Movement analysis by accelerometry of newborns and infants for the early detection of movement disorders due to infantile cerebral palsy

So far, developed diagnostic strategies for the early detection of movement disorders due to infantile cerebral palsy (ICP) in newborns are not easily applicable in clinical settings. They are either difficult to acquire or they are too expensive to be established in pediatric clinics and are not sufficiently usable to be integrated into daily routine. The aim of this study therefore was to develop a methodology that allows the objective diagnosis of developing movement disorders in newborns due to ICP. It should be applicable to pediatric offices and should easily integrate in daily routine. To achieve this, a simple to use and low-cost system based on accelerometers was developed to evaluate the newborn’s movement. Afterward, a classificator based on a decision tree algorithm was implemented to differentiate between healthy and pathological data in order to propose the most likely diagnosis. The developed methodology was validated in a clinical study with 19 healthy and 4 affected subjects that were evaluated at the first, third and fifths month after birth (corrected age). The overall detection rate of the developed methodology reached between 88 and 92% for all evaluated measurements. The developed methodology is simple to use, therefore is applicable for the objective diagnosis of developing movement disorders in newborns due to ICP and can be established in pediatric offices for use in daily routine.

[1]  Friedrich Foerster,et al.  Detection of posture and motion by accelerometry : a validation study in ambulatory monitoring , 1999 .

[2]  Øyvind Stavdahl,et al.  ENIGMA - Enhanced interactive general movement assessment , 2008, Expert Syst. Appl..

[3]  Pierre Geurts,et al.  Contributions to decision tree induction: bias/variance tradeoff and time series classification , 2002 .

[4]  K. Joseph,et al.  Increasing Prevalence of Cerebral Palsy Among Very Preterm Infants: A Population-Based Study , 2006, Pediatrics.

[5]  Henk J. Stam,et al.  Validity of accelerometry in assessing the duration of the sit-to-stand movement , 2008, Medical & Biological Engineering & Computing.

[6]  Stan C A M Gielen,et al.  Ambulatory motor assessment in Parkinson's disease , 2006, Movement disorders : official journal of the Movement Disorder Society.

[7]  H. Prechtl,et al.  General movement assessment as a method of developmental neurology: new paradigms and their consequences. The 1999 Ronnie MacKeith lecture. , 2001 .

[8]  David G. Stork,et al.  Pattern Classification , 1973 .

[9]  Mijna Hadders-Algra,et al.  A systematic review of the effects of early intervention on motor development. , 2005, Developmental medicine and child neurology.

[10]  S. Lennon,et al.  The modified Rivermead Mobility Index: validity and reliability , 2000, Disability and rehabilitation.

[11]  Peter H Veltink,et al.  Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. , 2002, Journal of biomechanics.

[12]  Satoru Morita,et al.  Time Series Analysis of Spontaneous Upper-Extremity Movements of Premature Infants With Brain Injuries , 2008, Physical Therapy.

[13]  Omar Bouhaddou,et al.  Knowledge Engineering in Health Informatics , 1997, Computers and Medicine.

[14]  Karl M Newell,et al.  The dynamics of resting and postural tremor in Parkinson's disease , 2000, Clinical Neurophysiology.

[15]  H. K. Ramakrishnan,et al.  Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait , 1989, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[16]  G M Lyons,et al.  Accelerometers in rehabilitation medicine for older adults. , 2005, Age and ageing.

[17]  Klaas Postema,et al.  General movements in early infancy predict neuromotor development at 9 to 12 years of age , 2005, Developmental medicine and child neurology.

[18]  F. B. Palmer.  Strategies for the early diagnosis of cerebral palsy. , 2004, The Journal of pediatrics.

[19]  A. Prochazka,et al.  Quantification of the UPDRS rigidity scale , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  J. Bussmann,et al.  Ambulatory accelerometry to quantify motor behaviour in patients after failed back surgery: a validation study , 1998, Pain.

[21]  U. Thyen,et al.  Predictive Value of Neurodevelopmental Assessment versus Evaluation of General Movements for Motor Outcome in Preterm Infants with Birth Weights <1500 g , 2007, Neuropediatrics.

[22]  B. Dobkin,et al.  Reliability and Validity of Bilateral Thigh and Foot Accelerometry Measures of Walking in Healthy and Hemiparetic Subjects , 2006, Neurorehabilitation and neural repair.

[23]  Wouter Olthuis,et al.  Procedure for in-use calibration of triaxial accelerometers , 1997 .

[24]  B. G. Celler,et al.  Classification of basic daily movements using a triaxial accelerometer , 2004, Medical and Biological Engineering and Computing.

[25]  Pier Luca Lanzi,et al.  Fast feature selection with genetic algorithms: a filter approach , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[26]  Steven Morrison,et al.  Reliability of segmental accelerations measured using a new wireless gait analysis system. , 2006, Journal of biomechanics.

[27]  Lars Adde,et al.  General movement assessment: predicting cerebral palsy in clinical practise. , 2007, Early human development.

[28]  Jihoon Yang,et al.  Feature Subset Selection Using a Genetic Algorithm , 1998, IEEE Intell. Syst..

[29]  W. Grundfest,et al.  ACCELEROMETERS FOR QUANTIFICATION OF GAIT AND MOVEMENT DISORDERS: A PERSPECTIVE REVIEW , 2008 .

[30]  K. Aminian,et al.  Physical activity monitoring based on accelerometry: validation and comparison with video observation , 1999, Medical & Biological Engineering & Computing.

[31]  Gérard Bréart,et al.  Cerebral Palsy Among Very Preterm Children in Relation to Gestational Age and Neonatal Ultrasound Abnormalities: The EPIPAGE Cohort Study , 2006, Pediatrics.

[32]  W. T. Federer,et al.  Stochastic Approximation and NonLinear Regression , 2003 .

[33]  Marco Thiel,et al.  Hierarchical organization of a reference system in newborn spontaneous movements. , 2007, Infant behavior & development.

[34]  K R Westerterp,et al.  Physical activity pattern of children assessed by triaxial accelerometry , 2004, European Journal of Clinical Nutrition.

[35]  B M Nigg,et al.  A method for inverse dynamic analysis using accelerometry. , 1996, Journal of biomechanics.

[36]  Roozbeh Jafari,et al.  QUANTIFIED DEEP TENDON REFLEX DEVICE, SECOND GENERATION , 2008 .

[37]  Christa Einspieler,et al.  Prechtl's assessment of general movements: a diagnostic tool for the functional assessment of the young nervous system. , 2005, Mental retardation and developmental disabilities research reviews.

[38]  J. Perry,et al.  Gait Analysis , 2024 .

[39]  G Rau,et al.  Movement analysis in the early detection of newborns at risk for developing spasticity due to infantile cerebral palsy. , 2006, Human movement science.

[40]  Vasiliki Kosmidou,et al.  Using sample entropy for automated sign language recognition on sEMG and accelerometer data , 2010, Medical & Biological Engineering & Computing.

[41]  Jun Yang,et al.  A simple approach to integration of acceleration data for dynamic soil–structure interaction analysis , 2006 .

[42]  R. Fitzpatrick,et al.  Age-related differences in walking stability. , 2003, Age and ageing.

[43]  L. B. Dahl,et al.  A randomized controlled trial of an early intervention program in low birth weight children: outcome at 2 years. , 2008, Early human development.

[44]  Hailong Zhu,et al.  Support vector machine for classification of walking conditions using miniature kinematic sensors , 2008, Medical & Biological Engineering & Computing.

[45]  S. Simon.  Gait Analysis, Normal and Pathological Function. , 1993 .

[46]  J. Kooloos,et al.  Reliability of videotaped observational gait analysis in patients with orthopedic impairments , 2005, BMC musculoskeletal disorders.

[47]  Jorunn L Helbostad,et al.  Estimation of gait cycle characteristics by trunk accelerometry. , 2004, Journal of biomechanics.