Wearable Sensor Networks for Early Detection of Developmental Disorders in Infants

Diagnosing and providing patient-specific care for Neuromotor Developmental Disorders (NDD) at the earliest after birth increases the positive effect of rehabilitative interventions. Many qualitative, observational, questionnaire-based evaluatory tests carried out worldwide are mostly screening tests for at-risk infants but cannot assess their degree of disability. Thus, using wearable sensor networks and monitoring multiple kinematic motor parameters, we can identify patterns of NDD before the onset of symptoms, aiding their growth to improve their lives. Wireless Sensor modules of Inertial Measurement Units (IMU) (for spatiotemporal parameters), Flex sensors (for flexion-extensions, grasping, and gripping parameters), Photo- Plethysmograph (PPG) (for heart rate variability) and Force Sensitive Resistor (for pressure and force parameters during gait) are used to constantly measure specific parameters of movements such as reaching, grasping, crawling, and walking of infants. The movement data of adults showed a Root Mean Square Error (RMSE) with less than a deviation of 2° from marker-based optical trackers. Implementation and tests of the developed network need to be improved to be fitted on infants. Doctors can provide patient-centric rehabilitative aid in infants' early stages of Neuromotor disorders by employing the affordable and easily deployable wearable sensor network. The network was proved to be better than conventional methods of using expensive technologies like Optical Motion Capture (Mo-Cap) cameras.