Increased Speed Elicited More Automatized but Less Predictable Control in Cyclical Arm and Leg Movements

Abstract

The present study explores variations in the degree of automaticity and predictability of cyclical arm and leg movements. Twenty healthy adults were asked to walk on a treadmill at a lower-than-preferred speed, their preferred speed, and at a higher-than-preferred speed. In a separate, repetitive punching task, the three walking frequencies were used to cue the target pace of the cyclical arm movements. Movements of the arms, legs, and trunk were digitized with inertial sensors. Whereas absolute slope values (|β|) of the linear fit to the power spectrum of the digitized movements (p < .001, η2 = .676) were systematically smaller in treadmill walking than in repetitive punching, sample entropy measures (p < .001, η2 = .570) were larger reflecting the former task being more automated but also less predictable than the latter task. In both tasks, increased speeds enhanced automatized control (p < .001, η2 = .475) but reduced movement predictability (p = .008, η2 = .225). The latter findings are potentially relevant when evaluating effects of task demand changes in clinical contexts.

More Predictable and Less Automatized Movements during Walking -not during Repetitive Punching- in Knee Osteoarthritis

“…These findings imply that the KO group was able to show an altered coordination mode (less predictable and more automatized control of the movement behavior) with an increase of walking speed. This speed effect was found for the control group as well and is in line with earlier studies (van de Ven et al, 2022;Walsh & Taylor, 2019). The found speed effect might be useful and valuable as therapeutic intervention in KO in order to provoke alternative compensatory strategies during walking and try to shift people with KO from 'careful' walkers into 'safer' walkers.…”

“…The data preprocessing and the determination of the kinematics were similar and have been described in detail in our recent study (van de Ven et al, 2022).…”

“…Six wireless 3D-inertial motion capturing sensors (MTw, XSens Technologies B.V., Enschede, The Netherlands) were used to capture the body-segment angular velocity (Filimon, 2015), with a 100 Hz sampling rate, at different segments of the effector system. For both tasks, the sensors were placed according to the sensor placement as described in our previous study (van de Ven et al, 2022). Each sensor sampled in three sensorbased directions (X, Y and Z).…”

Inertial-Sensor-Based Monitoring of Sample Entropy and Peak Frequency Changes in Treadmill Walking during Recovery after Total Knee Arthroplasty

“…Four wireless 3D-inertial motion-capturing sensors (MTw, XSens Technologies B.V., Enschede, The Netherlands) were used to capture the body-segment angular velocity [ 39 ], with a 100 Hz sampling rate, of the lower extremities. Following the sensor placement in our previous study [ 40 ], the sensors for the thighs were attached midway between the trochanter major and lateral femoral epicondyle on the lateral side of the right and left thigh with Velcro straps ( Figure 1 ). For the shanks, the sensors were attached midway between the apex patella and the malleoli on the anterior side of the right and left shank with Velcro straps ( Figure 1 ).…”