Long-term unsupervised mobility assessment in movement disorders.

Mobile health technologies (wearable, portable, body-fixed sensors, or domestic-integrated devices) that quantify mobility in unsupervised, daily living environments are emerging as complementary clinical assessments. Data collected in these ecologically valid, patient-relevant settings can overcome limitations of conventional clinical assessments, as they capture fluctuating and rare events. These data could support clinical decision making and could also serve as outcomes in clinical trials. However, studies that directly compared assessments made in unsupervised and supervised (eg, in the laboratory or hospital) settings point to large disparities, even in the same parameters of mobility. These differences appear to be affected by psychological, physiological, cognitive, environmental, and technical factors, and by the types of mobilities and diagnoses assessed. To facilitate the successful adaptation of the unsupervised assessment of mobility into clinical practice and clinical trials, clinicians and researchers should consider these disparities and the multiple factors that contribute to them.

Assessing Dynamic Balance Performance During Exergaming Based on Speed and Curvature of Body Movements.

Improving balance performance among the elderly is of utmost importance because of the increasing number of injuries and fatalities caused by fall incidences. Digital games controlled by body movements (exergames) have been proposed as a way to improve balance among older people. However, the assessment of balance performance in real-time during exergaming remains a challenging task. This assessment could be used to provide instantaneous feedback and automatically adjust the exergame difficulty. Such features could potentially increase the motivation of the player, thus augmenting the effectiveness of exergames. As clear differences in balance performance have been identified between older and younger people, distinguishing between older and younger adults can help identifying measures of balance performance. We used generalized linear models to investigate whether the assessment of balance performance based on movement speed can be improved by incorporating curvature of the movement trajectory into the analysis. Indeed, our results indicated that curvature improves the performance of the models. Five-fold cross validation indicated that our method is promising for the assessment of balance performance in real-time by showing more than 90% classification accuracy. Finally, this method could be valuable not only for exergaming, but also for real-time assessment of body movements in sports, rehabilitation, and medicine.

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.

Postural threat during walking: effects on energy cost and accompanying gait changes.

BACKGROUND: Balance control during walking has been shown to involve a metabolic cost in healthy subjects, but it is unclear how this cost changes as a function of postural threat. The aim of the present study was to determine the influence of postural threat on the energy cost of walking, as well as on concomitant changes in spatiotemporal gait parameters, muscle activity and perturbation responses. In addition, we examined if and how these effects are dependent on walking speed. METHODS: Healthy subjects walked on a treadmill under four conditions of varying postural threat. Each condition was performed at 7 walking speeds ranging from 60-140% of preferred speed. Postural threat was induced by applying unexpected sideward pulls to the pelvis and varied experimentally by manipulating the width of the path subjects had to walk on. RESULTS: Results showed that the energy cost of walking increased by 6-13% in the two conditions with the largest postural threat. This increase in metabolic demand was accompanied by adaptations in spatiotemporal gait parameters and increases in muscle activity, which likely served to arm the participants against a potential loss of balance in the face of the postural threat. Perturbation responses exhibited a slower rate of recovery in high threat conditions, probably reflecting a change in strategy to cope with the imposed constraints. The observed changes occurred independent of changes in walking speed, suggesting that walking speed is not a major determinant influencing gait stability in healthy young adults. CONCLUSIONS: The current study shows that in healthy adults, increasing postural threat leads to a decrease in gait economy, independent of walking speed. This could be an important factor in the elevated energy costs of pathological gait.

Energy cost of balance control during walking decreases with external stabilizer stiffness independent of walking speed.

Human walking requires active neuromuscular control to ensure stability in the lateral direction, which inflicts a certain metabolic load. The magnitude of this metabolic load has previously been investigated by means of passive external lateral stabilization via spring-like cords. In the present study, we applied this method to test two hypotheses: (1) the effect of external stabilization on energy cost depends on the stiffness of the stabilizing springs, and (2) the energy cost for balance control, and consequently the effect of external stabilization on energy cost, depends on walking speed. Fourteen healthy young adults walked on a motor driven treadmill without stabilization and with stabilization with four different spring stiffnesses (between 760 and 1820 Nm(-1)) at three walking speeds (70%, 100%, and 130% of preferred speed). Energy cost was calculated from breath-by-breath oxygen consumption. Gait parameters (mean and variability of step width and stride length, and variability of trunk accelerations) were calculated from kinematic data. On average external stabilization led to a decrease in energy cost of 6% (p<0.005) as well as a decrease in step width (24%; p<0.001), step width variability (41%; p<0.001) and variability of medio-lateral trunk acceleration (12.5%; p<0.005). Increasing stabilizer stiffness increased the effects on both energy cost and medio-lateral gait parameters up to a stiffness of 1260 Nm(-1). Contrary to expectations, the effect of stabilization was independent of walking speed (p=0.111). These results show that active lateral stabilization during walking involves an energetic cost, which is independent of walking speed.

Effect of balance support on the energy cost of walking after stroke.

OBJECTIVE: To examine the influence of balance support on the energy cost of treadmill and overground walking in ambulatory patients with stroke. DESIGN: Cross-sectional. SETTING: Research laboratory at a rehabilitation center. PARTICIPANTS: Patients with stroke depending on a walking aid in daily life (n=12; walking aid dependent ambulators) and walking aid independent ambulators (n=12), all able to walk for at least 5 minutes. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Energy cost (J·kg(-1)·m(-1)) and temporal gait parameters (walking speed, mean and coefficient of variation of stride time, and symmetry index) were obtained during 4 walking trials at preferred walking speed: overground with and without a cane and on a treadmill with and without handrail support. RESULTS: On the treadmill, handrail support resulted in a significant decrease in energy cost of 16%, independent of the group. Although walking aid dependent ambulators had on average a larger reduction in energy cost than walking aid independent ambulators (19% vs 14%), this interaction did not reach statistical significance (P=.11). Interestingly, overground walking with support resulted in an 8% reduction in energy cost for walking aid dependent ambulators, but a 6% increase for walking aid independent ambulators. The reduction in energy cost with support was accompanied by changes in temporal gait parameters, most notably an increase in stride time and symmetry and a decrease in stride time variability. CONCLUSIONS: Balance support can result in a significant reduction in the energy cost of walking in stroke patients, the magnitude of which depends on walking ability and the walking task. Impaired balance control should not be overlooked as a contributing factor to the increased energy cost of walking in patients with stroke, and improving or assisting balance control should be considered to reduce the energy cost of hemiplegic gait.

Energy expenditure of stroke patients during postural control tasks.

Two common impairments in patients after stroke are loss of balance control and fatigue. We propose that both could be inter-related. The purpose of this study was to investigate the metabolic energy demand for balance control in patients after stroke during upright standing. Ten stroke patients and 12 able-bodied controls performed four 5-min upright standing tasks on a force plate; unperturbed (SU), blindfolded (SUB), on foam surface (SUF) and with feet parallel against each other (SUP). Metabolic energy expenditure, posturography measures and muscle activity (EMG) of lower leg muscles were measured. Patients required on average 125% (33Jkg(-1)s(-1)) more metabolic energy for upright standing under the various conditions than controls. In addition, balance manipulation significantly (p<0.05) affected energy expenditure (21% higher in SUB, 52% in SUF, 40% in SUP compared to SU). Although the increase in energy expenditure was on average twice as high in patients than controls no significant group by condition interaction effect was found. Overall correlations between posturography measures, EMG and energy expenditure (r=0.33-0.60) were significant (p<0.001). We conclude that impaired balance control puts an extra demand on the energy expenditure during motor activities in stroke patients. This should be considered when prescribing interventions aimed at reducing physiological strain.