Abstract
Movement analysis of infants’ body parts is momentous for the early detection of various movement disorders such as cerebral palsy. Most existing techniques are either marker-based or use wearable sensors to analyze the movement disorders. Such techniques work well for adults, however they are not effective for infants as wearing such sensors or markers may cause discomfort to them, affecting their natural movements. This paper presents a method to help the clinicians for the early detection of movement disorders in infants. The proposed method is marker-less and does not use any wearable sensors which makes it ideal for the analysis of body parts movement in infants. The algorithm is based on the deformable part-based model to detect the body parts and track them in the subsequent frames of the video to encode the motion information. The proposed algorithm learns a model using a set of part filters and spatial relations between the body parts. In particular, it forms a mixture of part-filters for each body part to determine its orientation which is used to detect the parts and analyze their movements by tracking them in the temporal direction. The model is represented using a tree-structured graph and the learning process is carried out using the structured support vector machine. The proposed framework will assist the clinicians and the general practitioners in the early detection of infantile movement disorders. The performance evaluation of the proposed method is carried out on a large dataset and the results compared with the existing techniques demonstrate its effectiveness.
Highlights
Normal human movements, such as, moving an arm, look simple but require a complex coordination of control between the brain and the musculoskeletal system
This examination is known as the general movement assessment (GMA) [2,7]
We selected 10 patients of ages 2 weeks to 6 months with both genders, having movement disorders and currently they are being treated by the therapists
Summary
Normal human movements, such as, moving an arm, look simple but require a complex coordination of control between the brain and the musculoskeletal system. Any disruption in the coordination system may result in inhabit unwanted movements, trouble in making the intended movements or both [1]. These may appear due to abnormal development of the brain, injury in the brain of a child during the pregnancy or at birth, or genetic disorders. To diagnose the movement disorders, the spontaneous movements of an infant are observed by the doctors or the physiotherapists along with the family medical history. This examination is known as the general movement assessment (GMA) [2,7]. It is time consuming procedure to manually analyze every infant, an automatic system is needed to accurately analyze the movements in various body parts of infant
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