Guidelines for Open Research Data in Movement Sciences

A wearable sensory system for human lower extremity motion analysis is proposed, and an intelligent computation method for this sensory system is presented. The standard method for human motion analysis is the optical motion analysis using high-speed cameras to record human 3D motion, but this method is only limited in the laboratory research, because it requires expensive devices, large space and time-exhausted calibration experiments. In this study, two low-cost human motion analysis systems are constructed, deferent from the conventional 3D motion analysis system based on high-speed camera. These wearable systems incorporate gyroscopes (ENC-05EB) to measure angular velocities of body segments, and two-axis accelerometers (ADXL202) are used to measure the accelerations for the purpose of leg (foot, shank and thigh) motion analysis in every human motion cycle. The first wearable sensor system is designed for only foot motion analysis and the second system can be used for a leg (foot, shank and thigh) motion analysis. Then based on the two sensor systems, a fuzzy inference system (FIS) is developed for the calculation of the gait phases fed by sensors outputs. A digital filter is also designed to eliminate noises from of the output of the fuzzy inference system, which enhances robustness of the system. Finally, experimental study is conducted to validate the wearable sensor systems using an optical motion analysis system (Hi-DCam)

BackgroundCalls have been made for increased access to individual participant data (IPD) from clinical trials, to ensure that complete evidence is available. However, despite the obvious benefits, progress towards this is frustratingly slow. In the meantime, many systematic reviews have already collected IPD from clinical trials. We propose that a central repository for these IPD should be established to ensure that these datasets are safeguarded and made available for use by others, building on the strengths and advantages of the collaborative groups that have been brought together in developing the datasets.ObjectiveEvaluate the level of support, and identify major issues, for establishing a central repository of IPD.DesignOn-line survey with email reminders.Participants71 reviewers affiliated with the Cochrane Collaboration's IPD Meta-analysis Methods Group were invited to participate.Results30 (42%) invitees responded: 28 (93%) had been involved in an IPD review and 24 (80%) had been involved in a randomised trial. 25 (83%) agreed that a central repository was a good idea and 25 (83%) agreed that they would provide their IPD for central storage. Several benefits of a central repository were noted: safeguarding and standardisation of data, increased efficiency of IPD meta-analyses, knowledge advancement, and facilitating future clinical, and methodological research. The main concerns were gaining permission from trial data owners, uncertainty about the purpose of the repository, potential resource implications, and increased workload for IPD reviewers. Restricted access requiring approval, data security, anonymisation of data, and oversight committees were highlighted as issues under governance of the repository.ConclusionThere is support in this community of IPD reviewers, many of whom are also involved in clinical trials, for storing IPD in a central repository. Results from this survey are informing further work on developing a repository of IPD which is currently underway by our group.

Today, one can observe shifts in the research landscape, which is formed by digitization and open science principles. The open science movement continues to gain momentum, attention and debate. In parallel with the principle of unity, open science gives rise to a taxonomy of several related ideas, guidelines and concepts, such as open access, open replicable research and open data. Over the past fifteen years, research institutions have focused on open access to publications. However, recently the focus of attention has shifted to research data as a “new currency” in research activities and their distribution in open access, and the guiding principles of data management are becoming crucial for the wide implementation of open science practices and the effective use of data in research, industry, business and other sectors of the economy. In this context, it is relevant to carry out a thorough study of primary scientific works on open science issues and to study the role of the concept of “open research data” in the paradigm of a holistic ecosystem of open science and business ecosystem. In this work, it is proposed to use the methods of quantitative and qualitative bibliometric analysis, which allows to identify the main trends and form the basis for further research. The information base for this work was the international scientometric database Scopus, which enables to analyze bibliographic data using built-in tools and import them for external use in the VOSviewer software. The study revealed an increasing trend in the number of publications on the subject under study, with the highest annual growth rate in 2017 (76%) and 2019 (66%). Qualitative bibliographic analysis made it possible to analyze the most cited and, therefore, trending works on the selected topic. In terms of the number of citations per year, the results show that the studies with such directions in open science as open program code (open source); data/research reproducibility, research data management; open access to publications (open access) are most popular. In addition, a cluster analysis of the co-prevalence of keywords was conducted. It formed clusters dedicated to both institutional and infrastructural problems of the development of open science and research data. Separately, the results of the analysis create a scientific basis for further research into the key determinants of the effectiveness of the implementation of a proper research data management system at the micro, meso, and macro levels. It will improve the effectiveness of the implementation of scientific developments from one field of knowledge to another, while achieving increased interdisciplinary research. In parallel with this, interested persons of the real sector of the economy get the opportunity to analyze scientific results, determining the possibility of their adoption in their own activities.

Today, one can observe shifts in the research landscape, which is formed by digitization and open science principles. The open science movement continues to gain momentum, attention and debate. In parallel with the principle of unity, open science gives rise to a taxonomy of several related ideas, guidelines and concepts, such as open access, open replicable research and open data. Over the past fifteen years, research institutions have focused on open access to publications. However, recently the focus of attention has shifted to research data as a “new currency” in research activities and their distribution in open access, and the guiding principles of data management are becoming crucial for the wide implementation of open science practices and the effective use of data in research, industry, business and other sectors of the economy. In this context, it is relevant to carry out a thorough study of primary scientific works on open science issues and to study the role of the concept of “open research data” in the paradigm of a holistic ecosystem of open science and business ecosystem. In this work, it is proposed to use the methods of quantitative and qualitative bibliometric analysis, which allows to identify the main trends and form the basis for further research. The information base for this work was the international scientometric database Scopus, which enables to analyze bibliographic data using built-in tools and import them for external use in the VOSviewer software. The study revealed an increasing trend in the number of publications on the subject under study, with the highest annual growth rate in 2017 (76%) and 2019 (66%). Qualitative bibliographic analysis made it possible to analyze the most cited and, therefore, trending works on the selected topic. In terms of the number of citations per year, the results show that the studies with such directions in open science as open program code (open source); data/research reproducibility, research data management; open access to publications (open access) are most popular. In addition, a cluster analysis of the co-prevalence of keywords was conducted. It formed clusters dedicated to both institutional and infrastructural problems of the development of open science and research data. Separately, the results of the analysis create a scientific basis for further research into the key determinants of the effectiveness of the implementation of a proper research data management system at the micro, meso, and macro levels. It will improve the effectiveness of the implementation of scientific developments from one field of knowledge to another, while achieving increased interdisciplinary research. In parallel with this, interested persons of the real sector of the economy get the opportunity to analyze scientific results, determining the possibility of their adoption in their own activities.

Globally, open science movement is gaining momentum ever since the launching of the preprint repository Arxiv.org in 1991 and the signing of the global declaration Budapest Open Access Initiative in 2002. Free online scholarships have been getting support from the research funding agencies while they are committed to disseminating public-funded research studies to the common citizens. Following extensive global consultation, UNESCO submitted a draft Recommendation on Open Science to its 193 Member States in September 2020. The Global South is taking an interest in the global open science movement. Notably, the BRICS nations are leading the developing nations in producing open-access scholarship. In India, many universities and research institutions have established their respective open knowledge and research data repositories. At the same time, scholarly periodicals published by many of the public institutions have also been made accessible online freely. In the open science ecosystem, open research data is also an essential element. Globally, FAIR Data Principles have been adopted by the scientific community to make research data Findable, Accessible, Interoperable, and Reusable (FAIR). The FAIR Data Principles were published in 2016, while the term was coined in 2014. The present chapter discusses the salient features of FAIR Data Principles. The chapter also highlights the issues and challenges in India's open research data ecosystem as a member of the developing nations in the Global South. The chapter also highlights the availability of open research data in India vis-a-vis in the Global South, highlighting a few success stories.

Open research data in human movement analysis: Swiss-initiated-guidelines for broader scientific communities

Microsoft Kinect is one of the inventions used in various applications including human motion capture. In this paper, the processes involved for human motion capture and analysis using Microsoft Kinect is demonstrated through a review. This review includes the data acquisition protocol, data collection and data analysis based on the computer vision field. This paper is focused on rehabilitation and biomechanics application through human motion analysis.

Human body motion analysis is an important technology which modem bio-mechanics combines with computer vision and has been widely used in intelligent control, human computer interaction, motion analysis, and virtual reality and other fields. In which the moving human body detection is the most important part of the human body motion analysis, the purpose is to detect the moving human body with its behavior from the background image in video sequences, and for the follow- up treatment such as the target classification, the human body tracking and behavior understanding, its effective detection plays a very important role. Index Terms: Human motion detection, object detection, Classification, Subtraction method, Tread tracking system.

Generating human-like soccer primitives from human data

Vision-based motion detection, analysis and recognition of epileptic seizures—A systematic review

The paper presents a theoretical analysis of human reaching movements in manipulation of flexible objects. To predict the trajectory of human hand, a minimum crackle criterion has been recently proposed in literature. A different approach is explored in this paper. To explain the trajectory formation, we propose a dynamic version of the minimum hand jerk criterion. It is shown that this criterion matches experimental data available in literature. In addition, an analysis of this novel criterion shows the possibility of multiphase velocity profiles of the hand. Also, contrary to the minimum crackle criterion, our criterion produces bounded hand velocity profiles for multi-mass flexible objects. The results obtained in this paper can be used in devising new experimental protocols for the analysis of skillful human movements in virtual environments.

Analysis of human motion is extremely important in order to obtain fundamental data for training in the field of rehabilitation. At Nagoya University we are analysing human motion by use of a micro­ computer to elucidate functional characteristics of the locomotion system. After the introduction of micro-computers. it has become possible to accumulate and integrate more data and process them more quickly and conveniently. Data obtained from the weight balance analyzer. large force plate and three­ dimensional goniometer devised by the authors are subjected to on-line processing through an AI D convertor. I. The weight-balance analY/er for the evaluation of dynamic balance ability can be used both in standing and sitting positions. A computer block-break game is integrated into the program so that training can be performed enjoyably. 2. A large serial force plate is used to detect the floor reaction force of individual legs. Three force components in the directions of X. Y and Z are transformed to resultant force. velocity. acceleration and paths of center of pressure through mathematic processing. 3. The three­ dimensinal goniometer describes angular changes of the hip or knee joint in the three planes during walking. In addition to flexion-cxtension. adduction-abduction and internal-external rotation can be grasped easily by this device.

To compare the effectiveness and safety of oral misoprostol vs vaginal dinoprostone for the induction of labor (IOL) using an individual participant data (IPD) meta-analysis. We used a Cochrane review and searched Ovid MEDLINE, Ovid Embase, Ovid Emcare, CINAHL Plus, Scopus and ClinicalTrials.gov to identify randomized controlled trials (RCTs) that compared oral misoprostol with vaginal dinoprostone for IOL in viable singleton pregnancies. We invited the authors of eligible trials to share their anonymized data. Primary outcomes were vaginal delivery, a composite measure of adverse maternal outcomes and a composite measure of adverse perinatal outcomes. IPD meta-analysis was conducted using a two-stage random-effects model. An intention-to-treat approach was used for all analyses. Aggregate-data meta-analysis was undertaken with RCTs stratified by Trustworthiness in RAndomised Clinical Trials (TRACT) score. Of 18 eligible RCTs, eight provided IPD, of which five (1892 participants) met the TRACT criteria for trustworthiness. IPD meta-analysis showed similar rates of vaginal delivery after IOL with oral misoprostol or vaginal dinoprostone (odds ratio (OR), 0.99 (95% CI, 0.80-1.22); I2 = 0%). The rates of composite adverse perinatal outcome (adjusted odds ratio (aOR), 1.02 (95% CI, 0.61-1.72); I2 = 0%) and composite adverse maternal outcome (aOR, 1.39 (95% CI, 0.72-2.69); I2 = 0%) were also comparable between the groups. Of 10 RCTs that did not share IPD, seven met the TRACT criteria. Aggregate-data meta-analysis of the 12 RCTs (five with IPD and seven without IPD) meeting the trustworthiness criteria also showed comparable rates of vaginal delivery after oral misoprostol and after vaginal dinoprostone (OR, 1.08 (95% CI, 0.92-1.27)). In contrast, six studies not meeting the trustworthiness criteria (three with and three without IPD) reported a higher rate of vaginal delivery following oral misoprostol (OR, 1.34 (95% CI, 1.22-1.48)), resulting in an inflated overall estimate of the vaginal delivery rate after oral misoprostol based on all data (OR, 1.19 (95% CI, 1.05-1.36)). IOL with oral misoprostol or vaginal dinoprostone results in comparable rates of vaginal delivery and composite perinatal and maternal adverse outcomes. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

This chapter stands at the forefront of an innovative intersection between artificial intelligence (AI) and human kinetics, focusing on the transformative realm of skeleton-based movement recognition. At its core, this chapter investigates the sophisticated technologies and methodologies that are pivotal in accurately identifying and analyzing human movements through the lens of skeletal data. This exploration is not just a mere analysis of motion but a deep dive into the intricate dance between the mechanical precision of AI and the fluid complexity of human movement. The chapter meticulously dissects how AI algorithms can interpret skeletal data to recognize and predict human actions, illuminating our physical expressions' nuances. It delves into the myriad of applications this synergy can unlock, from enhancing athletic performance to revolutionizing healthcare and rehabilitation practices. Additionally, the study critically examines the challenges ahead, such as ensuring accuracy in diverse scenarios and addressing ethical concerns related to privacy and data security. By encapsulating the current achievements and envisioning the future landscape, this study contributes significantly to the academic discourse. It paves the way for groundbreaking developments in understanding and augmenting human movement through the power of AI. This interdisciplinary approach promises to redefine our interaction with technology, blurring the lines between the digital and physical realms and unlocking new possibilities in human motion analysis and beyond.

Human motion analysis is a field of increasing interest. In most applications, an accurate estimation of joint angles is needed. Inertial measurement units (IMUs) represent a very promising technology for motion capture. Unfortunately, their performances are strongly influenced by different sources of error (e.g., gyroscopes biases). To limit the effect of these sources of error, several algorithms (usually defined as “sensor fusion” algorithms) are used. The proposed work aims to validate a magnetic-free quaternion-based robust unscented Kalman filter (UKF) for upper limb kinematic analysis (i.e., estimation of the articular joint angles), using an inertial body sensor network, in a set of complex 3-D movements (i.e., the yoga poses). The algorithm was tested on ten expert yoga practitioners during the execution of the sun salutation sequence. Joint angle estimations were compared with the ones obtained from an optoelectronic reference system by evaluating the root mean square errors (RMSEs) and Pearson’s correlation coefficients. The achieved worst case was 8.41°, while the best one was 2.96° for RMSEs mean values. The accuracy of the algorithm was further confirmed by the high values of Pearson’s correlation coefficients (lowest mean value of 0.80). In addition, the comparison with one of the most used filters for attitude estimation [extended Kalman filter (EKF)] showed no significant differences between the two methods. Up to authors knowledge, the scientific literature lacks the development of a complete magnetic-free version of the UKF for human motion capture and analysis in complex movements, such as the one introduced here. The proposed work aims at filling this gap.