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

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

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

How do people with chronic low back pain pick a pencil off the floor?

BACKGROUND

Picking objects off the floor is provocative for people with chronic low back pain (CLBP). There are no clinically applicable methods evaluating movement strategies for this task. The relationship between strategy and multidimensional profiles is unknown.

OBJECTIVE

Develop a movement evaluation tool (MET) to examine movement strategies in people with CLBP (n = 289) picking a pencil off the floor. Describe those movement strategies, and determine reliability of the MET. Explore differences across multidimensional profiles and movement strategies.

METHODS

An MET was developed using literature and iterative processes, and its inter-rater agreement determined. Latent class analysis (LCA) derived classes demonstrating different strategies using six movement parameters as indicator variables. Differences between classes across multidimensional profiles were investigated using analysis of variance, Kruskal-Wallis, or chi-squared tests.

RESULTS

Six movement parameters were evaluated. There was substantial inter-rater agreement (Cohen's Kappa = 0.39-0.79) across parameters. LCA derived three classes with different strategies: Class 1 (71.8%) intermediate trunk inclination/knee flexion; Class 2 (24.5%) greater forward trunk inclination, lower knee flexion; Class 3 (3.7%) lower forward trunk inclination, greater knee flexion. Pain duration differed across all classes (p ≤ .001). Time taken to complete forward bends differed between Class 3 and other classes (p = .024).

CONCLUSIONS

Movement strategies can be reliably assessed using the MET. Three strategies for picking lightweight objects off the floor were derived, which differed across pain duration and speed of movement.

Identification of movement phenotypes from occupational gesture kinematics: Advancing individual ergonomic exposure classification and personalized training

The identification of personalized preventive strategies plays a major role in contrasting the occurrence of work-related musculoskeletal disorders. This requires the identification of distinct movement patterns within large samples and the attribution of a proper risk level to each identified movement phenotype. We assessed the feasibility of this approach by exploiting wearable inertial measurement units to estimate the whole-body kinematics of 43 healthy participants performing 18 reach-to-manipulate movements, which differed based on the object's position in the space and the type of manipulation required. Through unsupervised clustering, we identified multiple movement phenotypes graded by ergonomic performance. Furthermore, we determined which joints mostly contributed to instantiating the ergonomic differences across clusters, emphasizing the importance of monitoring this aspect during occupational gestures. Overall, our analysis suggests that movement phenotypes can be identified within occupational motor repertoires. Assigning individual performance to specific phenotypes has the potential to inform the development of more effective and tailored interventions.

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

BACKGROUND

Work-related musculoskeletal disorders (WMSDs) are a key topic in occupational health. In the primary prevention of these disorders, interventions to minimize exposure to work-related physical risk factors are widely advocated. Besides interventions aimed at the work organisation and the workplace, interventions are also aimed at the behaviour of workers, the so-called individual working practice (IWP). At the moment, no conceptual framework for interventions for IWP exists. This study is a first step towards such a framework.

METHODS

A scoping review was carried out starting with a systematic search in Ovid Medline, Ovid Embase, Ovid APA PsycInfo, and Web of Science. Intervention studies aimed at reducing exposure to physical ergonomic risk factors involving the worker were included. The content of these interventions for IWP was extracted and coded in order to arrive at distinguishing and overarching categories of these interventions for IWP.

RESULTS

More than 12.000 papers were found and 110 intervention studies were included, describing 810 topics for IWP. Eventually eight overarching categories of interventions for IWP were distinguished: (1) Workplace adjustment, (2) Variation, (3) Exercising, (4) Use of aids, (5) Professional skills, (6) Professional manners, (7) Task content & task organisation and (8) Motoric skills.

CONCLUSION

Eight categories of interventions for IWP are described in the literature. These categories are a starting point for developing and evaluating effective interventions performed by workers to prevent WMSDs. In order to reach consensus on these categories, an international expert consultation is a necessary next step.

Do age and work pace affect variability when performing a repetitive light assembly task?

This study examined whether a repetitive light assembly task could be performed according to different movement sequences identified as ways of doing (WoD), and whether the age of the participants or the work pace affected the number of WoDs selected by each participant, or the kinematic parameters for each WoDs. For two work paces, 62 right-handed men in 3 age-groups were asked to fix a handle on a base with 2 nuts without discontinuity for a period of 20 min; no assembly procedure was demonstrated. The WoDs were characterized by a cross tabulation video coding method, and by measuring vertical force applied and the parameters of upper limb kinematics, as well as these measures' approximate entropy (ApEN). Five main different WoDs were used. Although most participants varied their WoD, neither participant age nor work pace affected the number of WoD they used. However, the WoDs differed from each other by the sequence of movements and by the level of ApEn of their kinematic variables without interfering with the production rate. Allowing operators to vary their WoDs when performing repetitive tasks could reduce strain on the locomotor system.

Temporal leeway: can it help to reduce biomechanical load for older workers performing repetitive light assembly tasks?

Current industrial production systems allow assembly of customised products which include additional elements distinguishing them from a reference model. This customisation can result in significant additional time constraints which compel workers to complete their tasks faster, which may pose problems for older workers. The objective of this laboratory study was to investigate the impact of restrictive or flexible pacing during assembly of customised products among groups of younger and older participants. The data gathered were used to analyse cycle-time, assembly performance, muscular load, and kinematic adaptations. The flexible pacing condition was found to improve production performance, increasing customised assembly cycle-time and reducing biomechanical load, for both young and older participants. However, as the task required fine manual dexterity, older participants were subjected to a higher biomechanical load, even in the flexible pacing scenario. These results should encourage assembly-line designers to allow flexible time constraints as much as possible and to be particularly attentive to the needs of older workers.

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

Background

Movement screens are increasingly used in sport and rehabilitation to evaluate movement competency. However, common screens are often evaluated using subjective visual detection of a priori prescribed discrete movement features (e.g., spine angle at maximum squat depth) and may not account for whole-body movement coordination, or associations between different discrete features.

Objective

To apply pattern recognition and machine learning techniques to identify whole-body movement pattern phenotypes during the performance of exemplar functional movement screening tasks; the deep squat and hurdle step. Additionally, we also aimed to compare how discrete kinematic measures, commonly used to score movement competency, differed between emergent groups identified via pattern recognition and machine learning.

Methods

Principal component analysis (PCA) was applied to 3-dimensional (3D) trajectory data from participant's deep squat (DS) and hurdle step performance, identifying emerging features that describe orthogonal modes of inter-trial variance in the data. A gaussian mixture model (GMM) was fit and used to cluster the principal component scores as an unsupervised machine learning approach to identify emergent movement phenotypes. Between group features were analyzed using a one-way ANOVA to determine if the objective classifications were significantly different from one another.

Results

Three clusters (i.e., phenotypes) emerged for the DS and right hurdle step (RHS) and 4 phenotypes emerged for the left hurdle step (LHS). Selected discrete points commonly used to score DS and hurdle step movements were different between emergent groups. In regard to the select discrete kinematic measures, 4 out of 5, 7 out of 7 and 4 out of 7, demonstrated a main effect (p < 0.05) between phenotypes for the DS, RHS, and LHS respectively.

Conclusion

Findings support that whole-body movement analysis, pattern recognition and machine learning techniques can objectively identify movement behavior phenotypes without the need to a priori prescribe movement features. However, we also highlight important considerations that can influence outcomes when using machine learning for this purpose.

Biomechanical and physiological responses to electrically assisted cycling during simulated mail delivery

This study quantified the biomechanical (movements and forces) and physiological (energy expenditure) demands of postal delivery performed with electrically assisted bicycles (EABs). Ten postal workers and 10 recreational athletes performed three simulated postal tasks (simulated mail delivery circuit, delivery distance [close vs. far], and 3-min stationary cycling) while carrying 0, 16 and 32 kg. Physiological (energy expenditure) and biomechanical (internal and external forces and joint angles) responses were calculated. Energy expenditure (10-20%; p < 0.05) and power output (30-44%; p < 0.05) increased with increasing mail loads. Ground reaction force increased (∼10%) for the far delivery distance, but joint reaction forces were unchanged. Lower hip flexion (p < 0.01), less hip abduction (p < 0.01) and larger spine anterior flexion (p < 0.01) were observed for the far delivery distance. Joint forces were not affected by the mail load transported (0-32 kg) or distance from the mailbox (close vs far). EABs can provide a suitable transportation method to assist mail delivery in terms of energy expenditure reduction.