwPD. However, further validation is needed before clinical use can be widely recommended.

Validity and reliability of the Apple Health app on iPhone for measuring gait parameters in children, adults, and seniors

This study assessed the concurrent validity and test-retest-reliability of the Apple Health app on iPhone for measuring gait parameters in different age groups. Twenty-seven children, 28 adults and 28 seniors equipped with an iPhone completed a 6-min walk test (6MWT). Gait speed (GS), step length (SL), and double support time (DST) were extracted from the gait recordings of the Health app. Gait parameters were simultaneously collected with an inertial sensors system (APDM Mobility Lab) to assess concurrent validity. Test-retest reliability was assessed via a second iPhone-instrumented 6MWT 1 week later. Agreement of the Health App with the APDM Mobility Lab was good for GS in all age groups and for SL in adults/seniors, but poor to moderate for DST in all age groups and for SL in children. Consistency between repeated measurements was good to excellent for all gait parameters in adults/seniors, and moderate to good for GS and DST but poor for SL in children. The Health app on iPhone is reliable and valid for measuring GS and SL in adults and seniors. Careful interpretation is required when using the Health app in children and when measuring DST in general, as both have shown limited validity and/or reliability.

Use of a wearable accelerometer to evaluate physical frailty in people receiving haemodialysis

BACKGROUND

Physical frailty is a major health concern among people receiving haemodialysis (HD) for stage-5 chronic kidney disease (CKD-5). Wearable accelerometers are increasingly being recommended to objectively monitor activity levels in CKD-5 and recent research suggests they may also represent an innovative strategy to evaluate physical frailty in vulnerable populations. However, no study has yet explored whether wearable accelerometers may be utilised to assess frailty in the context of CKD-5-HD. Therefore, we aimed to examine the diagnostic performance of a research-grade wearable accelerometer in evaluating physical frailty in people receiving HD.

METHODS

Fifty-nine people receiving maintenance HD [age = 62.3 years (SD = 14.9), 40.7% female] participated in this cross-sectional study. Participants wore a uniaxial accelerometer (ActivPAL) for seven consecutive days and the following measures were recorded: total number of daily steps and sit-to-stand transitions, number of daily steps walked with cadence < 60 steps/min, 60-79 steps/min, 80-99 steps/min, 100-119 steps/min, and ≥ 120 steps/min. The Fried phenotype was used to evaluate physical frailty. Receiver operating characteristics (ROC) analyses were performed to examine the diagnostic accuracy of the accelerometer-derived measures in detecting physical frailty status.

RESULTS

Participants classified as frail (n = 22, 37.3%) had a lower number of daily steps (2363 ± 1525 vs 3585 ± 1765, p = 0.009), daily sit-to-stand transitions (31.8 ± 10.3 vs 40.6 ± 12.1, p = 0.006), and lower number of steps walked with cadence of 100-119 steps/min (336 ± 486 vs 983 ± 797, p < 0.001) compared to their non-frail counterparts. In ROC analysis, the number of daily steps walked with cadence ≥ 100 steps/min exhibited the highest diagnostic performance (AUC = 0.80, 95% CI: 0.68-0.92, p < 0.001, cut-off ≤ 288 steps, sensitivity = 73%, specificity = 76%, PPV = 0.64, NPV = 0.82, accuracy = 75%) in detecting physical frailty.

CONCLUSIONS

This study provided initial evidence that a wearable accelerometer may be a useful tool in evaluating physical frailty in people receiving HD. While the total number of daily steps and sit-to-stand transitions could significantly discriminate frailty status, the number of daily steps walked with cadences reflecting moderate to vigorous intensity of walking may be more useful in monitoring physical frailty in people receiving HD.

Age and walking conditions differently affect domains of gait

INTRODUCTION

Analysing gait in controlled conditions that resemble daily life walking could overcome the limitations associated with gait analysis in uncontrolled real-world conditions. Such analyses could potentially aid the identification of a walking condition that magnifies age-differences in gait. Therefore, the aim of the current study was to determine the effects of age and walking conditions on gait performance.

METHODS

Trunk accelerations of young (n = 27, age: 21.6) and older adults (n = 26, age: 68.9) were recorded for 3 min in four conditions: walking up and down a university hallway on a track of 10 m; walking on a specified path, including turns, in a university hallway; walking outside on a specified path on a pavement including turns; and walking on a treadmill. Factor analysis was used to reduce 27 computed gait measures to five independent gait domains. A multivariate analysis of variance was used to examine the effects of age and walking condition on these gait domains.

RESULTS

Factor analysis yielded 5 gait domains: variability, pace, stability, time & frequency, complexity, explaining 64% of the variance in 27 gait outcomes. Walking conditions affected all gait domains (p < 0.01) but age only affected the time & frequency domain (p < 0.05). Age and walking conditions differently affected the domains variability, stability, time & frequency. The largest age-differences occurred mainly during straight walking in a hallway (variability: 31% higher in older adults), or during treadmill walking (stability: 224% higher, time&frequency: 120% lower in older adults).

CONCLUSION

Walking conditions affect all domains of gait independent of age. Treadmill walking and walking on a straight path in a hallway, were the most constrained walking conditions in terms of limited possibilities to adjust step characteristics. The age by condition interaction suggests that for the gait domains variability, stability, and time & frequency, the most constrained walking conditions seem to magnify the age-differences in gait.

Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease

Objectives

To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson's disease (PD) increases the discriminative ability to predict future falls compared to fall history alone.

Methods

We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the feet and lower back for a week of passive gait monitoring. Logistic regression employing a "best subsets selection strategy" was used to find combinations of measures that discriminated future fallers from non-fallers, and the Area Under Curve (AUC). Participants were followed via email every 2 weeks over the year after the study for self-reported falls.

Results

Twenty-five subjects reported falls in the follow-up year. Quantity of gait and turning measures (e.g., number of gait bouts and turns per hour) were similar in future fallers and non-fallers. The AUC to discriminate future fallers from non-fallers using fall history alone was 0.77 (95% CI: [0.50-1.00]). In contrast, the highest AUC for gait and turning digital measures with 4 combinations was 0.94 [0.84-1.00]. From the top 10 models (all AUCs>0.90) via the best subsets strategy, the most consistently selected measures were variability of toe-out angle of the foot (9 out of 10), pitch angle of the foot during mid-swing (8 out of 10), and peak turn velocity (7 out of 10).

Conclusions

These findings highlight the importance of considering precise digital measures, captured via sensors strategically placed on the feet and low back, to quantify several different aspects of gait (walking and turning) during daily life to improve the classification of future fallers in PD.

Multidisciplinary Intensive Rehabilitation Program for People with Parkinson's Disease: Gaps between the Clinic and Real-World Mobility

Intensive rehabilitation programs improve motor and non-motor symptoms in people with Parkinson's disease (PD), however, it is not known whether transfer to daily-living walking occurs. The effects of multidisciplinary-intensive-outpatient rehabilitation (MIOR) on gait and balance in the clinic and on everyday walking were examined. Forty-six (46) people with PD were evaluated before and after the intensive program. A 3D accelerometer placed on the lower back measured daily-living walking during the week before and after the intervention. Participants were also stratified into "responders" and "non-responders" based on daily-living-step-counts. After the intervention, gait and balance significantly improved, e.g., MiniBest scores (p < 0.001), dual-task gait speed increased (p = 0.016) and 6-minute walk distance increased (p < 0.001). Many improvements persisted after 3 months. In contrast, daily-living number of steps and gait quality features did not change in response to the intervention (p > 0.1). Only among the "responders", a significant increase in daily-living number of steps was found (p < 0.001). These findings demonstrate that in people with PD improvements in the clinic do not necessarily carry over to daily-living walking. In a select group of people with PD, it is possible to ameliorate daily-living walking quality, potentially also reducing fall risk. Nevertheless, we speculate that self-management in people with PD is relatively poor; therefore, to maintain health and everyday walking abilities, actions such as long-term engaging in physical activity and preserving mobility may be needed.

Including cognitive assessments with functional testing predicts capabilities relevant to everyday walking in older adults

BACKGROUND

Dual-task (DT) testing reflects real-world walking demands in older adults but is not always feasible to perform in clinic. Whether clinical measures that predict single-task (ST) performance also predict DT performance or dual-task effects (DTEs) has not been fully explored.

RESEARCH QUESTION

What are the relationships between cognitive performance, functional mobility, and self-reported physical activity and balance confidence and ST and DT Gait Speed and Cognitive Reaction Time, as well as DTEs on Gait Speed (DTE_GS) and Cognitive Reaction Time (DTE_RT), in older adults?

METHODS

Sixty-two older adults (71.5 ± 7.1 years, 17 males) completed cognitive performance, functional mobility, and self-report physical activity and balance confidence assessments. Three 1-min trials were performed: 1) ST Cognition (clock task), 2) ST Gait and 3) DT Cognition + Gait, with Cognitive Reaction Time (recorded during clock task performance via DirectRT) and Gait Speed (measured during walking trial via APDM system) recorded, and DTE_GS and DTE_RT calculated, as the cognitive and gait outcomes. Six multivariate regressions were conducted to test whether cognitive performance, functional mobility, and self-report assessments predicted Gait Speed and Cognitive Reaction Time in ST and DT conditions and DTEs.

RESULTS

The Comprehensive Trail Making Test (CTMT) predicted Reaction Time in ST cognitive (β = - 0.525, p = .003) and DT (β = - 0.510, p = .006) trials. The Physical Activity Scale for the Elderly (PASE) predicted DTE_RT (β = - 0.397, p = .008). The 10-Meter Walk Test (10MWT) predicted Gait Speed in ST gait (β = 0.692, p < .001) and DT (β = 0.715, p < .001) trials. The Four Square Step Test (FSST) predicted ST Gait Speed (β = - 0.233, p = .034). The Montreal Cognitive Assessment (MoCA) (β = 0.293, p = .027), 10MWT (β = 0.322, p = .046), and the FSST (β = 0.378, p = .019) predicted DTE_GS.

SIGNIFICANCE

The 10MWT, CTMT, and MoCA can be easily implemented in the clinic and may be good choices to assess cognitive and functional abilities necessary for ambulation in older adults.

Abnormal gait and motor cortical processing in drug-resistant juvenile myoclonic epilepsy

BACKGROUND

Juvenile myoclonic epilepsy (JME) is characterized by generalized seizures. Nearly 30% of JME patients are drug-resistant (DR-JME), indicating a widespread cortical dysfunction. Walking is an important function that necessitates orchestrated coordination of frontocentral cortical regions. However, gait alterations in JME have been scarcely investigated. Our aim was to assess changes in gait and motor-evoked responses in DR-JME patients.

METHODS

Twenty-nine subjects (11 JME drug-responder, 8 DR-JME, and 10 healthy controls) underwent a gait analyses during usual walking and dual-task walking. Later, subjects underwent 64-channel EEG recordings while performing a simple motor task. We calculated the motor-evoked current source densities (CSD) at a priori chosen cortical regions. Gait and CSD measures were compared between groups and tasks using mixed model analysis.

RESULTS

DR-JME patients demonstrated an altered gait pattern that included slower gait speed (p = .018), reduced cadence (p = .003), and smaller arm-swing amplitude (p = .011). The DR-JME group showed higher motor-evoked CSD in the postcentral gyri compared to responders (p = .049) and both JME groups showed higher CSD in the superior frontal gyri compared to healthy controls (p < .011). Moreover, higher CSD in the superior frontal gyri correlated with worse performance in dual-task walking (r > |-0.494|, p < .008).

CONCLUSIONS

These alterations in gait and motor-evoked responses in DRE-JME patients reflect a more severe dysfunction of motor-cognitive neural processing in frontocentral regions, leading to poorer gait performance. Further studies are needed to investigate the predictive value of altered gait and cortical motor processing as biomarkers for poor response to treatment in JME and other epilepsy syndromes.

Effect of Levodopa and Environmental Setting on Gait and Turning Digital Markers Related to Falls in People with Parkinson's Disease

Background

It is unknown whether medication status (off and on levodopa) or laboratory versus home settings plays a role in discriminating fallers and non-fallers in people with Parkinson's disease (PD).

Objectives

To investigate which specific digital gait and turning measures, obtained with body-worn sensors, best discriminated fallers from non-fallers with PD in the clinic and during daily life.

Methods

We recruited 34 subjects with PD (17 fallers and 17 non-fallers based on the past 6 month's falls). Subjects wore three inertial sensors attached to both feet and the lumbar region in the laboratory for a 3-minute walking task (both off and on levodopa) and during daily life activities for a week. We derived 24 digital (18 gait and 6 turn) measures from the 3-minute walk and from daily life.

Results

In clinic, none of the gait and turning measures collected during on levodopa state were significantly different between fallers and non-fallers. In contrast, digital measures collected in the off levodopa state were significantly different between groups, (average turn velocity, average number of steps to complete a turn, and variability of gait speed, P < 0.03). During daily life, the variability of average turn velocity (P = 0.023) was significantly different in fallers than non-fallers. Last, the average number of steps to complete a turn was significantly correlated with the patient-reported outcomes.

Conclusions

Digital measures of turning, but not gait, were different in fallers compared to non-fallers with PD, in the laboratory when off medication and during a daily life.

Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development

Alzheimer's disease (AD) is a devastating neurodegenerative disease and the primary cause of dementia worldwide. Despite the magnitude of AD's impact on patients, caregivers, and society, nearly all AD clinical trials fail. A potential contributor to this high rate of failure is that established clinical outcome assessments fail to capture subtle clinical changes, entail high burden for patients and their caregivers, and ineffectively address the aspects of health deemed important by patients and their caregivers. AD progression is associated with widespread changes in physical behavior that have impacts on the ability to function independently, which is a meaningful aspect of health for patients with AD and important for diagnosis. However, established assessments of functional independence remain underutilized in AD clinical trials and are limited by subjective biases and ceiling effects. Digital measures of real-world physical behavior assessed passively, continuously, and remotely using digital health technologies have the potential to address some of these limitations and to capture aspects of functional independence in patients with AD. In particular, measures of real-world gait, physical activity, and life-space mobility captured with wearable sensors may offer value. Additional research is needed to understand the validity, feasibility, and acceptability of these measures in AD clinical research.

Reinvest to Assess: Advancing Approaches to Motor Competence Measurement Across the Lifespan

Measurement of motor competence is a vital process to advancing knowledge in the field of motor development. As motor competence is being more widely linked to research in other academic domains (e.g., public health, neuroscience, behavioral health), it is imperative that measurement methodology and protocols are reproducible with high degrees of validity and reliability. When addressing the plethora of available assessments, mostly developed for youth populations, there are potential questions and concerns that need to be addressed and/or clarified. One of the most prominent issues is the lack of a lifespan measure of motor competence, which is at odds with the premise of the field of motor development-studying changes in motor behavior across the lifespan. We address six areas of concern in lifespan assessment which include: (1) lack of assessment feasibility for conducting research with large samples, (2) lack of accountability for cultural significance of skills assessed, (3) limited sensitivity and discriminatory capabilities of assessments, (4) developmental and ecological validity limitations, (5) a problematic definition of 'success' in skill performance, and (6) task complexity and adaptability limitations. It is important to critically analyze current assessment methodologies as it will help us to envision the development and application of potential new assessments through a more comprehensive lens. Ultimately, we propose that reinvesting in how we think about assessment will be highly beneficial for integrating motor development from a holistic perspective, impact scientific advancements in other developmental domains, and increase global and lifespan surveillance of motor competence.

Need for personalized monitoring of Parkinson's disease: the perspectives of patients and specialized healthcare providers

Background

Digital tools such as wearable sensors may help to monitor Parkinson's disease (PD) in daily life. To optimally achieve the expected benefits, such as personized care and improved self-management, it is essential to understand the perspective of both patients and the healthcare providers.

Objectives

We identified the motivations for and barriers against monitoring PD symptoms among PD patients and healthcare providers. We also investigated which aspects of PD were considered most important to monitor in daily life, and which benefits and limitations of wearable sensors were expected.

Methods

Online questionnaires were completed by 434 PD patients and 166 healthcare providers who were specialized in PD care (86 physiotherapists, 55 nurses, and 25 neurologists). To gain further understanding in the main findings, we subsequently conducted homogeneous focus groups with patients (n = 14), physiotherapists (n = 5), and nurses (n = 6), as well as individual interviews with neurologists (n = 5).

Results

One third of the patients had monitored their PD symptoms in the past year, most commonly using a paper diary. Key motivations were: (1) discuss findings with healthcare providers, (2) obtain insight in the effect of medication and other treatments, and (3) follow the progression of the disease. Key barriers were: (1) not wanting to focus too much on having PD, (2) symptoms being relatively stable, and (3) lacking an easy-to-use tool. Prioritized symptoms of interest differed between patients and healthcare providers; patients gave a higher priority to fatigue, problems with fine motor movements and tremor, whereas professionals more frequently prioritized balance, freezing and hallucinations. Although both patients and healthcare providers were generally positive about the potential of wearable sensors for monitoring PD symptoms, the expected benefits and limitations varied considerably between groups and within the patient group.

Conclusion

This study provides detailed information about the perspectives of patients, physiotherapists, nurses and neurologists on the merits of monitoring PD in daily life. The identified priorities differed considerably between patients and professionals, and this information is critical when defining the development and research agenda for the coming years. We also noted considerable differences in priorities between individual patients, highlighting the need for personalized disease monitoring.

Effects of noninvasive brain stimulation on dual-task performance in different populations: A systematic review

Background

Increasing research has investigated the use of noninvasive brain stimulation (NIBS) on augmenting dual-task (DT) performance.

Objective

To investigate the effects of NIBS on DT performance in different populations.

Methods

Extensive electronic database search (from inception to November 20, 2022) was conducted in PubMed, Medline, Cochrane Library, Web of Science and CINAHL to identify randomized controlled trials (RCTs) that investigated the effects of NIBS on DT performance. Main outcomes were balance/mobility and cognitive function under both single-task (ST) and DT conditions.

Results

Fifteen RCTs were included, involving two types of intervention techniques: transcranial direct current stimulation (tDCS) (twelve RCTs) and repetitive transcranial magnetic stimulation (rTMS) (three RCTs); and four different population groups: healthy young adults, older adults, Parkinson's disease (PD), and stroke. For tDCS, under DT condition, significant improvement in speed was only observed in one PD and one stroke RCT, and stride time variability in one older adults RCT. Reduction in DTC in some gait parameters was demonstrated in one RCT. Only one RCT showed significant reduction in postural sway speed and area during standing under DT condition in young adults. For rTMS, significant improvements in fastest walking speed and time taken to Timed-up-and-go test under both ST and DT conditions were observed at follow-up in one PD RCT only. No significant effect on cognitive function in any RCT was observed.

Conclusion

Both tDCS and rTMS showed promising effects in improving DT walking and balance performance in different populations, however, due to the large heterogeneity of included studies and insufficient data, any firm conclusion cannot be drawn at present.

Treadmill training with virtual reality to enhance gait and cognitive function among people with multiple sclerosis: a randomized controlled trial

BACKGROUND

Motor and cognitive impairments impact the everyday functioning of people with MS (pwMS). The present randomized controlled trial (RCT) evaluated the benefits of a combined motor-cognitive virtual reality training program on key motor and cognitive symptoms and related outcomes in pwMS.

METHODS

In a single-blinded, two-arm RCT, 124 pwMS were randomized into a treadmill training with virtual reality (TT + VR) group or a treadmill training alone (TT) (active-control) group. Both groups received three training sessions per week for 6 weeks. Dual-tasking gait speed and cognitive processing speed (Symbol Digit Modalities Test, SDMT, score) were the primary outcomes. Secondary outcomes included additional tests of cognitive function, mobility, and patient-reported questionnaires. These were measured before, after, and 3 months after training.

RESULTS

Gait speed improved (p < 0.005) in both groups, similarly, by about 10 cm/s. The TT + VR group (n = 53 analyzed per-protocol) showed a clinically meaningful improvement of 4.4 points (95% CI 1.9-6.8, p = 0.001) in SDMT, compared to an improvement of only 0.8 points in the TT (n = 51 analyzed per-protocol) group (95% CI 0.9-2.5 points, p = 0.358) (group X time interaction effect p = 0.027). Furthermore, TT + VR group-specific improvements were seen in depressive symptoms (lowered by 31%, p = 0.003), attention (17%, p < 0.001), and verbal fluency (11.6% increase, p = 0.002).

DISCUSSION

These findings suggest that both TT and TT + VR improve usual and dual-task gait in pwMS. Nonetheless, a multi-modal approach based on VR positively impacts multiple aspects of cognitive function and mental health, more than seen after treadmill-treading alone. Trial registered at ClinicalTrials.Gov NCT02427997.

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.

Step-Counting Accuracy of a Commercial Smartwatch in Mild-to-Moderate PD Patients and Effect of Spatiotemporal Gait Parameters, Laterality of Symptoms, Pharmacological State, and Clinical Variables

Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device.

Cognitive parameters can predict change of walking performance in advanced Parkinson's disease - Chances and limits of early rehabilitation

Introduction

Links between cognition and walking performance in patients with Parkinson's disease (PD), which both decline with disease progression, are well known. There is lack of knowledge regarding the predictive value of cognition for changes in walking performance after individualized therapy. The aim of this study is to identify relevant predictive cognitive and affective parameters, measurable in daily clinical routines, for change in quantitative walking performance after early geriatric rehabilitation.

Methods

Forty-seven acutely hospitalized patients with advanced PD were assessed at baseline (T1) and at the end (T2) of a 2-week early rehabilitative geriatric complex treatment (ERGCT). Global cognitive performance (Montreal Cognitive Assessment, MoCA), EF and divided attention (Trail Making Test B minus A, delta TMT), depressive symptoms, and fear of falling were assessed at T1. Change in walking performance was determined by the difference in quantitative walking parameters extracted from a sensor-based movement analysis over 20 m straight walking in single (ST, fast and normal pace) and dual task (DT, with secondary cognitive, respectively, motor task) conditions between T1 and T2. Bayesian regression (using Bayes Factor BF₁₀) and multiple linear regression models were used to determine the association of non-motor characteristics for change in walking performance.

Results

Under ST, there was moderate evidence (BF₁₀ = 7.8, respectively, BF₁₀ = 4.4) that lower performance in the ∆TMT at baseline is associated with lower reduction of step time asymmetry after treatment (R ² _adj = 0.26, p ≤ 0.008, respectively, R ² _adj = 0.18, p ≤ 0.009). Under DT walking-cognitive, there was strong evidence (BF₁₀ = 29.9, respectively, BF₁₀ = 27.9) that lower performance in the ∆TMT is associated with more reduced stride time and double limb support (R ² _adj = 0.62, p ≤ 0.002, respectively, R ² _adj = 0.51, p ≤ 0.009). There was moderate evidence (BF₁₀ = 5.1) that a higher MoCA total score was associated with increased gait speed after treatment (R ² _adj = 0.30, p ≤ 0.02).

Discussion

Our results indicate that the effect of ERGT on change in walking performance is limited for patients with deficits in EF and divided attention. However, these patients also seem to walk more cautiously after treatment in walking situations with additional cognitive demand. Therefore, future development of individualized treatment algorithms is required, which address individual needs of these vulnerable patients.

Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset

INTRODUCTION

Turning in gait digital parameters may be useful in measuring disease progression in Parkinson's disease (PD), however challenges remain over algorithm validation in real-world settings. The influence of clinician observation on turning outcomes is poorly understood. Our objective is to describe a unique in-home video dataset and explore the use of turning parameters as biomarkers in PD.

METHODS

11 participants with PD, 11 control participants stayed in a home-like setting living freely for 5 days (with two sessions of clinical assessment), during which high-resolution video was captured. Clinicians watched the videos, identified turns and documented turning parameters.

RESULTS

From 85 hours of video 3869 turns were evaluated, averaging at 22.7 turns per hour per person. 6 participants had significantly different numbers of turning steps and/or turn duration between "ON" and "OFF" medication states. Positive Spearman correlations were seen between the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale III score with a) number of turning steps (rho = 0.893, p < 0.001), and b) duration of turn (rho = 0.744, p = 0.009) "OFF" medications. A positive correlation was seen "ON" medications between number of turning steps and clinical rating scale score (rho = 0.618, p = 0.048). Both cohorts took more steps and shorter durations of turn during observed clinical assessments than when free-living.

CONCLUSION

This study shows proof of concept that real-world free-living turn duration and number of turning steps recorded can distinguish between PD medication states and correlate with gold-standard clinical rating scale scores. It illustrates a methodology for ecological validation of real-world digital outcomes.

Patient-Reported Outcome Measures for Assessing Dual-Task Performance in Daily Life: A Review of Current Instruments, Use, and Measurement Properties

The patient perspective of dual-task (DT) impairment in real life is unclear. This review aimed (i) to identify patient-reported outcome measures (PROMs) on DT and evaluate their measurement properties and (ii) to investigate the usage of PROMs for the evaluation of DT difficulties. A systematic literature search was conducted using PubMed and Web of Science from inception to March 2022. Methodological quality was evaluated using the COSMIN checklist. Six studies examined the measurement properties of DT PROMs. Nine studies used DT PROMs as the outcome measure. Five PROMs were identified, including the Divided Attention Questionnaire (DAQ), Dual-Task-Impact on Daily-life Activities Questionnaire (DIDA-Q), a Questionnaire by Cock et al. (QOC), Dual-Tasking Questionnaire (DTQ), and Dual-Task Screening-List (DTSL). Fourteen measurement properties were documented: five (35.7%) rated quality as "sufficient", six (42.8%) "insufficient", and three (21.4%) "indeterminate". The quality of evidence for each measurement property ranged from very low to high. While DT performance is investigated in many populations, the use of PROMs is still limited, although five instruments are available. Currently, due to insufficient data, it is not possible to recommend a specific DT PROM in a specific population. An exception is DIDA-Q, which has the highest quality of measurement properties in people with multiple sclerosis.