Gait & Posture

BackgroundThree-dimensional gait analysis (3DGA) is widely used to support clinical decision-making in individuals with motor impairments. However, kinematic outputs depend strongly on the underlying biomechanical model. The open-source Conventional Gait Model II (CGM2) integrates updates to joint centre estimation (CGM2.1), inverse kinematics (CGM2.2), and cluster-based segment tracking (CGM2.3). While previous work demonstrated consistency among CGM2 variants in typically developing children, their effect in clinical populations remains unknown. This study quantified how CGM2 variants influence gait kinematics in individuals with cerebral palsy (CP). MethodsTwenty-one individuals with CP (GMFCS I-II) underwent 3DGA using a 12-camera motion capture system and a CGM2.3 marker set. Hip, knee, and ankle kinematics from 487 gait cycles were computed using pyCGM2. Differences between CGM2.1, CGM2.2, and CGM2.3 were evaluated using Mean Absolute Deviation (MAD) and the adjusted coefficient of determination (R2). ResultsOverall, small differences were observed between model variants. MAD values were typically below 5{degrees} for most joints and planes, with high correlation between curves (R2>0.7). Hip rotation showed the largest discrepancies, with maximum MAD up to 7.7{degrees} when comparing CGM2.2 and CGM2.3. Differences between CGM2.1 and CGM2.3 were greater in the transverse and frontal planes but remained within acceptable limits (<5{degrees}), except for hip rotation. ConclusionThe CGM2 variant selection has limited impact on gait kinematics in individuals with CP, and most differences fall within known repeatability error. However, transverse-plane kinematics, particularly hip rotation, should be interpreted with caution when comparing data across CGM2 variants.

BackgroundPeople with stroke often walk with temporal asymmetry; which is related to increased fall risk. The purpose of this study was to determine the relationship between temporal gait asymmetry and mechanical stability among people with sub-acute stroke. MethodsThirty-one people with sub-acute stroke (<6 months post-stroke) completed six walking trials in a biomechanics laboratory. Three-dimensional motion capture was recorded. Swing symmetry was calculated as a ratio of swing time on the more affected limb divided by swing time on the less affected limb. Mechanical stability was the minimum margin of stability, relative to the medial and lateral borders of the stance limb, during the single support phase of the gait cycle. Multiple linear regression was used to determine the relationship between swing symmetry and mechanical stability, controlling for step width and walking speed. ResultsThere was a significant negative relationship between swing symmetry and lateral margin of stability on the less affected side (p<0.0001) and medial margin of stability on the more affected side (p=0.023). That is, as swing symmetry increased, the extrapolated centre of mass tended to be closer to the lateral border of the less affected side and farther from the medial border of the more affected side. ConclusionGait asymmetry could, in part, result from a strategy to compensate for poor balance control on the more affected side. Alternatively, reduced lateral margin of stability on the less affected side among asymmetric participants indicates instability in this direction and could increase the risk for falling.

BackgroundThere is evidence that ambulatory people with incomplete spinal cord injury (iSCI) have an impaired ability to control lateral motion of their whole-body center of mass (COM) during walking. This impairment is believed to contribute to functional deficits in gait and balance, however that relationship is unclear. Thus, this cross-sectional study examines the relationship between the ability to control lateral COM motion during walking and functional measures of gait and balance in people with iSCI. MethodsWe assessed the ability to control lateral COM motion during walking and conducted clinical gait and balance outcome measures on twenty ambulatory adults with chronic iSCI (C1-T10 injury, American Spinal Injury Association Impairment Scale C or D). To assess their ability to control lateral COM motion, participants performed three treadmill walking trials. During each trial, real-time lateral COM position and a target lane were projected on the treadmill. Participants were instructed to keep their lateral COM position within the lane. If successful, an automated control algorithm progressively reduced the lane width, making the task more challenging. If unsuccessful, the lane width increased. The adaptive lane width was designed to challenge each participants maximum capacity to control lateral COM motion during walking. To quantify control of lateral COM motion, we calculated lateral COM excursion during each gait cycle and then identified the minimum lateral COM excursion occurring during five consecutive gait cycles. Our clinical outcome measures were Berg Balance Scale (BBS), Timed Up and Go test (TUG), 10-Meter Walk Test (10MWT) and Functional Gait Assessment (FGA). We used a Spearman correlation analysis ({rho}) to examine the relationship between minimum lateral COM excursion and clinical measures. ResultsMinimum lateral COM excursion had significant moderate correlations with BBS ({rho}=-0.54, p=0.014), TUG ({rho}=0.59, p=0.007), 10MWT-preferred ({rho}=-0.59, p=0.006), and FGA ({rho}=-0.59, p=0.007) and a significant strong correlation with 10MWT-fast ({rho}=-0.68, p=0.001). ConclusionControl of lateral COM motion during walking predicts a wide range of clinical gait and balance measures in people with iSCI. This finding suggests the ability to control lateral COM motion during walking could be a contributing factor to gait and balance in people with iSCI.

Three-dimensional gait analysis is widely used to support clinical decision-making in neuromuscular disorders, with the Conventional Gait Model (CGM) being the most commonly applied biomechanical model in clinical practice. Recent developments of the CGM, grouped under the open-source CGM2 framework, introduced methodological updates intended to improve robustness while preserving backward compatibility. However, the reliability of these successive CGM2 iterations has not been comprehensively evaluated, particularly in pathological gait populations. This study investigated within- and between-assessor reliability of lower-limb kinematics across three CGM2 versions (2.1, 2.2, and 2.3) in asymptomatic participants and individuals with cerebral palsy. Reliability was quantified using standard error of measurement and minimal detectable change across the gait cycle. Overall measurement error remained low and consistent across models and participant groups, with standard errors close to 2{degrees} and minimal detectable changes around 6{degrees}. Introducing kinematic fitting had minimal influence on reliability, while adding tracking markers on the thigh and shank produced a modest reduction in hip transverse rotation error. These findings indicate that methodological refinements implemented in CGM2 preserve the reliability of the original CGM while providing incremental improvements for clinically relevant parameters, supporting its use in both asymptomatic and pathological gait analysis and longitudinal clinical assessments

BackgroundMyotonic dystrophy type 1 (DM1) is a prevalent inherited muscular dystrophy in adults, affecting distal muscles such as the gastrocnemius, soleus, and tibialis anterior. This leads to significant gait deviations and reduced walking speed, impacting overall well-being and increasing fall risk. ObjectiveThis study aimed to assess how walking speed affects gait kinematics in individuals with DM1. MethodEighteen individuals with genetically confirmed DM1 (4 women, age: 41.0 [35.5; 47.8] years, mass: 76.8 [67.1; 94.6] kg, height: 166.0 [156.7; 173.3] cm) participated in this study. Each participant walked barefoot along a 13-meter walkway at comfortable and fast speeds. Subsequently, spatiotemporal parameters and joint kinematics were assessed. ResultsThe step length (p < 0.001), cycle speed (p < 0.001), and cadence (p < 0.001) increased significantly, leading to a higher walking speed. Moreover, the vertical amplitude of the center of mass (CoM) increased significantly (p = 0.015), while the mediolateral amplitude decreased (p = 0.001) at fast walking condition. In addition, significant kinematic changes included increased trunk tilt (p < 0.001), greater anterior pelvic tilt (p < 0.001), increased hip flexion at initial contact, and enhanced knee flexion during both stance and swing phases. Ankle dorsiflexion showed a trend towards increase during stance phase (p = 0.055) at fast walking condition. ConclusionsFast walking speed in individuals with DM1 lead to significant gait adaptations. These adaptations reflect compensatory mechanisms to manage muscle weakness. The present study revealed significant changes in spatiotemporal parameters related to walking speed. Fast walking also highlighted kinematic adaptations in trunk, pelvis and lower limb joints. These findings enhance our understanding of gait deviation in individuals with DM1 and suggest the potential benefits of targeted fast walking training in this population.

BackgroundPeople with stroke often have asymmetric motor impairment. Investigating asymmetries in, and dynamic properties of, centre of pressure movement during quiet standing can inform how well balance is controlled. Research questionWhat are the test-retest reliabilities of novel measures of quiet standing balance control in people with chronic stroke? MethodsTwenty people with chronic stroke (>6 months post-stroke), who were able to stand for at least 30 seconds without support, were recruited. Participants completed two 30-second quiet standing trials in a standardized position. Novel measures of quiet standing balance control included: symmetry of variability in centre of pressure displacement and velocity, between-limb synchronization, and sample entropy. Root mean square of centre of pressure displacement and velocity in the antero-posterior and medio-lateral directions were also calculated. Intraclass correlation coefficients (ICCs) were used to determine test-retest reliability, and Bland-Altman plots were created to examine proportional biases. ResultsICC3,2 were between 0.79 and 0.95 for all variables, indicating good to excellent reliability (>0.75). However, ICC3,1 for symmetry indices and between-limb synchronization were <0.75. Bland-Altman plots revealed possible proportional biases for root mean square of medio-lateral centre of pressure displacement and velocity and between-limb synchronization, with larger between-trial differences for participants with worse values. SignificanceThese findings suggest that centre of pressure measures extracted from a single 30-second quiet standing trial may have sufficient reliability for some research studies in chronic stroke. However, for clinical applications, the average of at least two trials may be required.

Low cost inside out wearable trackers can be deployed at scale to measure body motion, but errors in estimated sensor position propagate through coordinate transformations into derived gait and dynamic-stability metrics. Healthy adults walked on a treadmill at 0.5 to 2.0 m/s while VIVE Ultimate Tracker (VUT) and Vicon data were recorded. Data-driven calibration models were developed to correct tracker coordinates and to estimate full body centre of mass (CoM) from a sacrum-only configuration. Agreement with Vicon was assessed using RMSE, mixed-effects Bland-Altman limits of agreement, MAE, and intraclass correlation coefficients. Calibration improved coordinate-level agreement. For gait parameters, model-corrected VUT showed small errors against Vicon (MAE: 0.24 to 0.71 mm step height, 1.73 to 4.63 mm step length, 0.15 to 0.95 mm step width, 0.26 to 0.88 mm foot clearance). Proxy CoM-derived margin of stability (MoS) agreed excellently with Vicon. For the sacrum-only pipeline, calibration reduced CoM RMSE from 103.65 to 104.04 mm to 7.55 to 8.95 mm, and markedly reduced systematic error in stability outcomes, with extrapolated CoM bias decreasing from 172.92 to 0.29 mm and MoS bias from -75.09 to -3.54 mm. Data-driven calibration improved the measurement utility of low-cost VUTs, enabling inexpensive, relatively simple gait and stability measurement from a sacrum-only setup in controlled settings.

Detection and characterization of abnormalities of movement are important to develop a method for detecting early signs of Parkinsons disease (PD). Most of the current research in detection of characteristic reduction of movements due to PD, known as parkinsonism, requires using a set of invasive sensors in a clinical or controlled environment. Actigraphy has been widely used in medical research as a non-invasive data acquisition method in free-living conditions for long periods of time. The proposed algorithm uses triaxial accelerometer data obtained through actigraphy to detect walking bouts at least 10 seconds long and characterize them using cadence and arm swing. Accurate detection of walking periods is the first step toward the characterization of movement based on gait abnormalities. The algorithm was based on a Walking Score (WS) derived using the value of the auto-correlation function (ACF) for the Resultant acceleration vector. The algorithm achieved a precision of 0.90, recall of 0.77, and F1 score of 0.83 compared to the expert scoring for walking bout detection. We additionally described a method to measure arm swing amplitude.

AimsBalance requires the cortical control of visual, somatosensory, and vestibular inputs. The aim of this cross-sectional study was to compare the contributions of each of these systems on postural control and cortical activity using a sensory reweighting approach between participants with Parkinsons disease (PD) and controls. MethodsTen participants with PD (age: 72 {+/-} 9; 3 women; Hoehn & Yahr: 2 [1.5 - 2.50]) and 11 controls (age: 70 {+/-} 3; 4 women) completed a sensory organization test in virtual reality (VR-SOT) while cortical activity was being recorded using electroencephalography (EEG). Conditions 1 to 3 were completed on a stable platform; conditions 4 to 6 on a foam. Conditions 1 and 4 were done with eyes open; conditions 2 and 5 in a darkened VR environment; and conditions 3 and 6 in a moving VR environment. Linear mixed models were used to evaluate changes in center of pressure (COP) displacement and EEG alpha and theta/beta ratio power between the two groups across the postural control conditions. Condition 1 was used as reference in all analyses. ResultsParticipants with PD showed greater COP displacement than controls in the anteroposterior (AP) direction when relying on vestibular input (condition 5; p<0.0001). The mediolateral (ML) COP sway was greater in PD than in controls when relying on the somatosensory (condition 2; p = 0.03), visual (condition 4; p = 0.002), and vestibular (condition 5; p < 0.0001) systems. Participants with PD exhibited greater alpha power compared to controls when relying on visual input (condition 2; p = 0.003) and greater theta/beta ratio power when relying on somatosensory input (condition 4; p = 0.001). ConclusionsPD affects reweighting of postural control, exemplified by greater COP displacement and increased cortical activity. Further research is needed to establish the temporal dynamics between cortical activity and COP displacement.

BackgroundDue to the imposed constant belt speed, motorized treadmills are known to change linear and non-linear gait variability outcomes. This is particularly true of patients with Parkinsons disease where the treadmill can act as an external pacemaker. Therefore, the use of treadmills is generally not recommended when quantifying gait variability. Self-paced treadmills allow for updating the belt speed relative to the walking speed of the subject and might, therefore, be a useful tool for the collection of long consecutive walking trials, necessary for gait variability observations. Research questionTo validate gait variability measures collected on a self-paced treadmill as compared to overground walking. MethodsThirteen healthy subjects and thirteen patients with Parkinsons disease performed 5 - 8 minute long walking trials: overground, on a treadmill at a constant speed, as well as in three different self-paced treadmill modes. Stride times and stride lengths were recorded using a validated IMU-system and variability was quantified using the coefficient of variation, sample entropy, and detrended fluctuation analysis. Overground and treadmill trials were compared using Pearsons correlation coefficient, method error, and Bland and Altman analysis. ResultsFor healthy subjects, the self-paced treadmill resulted in increased correlation coefficients of 0.57 - 0.74 as compared to a constant speed treadmill. Correlation coefficients for stride length variability between overground and treadmill walking were not significant. For patients, generally, large errors of 33-40% of stride time variability were observed between overground and treadmill walking. Stride length variability is most similar at a constant belt speed and shows errors of 14-39%. SignificanceDespite an improvement of temporal gait variability validity in the self-paced mode for healthy subjects, the large systematic and random errors between overground and self-paced treadmill walking prohibit meaningful gait variability observations in patients with Parkinsons disease using self-paced treadmills.

BackgroundAccurate measurement of ankle range of motion (ROM) is essential for diagnosing and treating musculoskeletal conditions, optimizing athletic performance, and managing neurological disorders such as Parkinsons disease. This study evaluates the novel Ambulosono device, a sensor-based tool, against the traditional goniometer for assessing Ankle ROM in healthy participants. MethodsA comparative cross-sectional study was conducted on 54 healthy participants aged 15 to 24 years. Ankle ROM was measured using the goniometer, placed on the lateral malleolus, and the Ambulosono device, secured on the dorsum of the foot. Participants performed maximal dorsiflexion and plantarflexion with knees extended, and five measurements were taken per device on both feet in randomized order. Statistical analyses included descriptive statistics, Bland-Altman plots, and Intraclass Correlation Coefficients (ICCs) to assess agreement and reliability. ResultsMean goniometer ROM was 58.44{degrees} (SD=5.54) versus Ambulosonos 56.80{degrees} (SD=3.88). No significant differences emerged between devices, foot sides, or gender. Bland-Altman analysis indicated agreement without P proportional bias. Reliability was excellent (Cronbachs alpha=0.983, ICC=0.983). ConclusionThe Ambulosono device is a robust tool that offers a reliable alternative to traditional goniometry, with advantages such as real-time feedback and reduced inter-rater variability. Its potential applications extend beyond clinical and athletic settings to include neurological rehabilitation and remote patient monitoring. Further research is warranted to validate its efficacy across diverse populations and real-world scenarios.

Symptoms of multiple sclerosis (MS) are highly variable and include impaired senses, instability, and fatigue, making persons with MS (PwMS) ill-suited for the traditional six-month office visit paradigm. Instead, PwMS are well suited for remote monitoring to capture their true impairment. The objective of this work is to investigate the value of free-living data compared to prescribed walking tasks. Wearable sensor data were utilized from six-weeks of data from 25 PwMS. Participants completed a daily 1-minute walk, 30-second standing task, and patient reported outcomes of balance confidence (ABC), fatigue (MFIS) and walking impairment (MSWS). We compared gait and sway, as well as correlated them to patient reported outcomes (PRO). Lastly, we used a regression to determine the variance accounted for (VAF) in each PRO by different data sources. Temporal gait features were moderately correlated (r=0.6 - 0.81) between passive and prescribed walking, however, no postural sway features were correlated with each other. Passive data was found to have greater clinical relevance in our sample of PwMS compared to prescribe tasks for both gait and sway analyses. Passive sway features were found to be moderately related to ABC, MFIS, and MSWS (r=0.42-0.74, VAF=0.42-0.7), while prescribe sway was only correlated to MFIS (r = 0.41, VAF = 0.44). Both passive and prescribed measures of gait were related to ABC and MSWS; stronger relationships were found in the passive data (r = 0.42-0.78, VAF = 0.64-0.78). Additionally, we found the performance increased for passive monitoring with a shorter monitoring duration - highlighting the need to properly match the monitoring and analysis duration to the population. Overall, our findings highlight the importance of including passive free-living analysis in future studies.

Parkinsons disease (PD) is associated with debilitating motor symptoms, including gait impairments and stooped posture. While markerless motion capture offers a scalable alternative to quantify these deficits, the acute biomechanical effects of interventions like Dry Needling (DN) on PD gait remain under-investigated. This randomized clinical trial investigated the acute effects of upper trapezius myofascial release via DN on gait and turning biomechanics in individuals with PD, utilizing a 3D markerless motion capture system. Thirty-eight participants with mild-to-moderate PD and bilateral upper trapezius trigger points were randomly assigned to a DN or Sham group. Gait was evaluated during a modified Timed Up and Go (TUG) test at baseline, immediately post-intervention, and at a one-week follow-up. Video data were processed using the open-source vaila toolbox, which applied a rigorous spatial segmentation algorithm to isolate postural transitions, steady-state gait, and turning phases. Thirty-seven participants completed the protocol (DN = 18; Sham = 19). The algorithm-driven markerless pipeline successfully extracted high-fidelity spatiotemporal parameters and automated gait event detection. However, the quantitative analysis revealed no significant Group x Time interactions for spatiotemporal parameters or turning kinematics, with both groups exhibiting similar trajectories across all assessment points. In conclusion, a single session of upper trapezius DN does not yield superior acute improvements in gait or turning biomechanics compared to a sham intervention in PD, suggesting that macro-level motor adaptations likely require cumulative therapeutic sessions. Nevertheless, the successful implementation of this markerless workflow provides an objective, cost-effective framework for precisely tracking phase-specific kinematic changes in routine clinical settings.

BackgroundPatients with nervous system and musculoskeletal diseases display gait disturbance that is a leading cause of falls. Identification of disease-specific movement hallmarks is therefore an essential first step in preventing falls. Since turning, a common daily activity, is a unique movement that requires inter-limb spatial coordination, turning may be a suitable observational target for the identification of disease-specific movement disorder. However, to date, few comprehensive systematic review regarding disease-specific alterations in turning movement is available. Research questionThis systematic review with meta-analysis summarized the level of knowledge regarding movement disorders during turning in patients with nervous system and musculoskeletal diseases. MethodsA systematic review was conducted of papers throughout 2021 in accordance with PRISMA guideline. Including criteria were (1) were published in a peer-reviewed journal, (2) were written in English, (3) included adult patients who were diagnosed with musculoskeletal or nervous system diseases, (4) had a control group of age-matched healthy adults, and (5) outcomes included turning parameters. ResultsMeta-analysis revealed a significantly larger step number, longer turn duration, and shorter step length in patients with Parkinsons disease (PD) than in controls during the 180{degrees} turn, suggesting that these biomechanical alterations may be, at least in part, movement disorders associated with PD. Notably, this review identified methodological heterogeneity for turning movement assessments, which limited the identification of disease-specific movement disorders. SignificanceThis work serves as a call to action for the establishment of a standard assessment protocol towards the identification of disease-specific turning movement disorders and effective disease screening.

Falls occur more often as we age. To identify people at risk of falling, balance analysis requires an accurate base-of-support model. We previously developed a functional base-of-support (fBOS) model for standing young adults and showed that its area is smaller than the footprint area. Our fBOS model is a polygon that contains centre-of-pressure (COP) trajectories recorded as standing participants move their COP in the largest possible loop while keeping their feet flat on the ground. Here we assess how the size of the fBOS changes with age by comparing 38 younger (YA), 14 middle-aged (MA), and 34 older adults (OA). The fBOS area is smaller in older adults: OA area is 58% of the YA area (p < 0.001), and 59% of the MA area (p = 0.001), with no difference between YA and MA. The reduction in fBOS area among the OA is primarily caused by a reduction in the length of the fBOS. In addition, among older adults smaller fBOS areas correlated with a lower score on the Short Physical Performance Battery ({tau}=0.28, p = 0.04), a reduced walking speed ({tau}=0.25, p = 0.04), and a higher frailty level (p = 0.09). So that others can extend our work, we have made our fBOS models available online.

BackgroundMotion sensors are widely used for gait analysis. ORPHE ANALYTICS is a motion-sensor-based gait analysis system. The validity of commercial gait analysis systems is of great interest to clinicians because calculating position/angle-level gait parameters using motion sensor data potentially produces an error in the integration process; moreover, the validity of ORPHE ANALYTICS has not yet been examined. Research questionHow valid are the position/angle-level gait parameters calculated using ORPHE ANALYTICS relative to those calculated using conventional optical motion capture? MethodsNine young adults performed gait tasks on a treadmill at speeds of 2-12 km/h. The motion sensors were mounted on the shoe midsole (plantar-embedded) and shoe instep (instep-mounted). The three-dimensional marker position data of the foot as well as the acceleration and angular velocity data of the motion sensors were collected. The position/angle-level gait parameters were calculated from motion sensor data obtained using ORPHE ANALYTICS and optical motion capture data. Intraclass correlation coefficients [ICC(2,1)] were calculated for relative validities, and Bland-Altman plots were plotted. ResultsEight items, namely, stride duration, stride length, stride frequency, stride speed (plantar-embedded), vertical height (plantar-embedded), stance phase duration, swing phase duration, and sagittal angleIC, exhibited excellent relative validities [ICC(2,1) > 0.9]. In contrast, the sagittal angleTO demonstrated good relative validity [ICC(2,1) = 0.892-0.833], while the frontal angleIC exhibited moderate relative validity [ICC(2,1) = 0.566-0.627]. SignificanceORPHE ANALYTICS, a motion-sensor-based gait analysis system, was found to exhibit excellent relative validity for most gait parameters. This finding suggests its feasibility for gait analysis outside the laboratory setting. HighlightsO_LIGait-parameter validities were examined for treadmill-based gait tasks at 2-12 km/h. C_LIO_LIMost gait parameters showed excellent relative validity with optical motion capture. C_LIO_LIShoe midsole-embedded sensors had higher validities than instep-mounted sensors. C_LIO_LIORPHE ANALYTICS is potentially useful in clinical measurements. C_LI

Gait impairment is a hallmark symptom of Parkinsons disease (PD). However, traditional clinical assessments cannot capture real-world motor fluctuations, as they are sparsely performed. This study was designed to test and validate the use of nearables and passive sensing technologies, including Kinect RGB-D cameras and ultra-wideband (UWB) radar, for continuous, objective assessment of gait fluctuations in PD within a home-like setting. Fifteen PD patients with mild symptoms and fourteen age-and sex-matched healthy controls (HC) performed 4-meter walking tasks in a living lab facility. Patients repeated the task during both "ON" and "OFF" states of their daily medication cycle. Gait features, including stride length, stride time, and gait speed, were extracted from Kinect, radar, and a ground-truth smart floor. Data were analyzed to evaluate inter-sensor agreements and detect group-level differences. Stride time demonstrated the highest agreement between devices (r=0.903), while stride length showed weaker agreement (r=0.779), with Kinect tending to overestimate. Despite lower agreement, stride length from both Kinect and radar successfully distinguished PD OFF from HC (camera q=0.020; radar q=0.005) and radar was able to further differentiate ON and OFF states (q=0.020). Neither device differentiated PD ON from HC, indicating medication reduced observable gait differences. This study demonstrates that passive, contact-free sensing technologies such as depth cameras and UWB radars can effectively monitor gait in PD within naturalistic environments. While some spatial metrics, like stride length, show device discrepancies, both systems reliably capture gait patterns and medication-dependent changes, supporting their use for longitudinal, real-world monitoring of Parkinsons motor symptoms.

BackgroundBalance instability is a major contributor to disability and falls in people with Parkinsons disease (PwP) and is often insufficiently explained by motor impairment alone. Altered awareness of motor control has been suggested to contribute to sensorimotor dysfunction in PwP, but its relationship with balance performance is poorly understood. ObjectiveTo determine whether awareness of balance control, assessed using a control detection task (CDT), differs between healthy controls (HC) and PwP, and whether CDT performance is associated with balance-related measures. MethodsHealthy older adults (n=20) and PwP (n=22) performed a standing version of the CDT based on center-of-pressure (COP) control, using a force plate. CDT accuracy was used as the primary outcome measure. Static balance during quiet standing was assessed using the COP trajectory length and rectangular area. Dynamic standing balance was assessed using the Index of Postural Stability (IPS). Group differences were examined by independent-samples t-tests. Correlations between CDT accuracy and balance measures were analyzed. ResultsThe PwP group showed significantly lower CDT accuracy. Higher CDT accuracy was associated with better static balance in the HC group and the combined sample, and with higher IPS primarily in the PwP group. ConclusionsMotor awareness during postural tasks is altered in PwP and is associated with balance control. These findings suggest that balance instability in Parkinsons disease may involve altered balance-related action-outcome monitoring in addition to motor dysfunction.

A common clinical impression is that individuals with stroke tend to gaze downward while walking--focusing on the walking surface a short distance ahead for extended periods. However, this impression has not been formally verified, and thus, whether this is a true phenomenon--and, if so, what drives it--remains unknown. In this observational study, we examined the spatial and temporal aspects of walking gaze behavior in individuals with stroke and compared them to those of healthy controls. Our results indicate that individuals with stroke exhibit a greater tendency to gaze downward while walking compared to healthy controls. While the shorter look-ahead distances observed may be attributed to slower walking speeds, the prolonged duration of downward gazing (DWG) cannot be explained by speed alone. Instead, both the short look-ahead distance and prolonged DWG duration were associated with anxiety--particularly fear of falling--as well as impaired balance and gait control. Importantly, while participants reported consciously monitoring their stepping, this tendency was unrelated to DWG, suggesting that downward gaze is unlikely to serve this specific purpose. These findings suggest that anxiety related to walking instability may underlie both the slower walking speeds and the tendency for DWG. Having established the presence of the DWG phenomenon, we propose further investigation into its potential utility as a novel indicator of individuals self-assessed deficits in reactive and/or proactive balance and gait control.

ObjectivesEvaluate procedures for analyzing raw accelerometer data (inertial measurement units) to reconstruct the gait cycle using BioKinetoGraph (BKG). We examine whether footwear and walking surface influence gait (BKG) and evaluate test-retest reliability. We also examine the association between BKG and NIH 4-meter gait, and compare BKG to other neurobehavioral measures for predicting concussion symptoms. MethodsIn Study 1, a within-subjects design with 60 participants was used to examine the effects of footwear (shoes/no-shoes) and walking surface (tile floor/grass) on BKG data, and evaluate retest reliability. Study 2 employed a cross-sectional, cohort design of 1,008 participants to assess BKGs correlation with NIH 4-m gait, and prediction of Centers of Disease Control and Prevention (CDC) concussion symptoms relative to previously validated speed and balance measures. Results2x2 ANOVAs illustrate footwear and walking surface effects on BKG for the power, stride, stability, and symmetry, with variable effect sizes. Retest reliability (Pearson rs) for the no shoes/ tile surface condition ranged from .72-.91 (mean = .80, 4-day average interval). BKG correlates significantly with NIH 4-m gait. Regression analyses found BKG predicts CDC concussion symptom endorsement, and outperforms (2-3 fold) BESS and NIH 4-meter gait. ConclusionsGait assessments should be standardized for footwear and especially walking surface. When standardized (no shoes/hard surface) BKG results in strong test-retest reliability. BKG variables are strongly related to NIH 4-m gait, and are superior to standard measures of gait speed and balance when predicting concussion symptoms; offering additional information when predicting the sequalae of concussion. Summary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSO_LISensor technology to evaluate gait has established reliability and predicts a wide range of medical outcomes. However, the influence of footwear and walking surface on gait has not been studied, nor has a sensor-based gait assessment been compared to conventional measures for predicting concussion symptoms. C_LI What this study adds?O_LIGait sensor data is sensitive to footwear and walking surface, but can produce good reliability when these factors are standardized. Gait sensor scores converge with other validated measures of gait, and sensor-based measures of power, stride, symmetry, and stability can outperform established gait speed and balance measures when predicting CDC concussion symptoms. C_LI How this study might affect research, practice, or policy?O_LIUniform standards for footwear and walking surface are needed when evaluating gait in both research and practice, and sensor-based gait measures can be reliably assessed to provide insight into the behavioral sequelae of concussion, that are superior to simple gait speed. C_LI