Video-based quantification of human movement frequency using pose estimation: A pilot study

Assessment of repetitive movements (e.g., finger tapping) is a hallmark of motor examinations in several neurologic populations. These assessments are traditionally performed by a human rater via visual inspection; however, advances in computer vision offer potential for remote, quantitative assessment using simple video recordings. Here, we evaluated a pose estimation approach for measurement of human movement frequency from smartphone videos. Ten healthy young participants provided videos of themselves performing five repetitive movement tasks (finger tapping, hand open/close, hand pronation/supination, toe tapping, leg agility) at four target frequencies (1–4 Hz). We assessed the ability of a workflow that incorporated OpenPose (a freely available whole-body pose estimation algorithm) to estimate movement frequencies by comparing against manual frame-by-frame (i.e., ground-truth) measurements for all tasks and target frequencies using repeated measures ANOVA, Pearson’s correlations, and intraclass correlations. Our workflow produced largely accurate estimates of movement frequencies; only the hand open/close task showed a significant difference in the frequencies estimated by pose estimation and manual measurement (while statistically significant, these differences were small in magnitude). All other tasks and frequencies showed no significant differences between pose estimation and manual measurement. Pose estimation-based detections of individual events (e.g., finger taps, hand closures) showed strong correlations (all r>0.99) with manual detections for all tasks and frequencies. In summary, our pose estimation-based workflow accurately tracked repetitive movements in healthy adults across a range of tasks and movement frequencies. Future work will test this approach as a fast, quantitative, video-based approach to assessment of repetitive movements in clinical populations.

A Process-Oriented View of Procedural Memory Can Help Better Understand Tourette’s Syndrome

Tourette’s syndrome (TS) is a neurodevelopmental disorder characterized by repetitive movements and vocalizations, also known as tics. The phenomenology of tics and the underlying neurobiology of the disorder have suggested that the altered functioning of the procedural memory system might contribute to its etiology. However, contrary to the robust findings of impaired procedural memory in neurodevelopmental disorders of language, results from TS have been somewhat mixed. We review the previous studies in the field and note that they have reported normal, impaired, and even enhanced procedural performance. These mixed findings may be at least partially be explained by the diversity of the samples in both age and tic severity, the vast array of tasks used, the low sample sizes, and the possible confounding effects of other cognitive functions, such as executive functions, working memory or attention. However, we propose that another often overlooked factor could also contribute to the mixed findings, namely the multiprocess nature of the procedural system itself. We propose that a process-oriented view of procedural memory functions could serve as a theoretical framework to help integrate these varied findings. We discuss evidence suggesting heterogeneity in the neural regions and their functional contributions to procedural memory. Our process-oriented framework can help to deepen our understanding of the complex profile of procedural functioning in TS and atypical development in general.

Biomechanical analysis of the right elevated glenohumeral joint in violinists during legato-playing

BACKGROUND: Many statistics reveal that violin players suffer most often from musculoskeletal disorders compared to musicians of other instrument groups. A common phenomenon, especially observed in violin beginners, is the tendency to elevate the right shoulder during playing the violin. This can probably lead to serious disorders in long-term practice with repetitive movements. OBJECTIVE: For this reason, this study investigated the relationship between the right shoulder elevation and the force in the right glenohumeral joint during violin playing. It was hypothesized that the forces in the right glenohumeral joint are higher during playing with the right shoulder raised compared to playing in normal posture. METHODS: Motion capture data from four experienced violinists was recorded and processed by means of musculoskeletal simulation to get the force and elevation angle while playing with raised shoulder and in normal position. RESULTS: The results indicate that the absolute values of the resulting force, as well as the forces in the mediolateral, inferosuperior, and anteroposterior directions, are higher in playing the violin with the shoulder raised than in a normal posture. CONCLUSIONS: Elevating the right shoulder while playing the violin may pose a potential problem.

Classifier Module of Types of Movements Based on Signal Processing and Deep Learning Techniques

Human Activity Recognition (HAR) has been widely addressed by deep learning techniques. However, most prior research applied a general unique approach (signal processing and deep learning) to deal with different human activities including postures and gestures. These types of activity typically have highly diverse motion characteristics, which could be captured with wearable sensors placed on the user’s body. Repetitive movements such as running or cycling have repetitive patterns over time and generate harmonics in the frequency domain, while postures such as sitting or lying are characterized by a fixed position, with some positional changes and gestures or non-repetitive movements being based on an isolated movement usually performed by a limb. This work proposes a classifier module to perform an initial classification among these different types of movements, which would allow for applying afterwards the most appropriate approach in terms of signal processing and deep learning techniques for each type of movement. This classifier has been evaluated using the PAMAP2 and OPPORTUNITY datasets using a subject-wise cross-validation methodology. These datasets contain recordings from inertial sensors on hands, arms, chest, hip, and ankles, collected in a non-intrusive way. In the case of PAMAP2, the baseline approach for classifying the 12 activities using 5-s windows in the frequency domain obtained an accuracy of 85.26 ± 0.25%. However, an initial classifier module could distinguish between repetitive movements and postures using 5-s windows reaching higher performances. Afterward, specific window size, signal format, and deep learning architecture were used for each type of movement module, obtaining a final accuracy of 90.09 ± 0.35% (an absolute improvement of 4.83%).

De Re Metallica: An Early Ergonomics Lesson Applied to Machine Design in the Renaissance

The Renaissance treatise De Re Metallica (Georgius Agricola, 1556) is one of the first works that deals in detail with the state of the art of metal mining, compiling the main techniques and mechanical devices used in this industrial activity at that time. An advanced knowledge of the human–machine set is observed in this treatise, from a mechanical and ergonomics point of view. The main objective of this work is to carry out an ergonomics analysis of one of the mechanical devices collected in the sixth book of this treatise. It is intended to show that there was a certain concern for ergonomics in the Renaissance, long before the first appearance of this concept. Specifically, a mine water extraction pump, powered by three different systems, is analyzed. Current ergonomics assessment methods have been used to perform this comparative analysis. The postural load has been assessed by the rapid upper limb assessment (RULA) and the rapid entire body assessment (REBA). The Check List OCRA (occupational repetitive action) has been used to perform the analysis of repetitive movements. The results have shown an evolution of the machine, not only on a mechanical level, but also in movements, postures, and safety of the operator for the three methods applied. It is, therefore, an example of practical and real ergonomics applied to machine design dating from the 16th century. In addition, this work may be a very interesting tool for teaching, since it allows showing examples of ergonomics in productive areas related to historical context.

Misokinesia is a sensitivity to seeing others fidget that is prevalent in the general population

Misokinesia––or the ‘hatred of movements’––is a psychological phenomenon that is defined by a strong negative affective or emotional response to the sight of someone else’s small and repetitive movements, such as seeing someone fidget with a hand or foot. Among those who regularly experience misokinesia sensitivity, there is a growing grass-roots recognition of the challenges that it presents as evidenced by on-line support groups. Yet surprisingly, scientific research on the topic is lacking. This article is novel in systematically examining whether misokinesia sensitivity actually exists in the general population, and if so, whether there is individual variability in the intensity or extent of what sensitivities are reported. Across three studies that included 4100 participants, we confirmed the existence of misokinesia sensitivity in both student and non-student populations, with approximately one-third of our participants self-reporting some degree of sensitivity to seeing the repetitive, fidgeting behaviors of others as encountered in their daily lives. Moreover, individual variability in the range and intensity of sensitivities reported suggest that the negative social-affective impacts associated with misokinesia sensitivities may grow with age. Our findings thus confirm that a large segment of the general population may have a visual-social sensitivity that has received little formal recognition.

Exploring Stroke Rehabilitation in Malaysia: Are Robots Better than Humans for Stroke Recuperation?

Ranked as the second leading cause of death and the primary factor to adult disability worldwide, stroke has become a global epidemic problem and burden. As a developing country, Malaysia still faces challenges in providing ideal rehabilitation services to individuals with physical disabilities including stroke survivors. Conventional post-stroke care is often delivered in a team- based approach and involves several disciplines, such as physical therapy, occupational therapy, speech and language therapy, depending on the nature and severity of the deficits. Robots are potential tools for stroke rehabilitation as they can enhance existing conventional therapy by delivering a precise and consistent therapy of highly repetitive movements. In addition, robot- assisted therapy could facilitate the effectiveness of unsupervised rehabilitation and thus, may reduce the cost and duration of therapist-assisted rehabilitation. Research on robot-assisted physiotherapy for stroke in Malaysia is slowly coming into the limelight in the past two decades. This review explores the effectiveness of robot-assisted physiotherapy particularly in improving motor functions of stroke survivors in Malaysia.

On the study of the laws of fatigue with the rhythm of repetitive movements

Experimental data on the study of muscle fatigue by lifting a load on the Mosso ergograph, with the rhythmicity of repetitive movements, and the empirical formulas we derived suggest that:

Childhood-onset dystonia-causing KMT2B variants result in a distinctive genomic hypermethylation profile

Background Dystonia is a clinically and genetically heterogeneous movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements and/or postures. Heterozygous variants in lysine methyltransferase 2B (KMT2B), encoding a histone H3 methyltransferase, have been associated with a childhood-onset, progressive and complex form of dystonia (dystonia 28, DYT28). Since 2016, more than one hundred rare KMT2B variants have been reported, including frameshift, nonsense, splice site, missense and other in-frame changes, many having an uncertain clinical impact. Results We characterize the genome-wide peripheral blood DNA methylation profiles of a cohort of 18 patients with pathogenic and unclassified KMT2B variants. We resolve the “episignature” associated with KMT2B haploinsufficiency, proving that this approach is robust in diagnosing clinically unsolved cases, properly classifying them with respect to other partially overlapping dystonic phenotypes, other rare neurodevelopmental disorders and healthy controls. Notably, defective KMT2B function in DYT28 causes a non-random DNA hypermethylation across the genome, selectively involving promoters and other regulatory regions positively controlling gene expression. Conclusions We demonstrate a distinctive DNA hypermethylation pattern associated with DYT28, provide an epigenetic signature for this disorder enabling accurate diagnosis and reclassification of ambiguous genetic findings and suggest potential therapeutic approaches.