Characteristics Analysis And Function Abnormality Evaluation Of Children Crawling Motion

Crawling is an inherent ability of infants and young children,and it is also an important index for evaluating their growth and development.Crawling dyskinesia can be used as an important symptom in the clinical diagnosis of children with cerebral palsy.The study on crawling can promote people's understanding of inter-limb coordination pattern and neuromuscular control mechanism.On the other hand,the research of crawling can provide theoretical basis for clinical diagnosis and rehabilitation training for children with neuromuscular diseases such as cerebral palsy.Although some progress has been made in the study of crawling,most of the studies were conducted on healthy adults and children.Meanwhile,the analysis methods were relatively simple and the cognition of abnormal crawling function was insufficient.There is a lack of objective and quantitative analysis and assessment methods for abnormal crawling function of children with cerebral palsy.In view of the deficiencies in the study of crawling movement,the purpose of this paper is to use inertial sensors and surface electromyography(sEMG)detection technology to explore the kinematic characteristics and sEMG characteristics that can effectively describe the crawling movement,so as to achieve a quantitative assessment of thecrawling function of children with cerebral palsy.The main work and research results can be summarized as follows:(1)Crawling data acquisition scheme based on pressure,9-axis inertial sensors and surface EMG sensors was proposed,and the hands-knees crawling data acquisition experiments were conducted on 17 healthy children and 22 children with cerebral palsy.(2)Acceleration signal power,zero-crossing rate(ZCR),sample entropy(SampEN),Lempel-Ziv complexity(LZC),harmonic ratio(HR),and rotation angle of the waist were used to describe the strength,complexity,and stability of limbs and trunk movement during crawling.The power,root mean square(RMS),mean absolute value(MAV),co-activation index(CI),ZCR,SampEN,LZC,mean power frequency(MPF),and median frequency(MF)of the extracted sEMG signals respectively were calculated to describe the muscle activation level,antagonistic muscle pairco-activation level,complexity of sEMG,muscle fatigue,and pre-regulation of muscle activity.(3)Taking the healthy children as research objects,the descriptive abilities of the extracted kinematic features and sEMG features for crawling movement wereinvestigated.It was found that the acceleration signal power can describe the movement intensity of upper limb,but can't describe the lower limb's movement intensity;compared to the ZCR and LZC,the SampEN can better describe the movement complexity of upper and lower limbs;HR can't describe the limbs' stability consistently;The extracted kinematic features showed no consistent performance in the ML and VT orientations of the lower limb acceleration.As for the sEMG features,it was found that both RMS and MAV were good for describing the level of muscle activation;CI can describe the level of co-activation of antagonistic muscle pairs;compared to ZCR and LZC,SampEN can better describe the complexity of sEMG signals;both MPF and MF can characterize the muscle fatigue during crawling;the changes of RMS or MAV value in the biceps brachii,triceps brachii,and trunk latissimus dorsi had a good ability to characterize the pre-regulation of muscle activity.(4)Taking the healthy children as reference,a deviation index that measured the deviation degree of CP children characteristic value from the TD group was given to assess the abnormality of crawling function in children with cerebral palsy effectively.Using the PCA algorithm to reduce the dimension of feature vectors,a method based on eigenvector distance ratio was proposed to quantitatively evaluate the abnormality ofcrawling function in children with cerebral palsy.