Literature DB >> 18707688

Quantification of the segmental kinematics of spontaneous infant movements.

Dominik Karch1, Keun-Sun Kim, Katarzyna Wochner, Joachim Pietz, Hartmut Dickhaus, Heike Philippi.   

Abstract

This article introduces a method to capture the movements of the upper and the lower limb of infants using an electromagnetic tracking system and to reliably calculate the segmental kinematics. Analysis of the spontaneous movements of infants is important e.g. in the context of the "General Movement Analysis", which aims at the early diagnosis of motor dysfunctions. Due to special constraints regarding infant anatomy, previous approaches based on optical tracking could only gather position data of the infant' segments, whereas with this method in addition relative segment angles can be calculated. The spontaneous movements of the infant and simple calibration movements of the hand and the foot are used to calculate the joint centers and the joint axes of a multi-segmental chain model. The quality of the calibration movements is assessed at calibration time by calculating the root mean square deviation from the total least squares regression plane. The general accuracy of the recording is evaluated by the difference between recorded and estimated sensor positions and the difference between recorded and estimated sensor orientations. Movements of 20 infants between term and 3 months post term age were recorded and processed. A first application illustrates how abnormal movement patterns are manifested in the segmental kinematics. The results show that the presented method is a practicable and reliable way to record spontaneous infant movements and to calculate the segmental kinematics.

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Year:  2008        PMID: 18707688     DOI: 10.1016/j.jbiomech.2008.06.033

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  10 in total

1.  Correlation properties of spontaneous motor activity in healthy infants: a new computer-assisted method to evaluate neurological maturation.

Authors:  Sandra Waldmeier; Sebastian Grunt; Edgar Delgado-Eckert; Philipp Latzin; Maja Steinlin; Katharina Fuhrer; Urs Frey
Journal:  Exp Brain Res       Date:  2013-05-28       Impact factor: 1.972

2.  Novel AI driven approach to classify infant motor functions.

Authors:  Simon Reich; Dajie Zhang; Tomas Kulvicius; Sven Bölte; Karin Nielsen-Saines; Florian B Pokorny; Robert Peharz; Luise Poustka; Florentin Wörgötter; Christa Einspieler; Peter B Marschik
Journal:  Sci Rep       Date:  2021-05-10       Impact factor: 4.379

Review 3.  Movement recognition technology as a method of assessing spontaneous general movements in high risk infants.

Authors:  Claire Marcroft; Aftab Khan; Nicholas D Embleton; Michael Trenell; Thomas Plötz
Journal:  Front Neurol       Date:  2015-01-09       Impact factor: 4.003

4.  Developmental Trajectories of Hand Movements in Typical Infants and Those at Risk of Developmental Disorders: An Observational Study of Kinematics during the First Year of Life.

Authors:  Lisa Ouss; Marie-Thérèse Le Normand; Kevin Bailly; Marluce Leitgel Gille; Christelle Gosme; Roberta Simas; Julia Wenke; Xavier Jeudon; Stéphanie Thepot; Telma Da Silva; Xavier Clady; Edith Thoueille; Mohammad Afshar; Bernard Golse; Mariana Guergova-Kuras
Journal:  Front Psychol       Date:  2018-02-19

5.  3D Motion Capture May Detect Spatiotemporal Changes in Pre-Reaching Upper Extremity Movements with and without a Real-Time Constraint Condition in Infants with Perinatal Stroke and Cerebral Palsy: A Longitudinal Case Series.

Authors:  Julia Mazzarella; Mike McNally; Daniel Richie; Ajit M W Chaudhari; John A Buford; Xueliang Pan; Jill C Heathcock
Journal:  Sensors (Basel)       Date:  2020-12-19       Impact factor: 3.576

6.  Early Moves: a protocol for a population-based prospective cohort study to establish general movements as an early biomarker of cognitive impairment in infants.

Authors:  Catherine Elliott; Caroline Alexander; Alison Salt; Alicia J Spittle; Roslyn N Boyd; Nadia Badawi; Catherine Morgan; Desiree Silva; Elizabeth Geelhoed; Robert S Ware; Alishum Ali; Anne McKenzie; David Bloom; Mary Sharp; Roslyn Ward; Samudragupta Bora; Susan Prescott; Susan Woolfenden; Vuong Le; Sue-Anne Davidson; Ashleigh Thornton; Amy Finlay-Jones; Lynn Jensen; Natasha Amery; Jane Valentine
Journal:  BMJ Open       Date:  2021-04-09       Impact factor: 2.692

7.  Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study.

Authors:  Kamini Raghuram; Silvia Orlandi; Paige Church; Maureen Luther; Alex Kiss; Vibhuti Shah
Journal:  Children (Basel)       Date:  2022-06-07

8.  Infant trunk posture and arm movement assessment using pressure mattress, inertial and magnetic measurement units (IMUs).

Authors:  Andraž Rihar; Matjaž Mihelj; Jure Pašič; Janko Kolar; Marko Munih
Journal:  J Neuroeng Rehabil       Date:  2014-09-06       Impact factor: 4.262

9.  Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.

Authors:  Iwona Doroniewicz; Daniel J Ledwoń; Alicja Affanasowicz; Katarzyna Kieszczyńska; Dominika Latos; Małgorzata Matyja; Andrzej W Mitas; Andrzej Myśliwiec
Journal:  Sensors (Basel)       Date:  2020-10-22       Impact factor: 3.576

Review 10.  AI Approaches Towards Prechtl's Assessment of General Movements: A Systematic Literature Review.

Authors:  Muhammad Tausif Irshad; Muhammad Adeel Nisar; Philip Gouverneur; Marion Rapp; Marcin Grzegorzek
Journal:  Sensors (Basel)       Date:  2020-09-17       Impact factor: 3.576

  10 in total

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