Garment suggestion based on comfort extracted from physiological and emotional parameters

The purpose of the study was to find the true comfort of the wearer by conceptualizing, formulating, and proving the relation between physiological and emotional parameters with clothing fit and fabric. A mixed-method research design was used, and the findings showed that physiological indicators such as heart rate are closely linked with user comfort. However, a significant change in emotional response indicated a definite relationship between different fabric and fit types. The research was conducted to discover the relation between true comfort parameters and clothing, which is unique to the field. The findings help us understand how fabric types and clothing fit types can affect physiological and emotional responses, providing the consumer with satisfactory clothing with the suitable properties needed.

Temperature Detection from Images Using Smartphones

Since late 2019, the global spread of COVID-19 has affected people's daily life. Temperature is an early and common symptom of Covid. Therefore, a convenient and remote temperature detection method is needed. In this paper, a non-contact method for detecting body temperature is proposed. Our developed algorithm based on blackbody radiation calculates the body temperature of a user-selected area from an obtained image. The findings were confirmed using a FLIR Thermal Camera with an accuracy of 97%.