Movement analysis in the early detection of newborns at risk for developing spasticity due to infantile cerebral palsy

Meinecke, Lars; Breitbach-Faller, N.; Bartz, Claudia; Damen, R.; Rau, G.; Disselhorst‐Klug, Catherine

doi:10.1016/j.humov.2005.09.012

Cited by 99 publications

(141 citation statements)

References 11 publications

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“…The healthy subjects of the control group were separated from 'at-risk' patients according to (Meinecke et al 2006). Pathology of the 'at-risk' patients was ensured through ultrasound-based detection of cerebral haemorrhage or periventricular leukomalacia.…”

Section: Participantsmentioning

confidence: 99%

“…Table 2 gives an overview of the number of infants and available movement trails for each instant of time. Table 1 The optimal combination of eight parameters with corresponding visual assessment (Meinecke et al 2006) # Parameter description Corresponding visual assessment according to Prechtl (1990), Prechtl (1997) and Prechtl (2001) …”

Section: Participantsmentioning

confidence: 99%

“…However, the video-based evaluation of GM does not allow the quantitative description of the movement and, with that, a monitoring of the developmental process is impossible. A Wrst step towards an objective and quantitative description of the spontaneous movements of newborns within the Wrst month of live was performed by Meinecke et al (2006). The measurement procedure, 3D motion analysis, used allows the spatial detection and quantiWcation of full body movements.…”

Section: Introductionmentioning

confidence: 99%

“…Besides the fact that the movement is recorded three-dimensionally as well as quantitatively, another major advantage of 3D motion analysis is its suitability for long-term control and, consequently, monitoring of a child's motor development. This is due to the fact that earlier recordings can be evaluated and compared with recordings made at a later time (Rau et al 2000;Meinecke et al 2006). Under these conditions, 3D motion analysis might be suitable for the evaluation of the development of spontaneous motor activity with age.…”

Section: Introductionmentioning

confidence: 99%

“…These parameters can be extracted from the recorded 3D movement analysis data and allow a satisfactory discrimination between normal and pathodological movement patterns of infants of an age below 1 month (Table 1) (Meinecke et al 2006). In discrimination between healthy subjects and babies with ICP by these parameters, a 73% overall detection rate with a sensitivity of 100% and a speciWcity of 70% have been achieved.…”

Section: Introductionmentioning

confidence: 99%

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Introduction of a method for quantitative evaluation of spontaneous motor activity development with age in infants

et al. 2012

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Coordination between perception and action is required to interact with the environment successfully. This is already trained by very young infants who perform spontaneous movements to learn how their body interacts with the environment. The strategies used by the infants for this purpose change with age. Therefore, very early progresses in action control made by the infants can be investigated by monitoring the development of spontaneous motor activity. In this paper, an objective method is introduced, which allows the quantitative evaluation of the development of spontaneous motor activity in newborns. The introduced methodology is based on the acquisition of spontaneous movement trajectories of the feet by 3D movement analysis and subsequent calculation of specific movement parameters from them. With these movement-based parameters, it was possible to provide an objective description of age-dependent developmental steps in healthy newborns younger than 6 months. Furthermore, it has been shown that pathologies like infantile cerebral palsy influence development of motor activity significantly. Since the introduced methodology is objective and quantitative, it is suitable to monitor how newborns train their cognitive processes, which will enable them to cope with their environment by motor interaction.

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Section: Participantsmentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Introduction of a method for quantitative evaluation of spontaneous motor activity development with age in infants

et al. 2012

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Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis

Hesse

Pujades

Romero³

et al. 2018

Lecture Notes in Computer Science

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Computer Vision for Medical Infant Motion Analysis: State of the Art and RGB-D Data Set

Hesse

Bodensteiner

Arens

et al. 2019

Lecture Notes in Computer Science

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Assessment of spontaneous movements of infants lets trained experts predict neurodevelopmental disorders like cerebral palsy at a very young age, allowing early intervention for affected infants. An automated motion analysis system requires to accurately capture body movements, ideally without markers or attached sensors to not affect the movements of infants. A vast majority of recent approaches for human pose estimation focuses on adults, leading to a degradation of accuracy if applied to infants. Hence, multiple systems for infant pose estimation have been developed. Due to the lack of publicly available benchmark data sets, a standardized evaluation, let alone a comparison of different approaches is impossible. We fill this gap by releasing the Moving INfants In RGB-D (MINI-RGBD) † data set, created using the recently introduced Skinned Multi-Infant Linear body model (SMIL). We map real infant movements to the SMIL model with realistic shapes and textures, and generate RGB and depth images with precise ground truth 2D and 3D joint positions. We evaluate our data set with state-of-the-art methods for 2D pose estimation in RGB images and for 3D pose estimation in depth images. Evaluation of 2D pose estimation results in a PCKh rate of 88.1% and 94.5% (depending on correctness threshold), and PCKh rates of 64.2%, respectively 90.4% for 3D pose estimation. We hope to foster research in medical infant motion analysis to get closer to an automated system for early detection of neurodevelopmental disorders.

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Movement analysis in the early detection of newborns at risk for developing spasticity due to infantile cerebral palsy

Cited by 99 publications

References 11 publications

Introduction of a method for quantitative evaluation of spontaneous motor activity development with age in infants

Introduction of a method for quantitative evaluation of spontaneous motor activity development with age in infants

Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis

Computer Vision for Medical Infant Motion Analysis: State of the Art and RGB-D Data Set

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