Arm swing asymmetry in overground walking

Arm swing deviations in patients with Parkinson's disease at different gait velocities

Asymmetry of arm swing (AS) has been described as a characteristic of normal physiological gait. In patients with Parkinson's disease (PWPD), a one-sided reduction of AS can occur already as a prodromal symptom. There is limited evidence regarding AS in PWPD, but a growing interest in AS as a focus of exercise therapy. The differences of AS between 32 healthy subjects (HS) and 36 mildly-to-moderately impaired PWPD were assessed in overground walking at various gait speeds. Assessments were carried out with a sensor-based gait measurement system over a 40 m walk in very slow, slow, preferred, fast, and very fast gait speed. Longitudinal and AS kinematics were compared with ANOVA function and regression analysis. PWPD exhibited a one-sided reduction of AS compared to HS at normal, fast, and very fast walking. AS coordination, representing the timing of reciprocity of right and left AS, was reduced in PWPD in very slow and normal walking. With respect to leg movements, PWPD exhibited an increase in stride time variability in very slow gait. There were no group differences for cadence, stride length, and gait velocity. This study informs about the kinematics of AS at various gait velocities ranging from very slow to very fast in mildly-to-moderately impaired PWPD. Reduced one-sided AS can be considered as a very early sign of parkinsonian gait disturbance that precedes alterations of locomotive leg movements and improves at faster gait speeds.

Automatic ML-based vestibular gait classification: examining the effects of IMU placement and gait task selection

BACKGROUND

Vestibular deficits can impair an individual's ability to maintain postural and/or gaze stability. Characterizing gait abnormalities among individuals affected by vestibular deficits could help identify patients at high risk of falling and inform rehabilitation programs. Commonly used gait assessment tools rely on simple measures such as timing and visual observations of path deviations by clinicians. These simple measures may not capture subtle changes in gait kinematics. Therefore, we investigated the use of wearable inertial measurement units (IMUs) and machine learning (ML) approaches to automatically discriminate between gait patterns of individuals with vestibular deficits and age-matched controls. The goal of this study was to examine the effects of IMU placement and gait task selection on the performance of automatic vestibular gait classifiers.

METHODS

Thirty study participants (15 with vestibular deficits and 15 age-matched controls) participated in a single-session gait study during which they performed seven gait tasks while donning a full-body set of IMUs. Classification performance was reported in terms of area under the receiver operating characteristic curve (AUROC) scores for Random Forest models trained on data from each IMU placement for each gait task.

RESULTS

Several models were able to classify vestibular gait better than random (AUROC > 0.5), but their performance varied according to IMU placement and gait task selection. Results indicated that a single IMU placed on the left arm when walking with eyes closed resulted in the highest AUROC score for a single IMU (AUROC = 0.88 [0.84, 0.89]). Feature permutation results indicated that participants with vestibular deficits reduced their arm swing compared to age-matched controls while they walked with eyes closed.

CONCLUSIONS

These findings highlighted differences in upper extremity kinematics during walking with eyes closed that were characteristic of vestibular deficits and showed evidence of the discriminative ability of IMU-based automated screening for vestibular deficits. Further research should explore the mechanisms driving arm swing differences in the vestibular population.

Upper-extremity kinematics and interlimb movement correlation in persons with Parkinson Disease on irregular terrain, cross-slope, and under dual-task condition

Background

A defining clinical characteristics of Parkinson disease is reduced upper-extremity movements. Irregular terrain, the presence of a cross slope, and dual-task conditions have been found to alter the lower-limb gait characteristics of persons with Parkinson disease but there is little information how different environmental and cognitive conditions impact upper-limb kinematics as well as interlimb movement correlation.

Research question

Do environmental conditions, such as irregular terrain and the presence of cross slope, as well as dual-task condition impact the upper-extremity kinematics and interlimb movement correlation of persons with Parkinson disease compared to healthy, age-matched controls?

Methods

Three-dimensional whole-body gait data were collected for nine participants with mild-to-moderate Parkinson disease and nine healthy age-matched control participants. All participants ambulated on a regular terrain, irregular terrain, with and without cross slope, and under dual and single-task conditions. The primary outcomes were arm swing magnitude, arm swing asymmetry, and normalized cross-correlation between the ipsilateral arms and contralateral legs, which characterized movement correlation.

Results

For all conditions, persons with Parkinson disease exhibited reduced arm swing magnitude and greater arm swing asymmetry compared to the healthy controls. All participants increased their arm swing magnitude on the irregular surface and under the dual-task condition. In the healthy group, the arm swing asymmetry was invariant to terrain but declined under the dual-task condition while the persons with Parkinson disease exhibited increased asymmetry on the cross slope, on the irregular terrain, and under the dual-task condition. Interlimb movement correlation decreased on the irregular terrain for the persons with Parkinson disease while the healthy group exhibited decreased interlimb movement correlation on the cross slope as well as under the dual-task condition.

Significance

Persons with Parkinson disease were able to increase their arm swing magnitude when their balance was challenged and the most significant threat to their safety as defined by the greatest reduction in the interlimb movement correlation was the irregular terrain.

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Persons with PD had reduced arm swing magnitude compared to healthy participants.

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Persons with PD increased arm swing magnitude when their balance was challenged.

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The irregular terrain was the condition that impacted both health groups the most.

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Dual-task increased arm swing magnitude and reduced interlimb movement correlation.

Effect of Unilateral Shoulder Disorder on the Stance Phase of Human Gait

Background. Gait analysis systems serve as important tools for assessing disturbed gait patterns. Amongst other factors, functional limitations of the shoulder joint may relate to such disturbances. Patient-reported outcome measures, assessment of pain, and active range of motion are commonly used to describe shoulder impairment. Purpose. The aim of this cohort study was to evaluate the impact of unilateral limitations of shoulder mobility and pain on gait patterns and to detect correlations between pain, shoulder mobility, and particular phases of human gait using a Zebris gait analysis system. Methods. 20 subjects with unilaterally restricted mobility and pain of the affected shoulder and a control group of 10 healthy subjects underwent a gait analysis. Various gait parameters, the DASH score, pain at rest and movement of the affected shoulder, and the active range of motion (aROM) for shoulder flexion and abduction were recorded. Results. We determined significant differences of the duration of the loading response ( $p$  = 0.021), midstance ( $p$  = 0.033), and the terminal stance phase ( $p$  = 0.019) between the shoulder group and the control group, with a shorter loading response phase and a longer terminal stance phase of the affected side in the shoulder group. In the shoulder group, we found significant correlations between the DASH and the duration of the midstance phase ( $p$  = 0.023) and the terminal stance phase ( $p$  = 0.038). In addition, there was a significant correlation between shoulder flexion and the duration of the midstance phase ( $p$  = 0.047).

Neural correlates of dual-task walking in people with central neurological disorders: a systematic review

BACKGROUND

People with central neurological disorders experience difficulties with dual-task walking due to disease-related impairments. The objective of this review was to provide a comprehensive examination of the neural correlates (structural/functional brain changes) of dual-task walking in people with Parkinson's disease (PD), multiple sclerosis (MS), stroke, and Alzheimer's disease (AD).

METHODS

A systematic review of the literature was conducted, following PRISMA guidelines, on Medline, Embase, and Scopus. Included studies examined the relationship between structural and functional brain imaging and dual-task walking performance in people with PD, MS, stroke, and AD. Articles that met the inclusion criteria had baseline characteristics, study design, and behavioral and brain outcomes extracted. Twenty-three studies were included in this review.

RESULTS

Most structural imaging studies (75%) found an association between decreased brain integrity and poor dual-task performance. Specific brain regions that showed this association include the striatum regions and hippocampus in PD and supplementary motor area in MS. Functional imaging studies reported an association between increased prefrontal activity and maintained (compensatory recruitment) or decreased dual-task walking performance in PD and stroke. A subset (n = 2) of the stroke papers found no significant correlations. Increased supplementary motor area activity was associated with decreased performance in MS and stroke. No studies on AD were identified.

CONCLUSION

In people with PD, MS, and stroke, several neural correlates of dual-task walking have been identified, however, the direction of the association between neural and performance outcomes varied across the studies. The type of cognitive task used and presentation modality (e.g., visual) may have contributed to these mixed findings.

Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data

One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensive gait analysis, such as the Dresden protocol for multidimensional walking assessment, covers several facets of walking impairment including a 2-min walk test, in which the distance taken by the patient in two minutes is measured by an odometer. Using this approach, it is questionable how precise the measuring methods are at recording the distance traveled. In this project, we investigate whether the current measurement can be replaced by a digital measurement method based on accelerometers (six Opal sensors from the Mobility Lab system) that are attached to the patient’s body. We developed two algorithms using these data and compared the validity of these approaches using the results from 2-min walk tests from 562 pwMS that were collected with a gold-standard odometer. In 48.4% of pwMS, we detected an average relative measurement error of less than 5%, while results from 25.8% of the pwMS showed a relative measurement error of up to 10%. The algorithm had difficulties correctly calculating the walking distances in another 25.8% of pwMS; these results showed a measurement error of more than 20%. A main reason for this moderate performance was the variety of pathologically altered gait patterns in pwMS that may complicate the step detection. Overall, both algorithms achieved favorable levels of agreement (r = 0.884 and r = 0.980) with the odometer. Finally, we present suggestions for improvement of the measurement system to be implemented in the future.

The Power of Musification: Sensor-Based Music Feedback Improves Arm Swing in Parkinson's Disease

Background

Reduction of arm swing during gait is an early and common symptom in Parkinson's disease (PD). By using the technology of a mobile phone, acceleration of arm swing can be converted into a closed‐loop musical feedback (musification) to improve gait.

Objectives

To assess arm swing in healthy subjects and the effects of musification on arm swing amplitude and other gait parameters in patients with PD.

Methods

Gait kinematics were analyzed in 30 patients during a 320 m walk in 3 different conditions comprising (1) normal walking; (2) focused swinging of the more affected arm; and (3) with musification of arm swing provided by the iPhone application CuraSwing. The acceleration of arm swing was converted into musical feedback. Arm swing range of motion and further gait kinematics were analyzed. In addition, arm swing in patients was compared to 32 healthy subjects walking at normal, slow, and fast speeds.

Results

Musification led to a large and bilateral increase of arm swing range of motion in patients. The increase was greater on the more affected side of the patient (+529.5% compared to baseline). In addition, symmetry of arm swing, sternum rotation, and stride length increased. With musical feedback patients with PD reached arm swing movements within or above the range of healthy subjects.

Conclusions

Musification has an immediate effect on arm swing and other gait kinematics in PD. The results suggest that closed‐loop musical feedback is an effective technique to improve walking in patients with PD.

Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

In multiple sclerosis (MS), gait impairment is one of the most prominent symptoms. For a sensitive assessment of pathological gait patterns, a comprehensive analysis and processing of several gait analysis systems is necessary. The objective of this work was to determine the best diagnostic gait system (DIERS pedogait, GAITRite system, and Mobility Lab) using six machine learning algorithms for the differentiation between people with multiple sclerosis (pwMS) and healthy controls, between pwMS with and without fatigue and between pwMS with mild and moderate impairment. The data of the three gait systems were assessed on 54 pwMS and 38 healthy controls. Gaussian Naive Bayes, Decision Tree, k-Nearest Neighbor, and Support Vector Machines (SVM) with linear, radial basis function (rbf) and polynomial kernel were applied for the detection of subtle walking changes. The best performance for a healthy-sick classification was achieved on the DIERS data with a SVM rbf kernel (κ = 0.49 ± 0.11). For differentiating between pwMS with mild and moderate disability, the GAITRite data with the SVM linear kernel (κ = 0.61 ± 0.06) showed the best performance. This study demonstrates that machine learning methods are suitable for identifying pathologic gait patterns in early MS.

Slow walking synergies reveal a functional role for arm swing asymmetry in healthy adults: A principal component analysis with relation to mechanical work

INTRODUCTION

The purpose of this study was to reveal a functional role for arm-swing asymmetry during gait in healthy adults. To this end, the primary aim was to investigate the role of neuromuscular control on the asymmetry of propulsive and collision joint work at either end of the double-support phase (W_DS) in the context of sidedness. The secondary aim was to investigate the effect of neuromuscular control on propulsive and collision joint work at either end of the single-support phase (W_SS) in the context of arm-swing asymmetry.

METHODS

Slow -walking trials of 25 participants were analysed using principal component analysis to generate movement synergies (PM_k). Independent variables included the tightness of neuromuscular control (N₁) formulated from the first PM_k and the directional Arm-swing asymmetry index (dASI). Dependent variables included the difference between double-support collision and propulsive joint work (W_DS) and a ratio consisting of the difference between single-support collision and propulsive work of both sides (W_SS). A linear mixed-effects model was utilized for aim 1 while a multiple linear regression analysis was undertaken for aim 2.

RESULTS

Healthy adult gait was accompanied by a left-side dominant arm-swing on average. For aim 1, N₁ demonstrated a significant negative effect on W_DS while sidedness had a negative direct effect and positive indirect effect through N₁ on W_DS. The most notable finding was the interaction between dASI and N₁ which demonstrated a highly significant positive effect on W_SS.

INTERPRETATION

Evidence was put forward that arm-swing asymmetry during gait is related to footedness among healthy adults. Future studies should look to formally confirm this finding.

Quantification of Arm Swing during Walking in Healthy Adults and Parkinson's Disease Patients: Wearable Sensor-Based Algorithm Development and Validation

Neurological pathologies can alter the swinging movement of the arms during walking. The quantification of arm swings has therefore a high clinical relevance. This study developed and validated a wearable sensor-based arm swing algorithm for healthy adults and patients with Parkinson’s disease (PwP). Arm swings of 15 healthy adults and 13 PwP were evaluated (i) with wearable sensors on each wrist while walking on a treadmill, and (ii) with reflective markers for optical motion capture fixed on top of the respective sensor for validation purposes. The gyroscope data from the wearable sensors were used to calculate several arm swing parameters, including amplitude and peak angular velocity. Arm swing amplitude and peak angular velocity were extracted with systematic errors ranging from 0.1 to 0.5° and from −0.3 to 0.3°/s, respectively. These extracted parameters were significantly different between healthy adults and PwP as expected based on the literature. An accurate algorithm was developed that can be used in both clinical and daily-living situations. This algorithm provides the basis for the use of wearable sensor-extracted arm swing parameters in healthy adults and patients with movement disorders such as Parkinson’s disease.

Three-dimensional thoracic and pelvic kinematics and arm swing maximum velocity in older adults using inertial sensor system

Understanding characteristics of torso motion and arm swing of older adults is important. A comprehensive database of three-dimensional thoracic and pelvic kinematics and arm swing maximum velocity of older adults during overground walking is still lacking. Moreover, the relationships between these variables are not fully understood. Therefore, we investigated age and gender effects of three-dimensional thoracic and pelvic ranges of motion and arm swing maximum velocity in 113 healthy old adults (aged 60–89 years) in a 2-min walk test using APDM Movement Monitoring inertial sensor system by two-way ANOVA, and post hoc Bonferroni correction was applied for multiple comparisons between age groups. A paired t-test was used to study the side preference of arm swing maximum velocity. The relationships between variables were investigated via multiple linear regression models. In general, thoracic and pelvic motions showed reduced amplitude with aging. Gait speed, pelvis coronal plane motion and arm swing maximum velocity significantly declined with age. Only the pelvic sagittal plane motion showed a gender main effect. Coronal plane motions of the thorax and pelvis were closely associated, as were sagittal plane motions. Thoracic coronal plane motion was the significant variable influencing pelvic transverse plane motion and vice versa. Gait speed, pelvic coronal and transverse plane motions and thorax sagittal plane motion were significant independent variables that influenced dominant arm maximum velocity. A larger maximum velocity was seen in the left arm. This investigation is valuable for better understanding of gait phenomena and will contribute to identification of gait dysfunction and development of rehabilitation measures.