Home // International Journal On Advances in Life Sciences, volume 14, numbers 1 and 2, 2022 // View article
Authors:
Rama Krishna Thelagathoti
Hesham H. Ali
Keywords: mobility; childhood developmental disorder; wearable sensor.
Abstract:
As estimated by the World Health Organization (WHO), 5% of the world’s children population are diagnosed with an early developmental disability such as autism and cerebral palsy. State-of-the-art clinical diagnostic procedures are predominantly dependent on observational assessment by a trained physician. Physicians assess the severity of the disability by observing the child as well as by considering the feedback from the parents. However, as the final decision is completely dependent on the observer the procedure becomes subjective and does not provide an accurate decision. Moreover, such approaches are time-intensive and require enormous human effort. Hence, it is essential to explore the alternative opportunities that provide an accurate assessment. Recent studies show that abnormal motor skills are often the initial signs of later developmental disorders. This paves the way for exploring alternative opportunities to identify the disease in the early stages of childhood. Although different methods for collecting neonate motor data have been explored in the past, improvements in sensing technologies facilitate convenient as well as unobtrusive methods to collect the mobility data even from the infants and be able to detect the abnormality in the motor movements. Since wearable devices are tiny and easy to use in collecting motor data from neonates, it is feasible to distinguish abnormal motor development from normal motor development. Thus, mobility data collection from an infant using a wearable sensor is beneficial in the early diagnosis of developmental disabilities like cerebral palsy. Our main contribution to this study is to present the analysis of various wearable sensor-based motor assessment methods in predicting childhood disorders. This article first presents some of the existing clinical diagnostic procedures and then elaborates on mobility-based quantitative assessment methods. Furthermore, this document presents various crucial mobility parameters associated with identifying childhood disorders.
Pages: 42 to 52
Copyright: Copyright (c) to authors, 2022. Used with permission.
Publication date: June 30, 2022
Published in: journal
ISSN: 1942-2660