Designing comfortable smart clothing: for infants’ health monitoring

Abstract

The integration of multiple domains is encouraged in order to respond to the need for societal wellbeing. For example, smart clothing is expected to be beneficial for health monitoring. However, there still exists the challenge of designing casual smart clothing that can both accurately measure health parameters and ensure a high level of wearing comfort, especially for infants. This study meets the challenge of designing smart clothing that applies knowledge of infant clothing design, sensor technology, and machine learning in an experiment. The aim is to solve the problems associated with the use of sensors for real-time body temperature monitoring. The use skintight sensors is more accurate but uncomfortable. Skin-loose sensors, on the other hand, enhance comfort but limit the accuracy of the temperature readings. The results show that a combination of multiple skin-loose sensors can be used to overcome the trade-off between sensor accuracy and wearing comfort in smart clothing for health monitoring.