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The Prechtl General Movements Assessment (GMA) has become a clinician and researcher tool-box for evaluating neurodevelopment in early infancy. Given it involves observation of infant movements from video recordings, utilising smartphone applications to obtain these recordings seems like the natural progression for the field. In this review, we look back on the development of apps for acquiring general movement videos, describe the application and research studies of available apps, and discuss future directions of mobile solutions and their usability in research and clinical practice. We emphasise the importance of understanding the background that has led to these developments while introducing new technologies, including the barriers and facilitators along the pathway. The GMApp and Baby Moves App were the first ones developed to increase accessibility of the GMA, with two further apps, NeuroMotion and InMotion, designed since. The Baby Moves app has been applied most frequently. For the mobile future of GMA, we advocate collaboration to boost the field's progression and to reduce research waste. We propose future collaborative solutions including standardisation of cross-sites data collection, adaption to local context and privacy laws, employment of user feedback, and sustainable IT structures enabling continuous software updating., Comment: 19 pages, 3 Figures, 2 Tables

Hintergrund: Einheitliche Empfehlungen zur stationären und ambulanten Physiotherapie bei Frühgeborenen fehlen in Deutschland. Ziel dieser Studie war die Untersuchung der Verordnungspraxis in deutschen Perinatalzentren. Werden standardisierte Assessments zur Indikationsstellung genutzt? Welchen Stellenwert nimmt die General Movements Analyse in der postnatalen Diagnostik ein? Methodik: Online-Befragung der deutschen Perinatalzentren mit 21 Fragen zur Indikationsstellung und Verordnungspraxis für stationäre und ambulante Physiotherapie in der Versorgung Frühgeborener sowie den Kenntnissen zur General Movements Analyse und deren klinische Anwendung via Lime-Survey. Ergebnisse: 81% der Teilnehmer empfehlen indikationsbasiert „immer“ oder „häufig“ stationäre, 53% ambulante Physiotherapie für Frühgeborene. Die Indikationsstellung erfolgt v.a. bei diesen Symptomen (N=344) und Diagnosen (N=273) (Mehrfachnennungen): Hypotonie (94%), Tonusregulationsstörung (92%), neurologische Auffälligkeiten (97%) und Hirnschädigungen (94%). Standardisierte Testungen nutzen 41% der Teilnehmer. Die General Movements Analyse ist 41% der Zentren bekannt, 11% setzen diese mehrmals in der Woche, 17% mehrmals im Monat zur Indikationsstellung für Physiotherapie ein. Schlussfolgerung: Physiotherapie wird bei Frühgeborenen häufig verordnet. Die Indikationsstellung erfolgt mehrheitlich nach Symptom- oder Krankheitsbild, weniger auf Grundlage von standardisierten Testverfahren. Die General Movements Analyse ist zwar eine weitreichend geläufige Methode, findet jedoch derzeit noch keine breite klinische Anwendung.

The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA). This study proposes a novel machine learning algorithm to detect an age-specific movement pattern, the fidgety movements (FMs), in a prospectively collected sample of typically developing infants. Participants were recorded using a passive, single camera RGB video stream. The dataset of 2800 five-second snippets was annotated by two well-trained and experienced GMA assessors, with excellent inter- and intra-rater reliabilities. Using OpenPose, the infant full pose was recovered from the video stream in the form of a 25-points skeleton. This skeleton was used as input vector for a shallow multilayer neural network (SMNN). An ablation study was performed to justify the network’s architecture and hyperparameters. We show for the first time that the SMNN is sufficient to discriminate fidgety from non-fidgety movements in a sample of age-specific typical movements with a classification accuracy of 88%. The computer-based solutions will complement original GMA to consistently perform accurate and efficient screening and diagnosis that may become universally accessible in daily clinical practice in the future.

Aiming at objective early detection of neuromotor disorders such as cerebral palsy, we proposed an innovative non-intrusive approach using a pressure sensing device to classify infant general movements (GMs). Here, we tested the feasibility of using pressure data to differentiate typical GM patterns of the ''fidgety period'' (i.e., fidgety movements) vs. the ''pre-fidgety period'' (i.e., writhing movements). Participants (N = 45) were sampled from a typically-developing infant cohort. Multi-modal sensor data, including pressure data from a 32x32-grid pressure sensing mat with 1024 sensors, were prospectively recorded for each infant in seven succeeding laboratory sessions in biweekly intervals from 4-16 weeks of post-term age. For proof-of-concept, 1776 pressure data snippets, each 5s long, from the two targeted age periods were taken for movement classification. Each snippet was pre-annotated based on corresponding synchronised video data by human assessors as either fidgety present (FM+) or absent (FM-). Multiple neural network architectures were tested to distinguish the FM+ vs. FM- classes, including support vector machines (SVM), feed-forward networks (FFNs), convolutional neural networks (CNNs), and long short-term memory (LSTM) networks. The CNN achieved the highest average classification accuracy (81.4%) for classes FM+ vs. FM-. Comparing the pros and cons of other methods aiming at automated GMA to the pressure sensing approach, we concluded that the pressure sensing approach has great potential for efficient large-scale motion data acquisition and sharing. This will in return enable improvement of the approach that may prove scalable for daily clinical application for evaluating infant neuromotor functions.

Video recording is a widely used method for documenting infant and child behaviours in research and clinical practice. Video data has rarely been shared due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-driven computer-based approaches are involved, such as screening tools to complement clinical assessments. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing the Prechtl's general movements assessment (GMA), an established and globally practised video-based diagnostic tool in early infancy for detecting neurological deficits, such as cerebral palsy. To date, no shared expert-annotated large data repositories for infant movement analyses exist. Such datasets would massively benefit training and recalibration of human assessors and the development of computer-based approaches. In the current study, sequences from a prospective longitudinal infant cohort with a total of 19451 available general movements video snippets were randomly selected for human clinical reasoning and computer-based analysis. We demonstrated for the first time that pseudonymisation by face-blurring video recordings is a viable approach. The video redaction did not affect classification accuracy for either human assessors or computer vision methods, suggesting an adequate and easy-to-apply solution for sharing movement video data. We call for further explorations into efficient and privacy rule-conforming approaches for deidentifying video data in scientific and clinical fields beyond movement assessments. These approaches shall enable sharing and merging stand-alone video datasets into large data pools to advance science and public health.

This article explores the clinical implications of the three different classes drawn from a Rasch analysis of the general movements optimality scores (GMOS) of 383 infants. Parametric analysis of the class membership examines four variables: age of assessment, brain injury presence, general movement patterns, and 2-year-old outcomes. GMOS separated infants with typical (class 3) from atypical development, and further separated cerebral palsy (class 2) from other neurodevelopmental disorders (class 1). Each class is unique regarding its quantitative and qualitative representations on the four variables. The GMOS has strong psychometric properties and provides a quantitative measure of early motor functions. The GMOS can be confidently used to assist with early diagnosis and predict distinct classes of developmental outcomes, grade motor behaviors, and provide a solid base to study individual general movement developmental trajectories.

Antibiotic contamination has become a serious environmental problem and much attention has been paid to its purification. The sulfate radical (SO4 −) based advanced oxidation processes (AOPs) exhibited significant potential in the treatment of antibiotics. In this study, the magnetic biochar (Fe2O3@LBC) derived from loofah was prepared to activate persulfate (PS) for cephalexin (CEX) degradation. Under the optimal conditions, 73.9% of CEX was removed in the Fe2O3@LBC/PS system. Free radicals quenching experiments and electron paramagnetic resonance (EPR) analysis revealed that HO and SO4 − were responsible for the degradation of CEX. The C-OH of the catalyst played a crucial role in the degradation process. In addition, the conversion between Fe3+ and Fe2+ enhanced the degradation of CEX by producing SO4 −. The degradation performance of other antibiotics and CEX in different water matrices indicated the broad adaptability and applications of Fe2O3@LBC. The main intermediates and the possible transformation pathways were proposed. These results provided a potential insight into biochar based catalysts for the degradation of antibiotics by activation of persulfate.

4-Nitrophenol (4-NP) has a significant toxic effect on human health and environment, so it is urgent to find out an effective method to treat the pollutant. In this work, a green catalyst resin-stabilized copper nanocomposites were synthesized to study the catalytic reduction performance of 4-NP. The 13% Cu-D001 resin (D001 resin stabilized 13% of copper nanocomposites) showed high catalytic activity in the reduction of 4-NP to 4-aminophenol (4-AP). The pseudo-first-order kinetic constant reached 0.0132 min−1. The activation energy for the reduction of 13% Cu-D001 resin was 12.48 kJ/mol, which was lower than that of silver nanoshell-coated resin (24.08 kJ/mol). The high catalytic property of 13% Cu-D001 resin strongly depended on the oxidation state of copper nanocomposites supported on the resin. The catalyst also showed high reusability and the catalytic conversion rate still reached 80% in the sixth cycle. In this study, a promising catalyst was introduced for the practical reduction of 4-NP in wastewater.

PURPOSES: Typically, early (pre-diagnostic) development in individuals later diagnosed with Rett syndrome (RTT) has been investigated retrospectively using parent reports, medical records and analysis of home videos. In recent years, prospective research designs have been increasingly applied to the investigation of early development in individuals with late phenotypical onset disorders, for example, autism spectrum disorder.METHODS: In this study, data collected by the Danish National Birth Cohort lent itself to prospective exploration of the early development of RTT, in particular early motor-, speech-language, and socio-communicative behaviors, mood, and sleep.RESULTS AND CONCLUSIONS: Despite limitations, this quasi prospective methodology proved promising. In order to add substantially to the body of knowledge, however, specific questions relating to peculiarites in early development could usefully be added to future cohort studies. As this involves considerable work, it may be more realistic to consider a set of indicators which point to a number of developmental disorders rather than to one.

Purpose of reviewSubstantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood.Recent findingsThis early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention. We believe that only a comprehensive interdisciplinary approach will enable us to detect and delineate specific parameters for specific neurodevelopmental disorders at a very early age to improve early detection/diagnosis, enable prospective studies and eventually facilitate randomised trials of early intervention. In this article, we propose a dynamic framework for characterising neurofunctional biomarkers associated with specific disorders in the development of infants and children. We have named this automated detection 'Fingerprint Model', suggesting one possible approach to accurately and early identify neurodevelopmental disorders.

The chemical composition, the content and the leachability of heavy metals in municipal solid waste incineration (MSWI) fly ash were tested and analyzed. It is shown that the leachability of Pb and Cr exceeds the leaching toxicity standard, and so the MSWI fly ash is considered as hazardous waste and must be solidified. The effect of solidifying the MSWI fly ash by cement was studied, and it is indicated that the heavy metals can be well immobilized if the mass fraction of the fly ash is appropriate. The heavy metals were immobilized within cement hydration products through either physical fixation substitution, deposition or adsorption mechanisms.

The objective of this study is to assess the feasibility of solidification/stabilization on MSWI fly ash using Na3PO4 combined with coal fly ash agent. Coal fly ash agent (CF, coal fly ash mixed with 30 wt% cement clinker) was added to MSWI fly ash at 25% and 35% dry weight, portions. Then, Na3PO4 was added to the mix in amounts of 0, 0.5%, 0.75%, 1.0% and 1.25% dry weight, respectively. Compressive strength tests and toxicity characteristic leaching procedure (TCLP) results show that using Na3PO4 combined with coal fly ash agent, the solidified MSWI fly ash sample can meet the landfill standard after 28 days of curing. Therefore, this method provides a possibility to achieve a cheap and effective solution for MSWI fly ash treatment before land filling.