Clinical Biomechanics · May 23, 2019

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

By Combs-Miller SA, Dugan EL, Beachy A et al.

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.

doi.org/10.1016/j.clinbiomech.2019.05.032PubMed 31146080Populations