Grasping an object at floor-level: Is movement strategy a matter of age?

Abstract

Bending down to pick things up off the floor is something that we do every day. This multisegment task can be done in a considerable number of postural configurations because of the large number of degrees of freedom to be controlled when executing it. In this study where volunteers performed a repetitive bending task, multisegment kinematic analysis allowed us to identify seven different bending strategies. Most operators used more than one bending strategy, but no particular strategy-type was found to be specific for a specific age group. However, the number of strategies used by an operator decreased with increasing age. It therefore appears that this factor influences the variability of the strategies used when repeatedly executing a movement involving the lower limbs to collect small objects from floor-level. This decrease in movement variability in senior operators may contribute to their increased risk of developing musculoskeletal disorders.

A first step towards a framework for interventions for individual working practice to prevent work-related musculoskeletal disorders: a scoping review

“…Motoric skill: the worker applies specific trained movements to perform the work with less physical strain. (323 topics) Examples: • More relaxed (neutral) positions in joints • Patient-handling techniques • Accurate acceleration-velocity-timing in movement [ 25 ]; [ 92 ]; [ 105 ]; [ 73 ]; [ 27 ]; [ 28 ]; [ 106 ]; [ 29 ]; [ 107 ] ; [ 30 ]; [ 31 ] ; [ 93 ]; [ 101 ]; [ 108 ]; [ 34 ]; [ 23 ]; [ 94 ]; [ 35 ]; [ 75 ]; [ 76 ]; [ 86 ]; [ 77 ]; [ 109 ]; [ 110 ]; [ 37 ]; [ 111 ]; [ 112 ]; [ 39 ]; [ 113 ]; [ 40 ]; [ 41 ]; [ 42 ]; [ 43 ]; [ 44 ]; [ 87 ]; [ 98 ]; [ 114 ]; [ 79 ]; [ 80 ]; [ 45 ]; [ 115 ]; [ 116 ]; [ 46 ]; [ 47 ]; [ 48 ]; [ 49 ]; [ 117 ]; [ 50 ]; [ 51 ]; [ 52 ]; [ 53 ]; [ 54 ]; [ 55 ]; [ ...…”

Development and Evaluation of a Hybrid Measurement System to Determine the Kinematics of the Wrist

“…The evaluated hybrid system appears to be suitable for ergonomic studies, such as analyzing daily activities or work situations [ 34 ]. Nevertheless, for more detailed biomechanical studies, especially regarding gesture variability, higher precision is required [ 35 , 36 ]. Movements of the upper limb during fine manipulations often exhibit variations below 5°.…”

Exploring the Application of Pattern Recognition and Machine Learning for Identifying Movement Phenotypes During Deep Squat and Hurdle Step Movements

“…As an example, clustering is an unsupervised machine learning method that iteratively clusters data points into groups assigning each observation to a cluster. In the biomechanical analysis of human movement data, clustering has proven useful for grouping participants with similar patterns (Sawacha et al, 2010;Bennetts et al, 2013;Gilles and Wild, 2018) and gait waveforms (Watelain et al, 2000;Toro et al, 2007;Roche et al, 2014). Previously, PCA and clustering techniques have been combined to identify and group distinct spine spatiotemporal movement strategies (Beaudette et al, 2019), which support that a combination of these methods may have utility in objectively identifying movement phenotypes in a movement screening context.…”