Fatigue predictive model for mid-air gesture interaction / Md Ibnul Adib - Md Ibnul , Adib (2021)
Gesture interaction in HCI has been one of the most important evaluation. For mid-air gesture interaction, the user moves their hand in different directions to imitate signals that the machine can understand. These hand gestures were borrowed from different sign languages. Studies performed on sign language interpreters show that most of the sign language interpreters face different kinds of fatigue or mild to serious kind of physical disorder which is an alarming phenomenon for the computer science industry. The objective of the present research is to identify the existing hand gesture signals in HCI application areas and find the fatigue criteria for these hand gesture signals. Based on the fatigue criteria a Fatigue Predictive Model has been proposed, based on a preliminary study done using the Cogulator tool. Then a prototype which can analyze fatigue in mid-air gesture interaction was designed, developed, and evaluated. A quantitative study of the prototype was conducted with 60 participants. From 29 mid-air hand gesture signals participants felt discomfort and muscle tension in 7 hand gesture interactions. These 7 gestures are separated into two categories based on their gesture design pattern. These gestures were unique in design, involved extensive muscle usage and had to repeat the gestures to avoid false tracking. This study proposes a predictive model to find out the gestures which have higher possibilities to cause fatigue among users based on the data found from fatigue criteria which will help HCI industry or manufacturers to choose the gestures according to the convenience to the users who will be conducting the gestures.