Deep brain stimulation enhances movement complexity during gait in individuals with Parkinson's disease

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

Baseline Postural Control and Lower Extremity Injury Incidence Among Those With a History of Concussion

CONTEXT

Lower extremity musculoskeletal (LEMSK) injury may be more prevalent among those with a history of sport-related concussion (SRC).

OBJECTIVE

To investigate the relationship between baseline postural control metrics and the LEMSK injury incidence in National Collegiate Athletic Association Division I student-athletes with a history of SRC.

SETTING

National Collegiate Athletic Association Division I athletes.

DESIGN

Cohort study.

PATIENTS OR OTHER PARTICIPANTS

Of 84 total athletes (62 males), 42 had been previously diagnosed with an SRC, and 42 were matched controls based on age, sex, height, weight, and sport.

MAIN OUTCOME MEASURE(S)

During the preseason baseline evaluation, all participants performed 3 trials of eyes-open and eyes-closed upright quiet stance on a force platform. Medical charts were assessed for all the LEMSK injuries that occurred from preseason baseline to 1 year later. Center-of-pressure data in the anteroposterior and mediolateral directions were filtered before we calculated root mean square and mean excursion velocity; the complexity index was calculated from the unfiltered data. Factorial analysis-of-variance models were used to examine differences between groups and across conditions for root mean square; mean excursion velocity, complexity index, and tests of association to examine between-groups LEMSK differences; and logistic regression models to predict LEMSK.

RESULTS

Concussion history and injury incidence were related in the SRC group (P = .043). The complexity index of the SRC group was lower with eyes closed (14.08 ± 0.63 versus 15.93 ± 0.52) and eyes open (10.25 ± 0.52 vs 11.80 ± 0.57) in the mediolateral direction than for the control participants (P < .05). Eyes-open root mean square in the mediolateral direction was greater for the SRC group (5.00 ± 0.28 mm) than the control group (4.10 ± 0.22 mm). Logistic regression models significantly predicted LEMSK only in control participants.

CONCLUSIONS

These findings may suggest that LEMSK after SRC cannot be predicted from postural-control metrics at baseline.

Physiological complexity of gait between regular and non-exercisers with Parkinson's disease

BACKGROUND

Physiological complexity represents overall health of a system and its underlying capacity to adapt to stresses. The primary purpose of this study was to determine if physiological complexity of gait both ON and OFF anti-Parkinson medication differed between regular and non-exercisers with Parkinson's disease.

METHODS

Twenty participants with idiopathic Parkinson's disease were enrolled in this cross-sectional study (regular exercisers n = 10, non-exercisers n = 10). Two data collection sessions were completed during a single visit, first after a 12-hour overnight withdrawal from anti-Parkinson medications (OFF), and again one-hour after taking anti-Parkinson medications (ON). During each session participants completed a 2-minute walking task at their preferred pace while wearing wireless inertial measurement units on each lower extremity segment (thigh, shank, foot). Multivariate multiscale entropy was calculated from the tri-axial accelerometer signals and converted to a complexity index for analysis.

FINDINGS

Regular exercisers demonstrated significantly higher complexity indices ON and OFF anti-Parkinson medications compared to non-exercisers (ON F = 3.84 P = 0.02; OFF F = 3.61, P < 0.03). Regular exercisers did not significantly differ in complexity between OFF and ON states (most affected leg F = 0.15 P = 0.71; least affected leg F = 0.30 P = 0.60), but non-exercisers demonstrated significantly decreased complexity in the least affected leg OFF anti-Parkinson medications (F = 5.17 P < 0.04).

INTERPRETATION

Enhanced gait complexity in the regular exercisers may indicate that ongoing exercise is a key ingredient contributing to health in persons with Parkinson's disease. Exercising on a regular basis with Parkinson's disease may augment one's ability to adapt to barriers encountered during gait regardless of medication state.