Thermal electronic textiles (e-textiles) are increasingly common in the market and aim to provide thermal comfort in cold environments. Currently, however, there is a paucity of information on the relative effectiveness of the different types of thermal e-textile. This study sets out to compare the effectiveness of a range of such textiles reported in the relevant literature. The study addresses the issue of heating effectiveness in terms of gender and particular body regions. Among the results reported, three primary categories emerged for investigation: (a) metabolic response, comprising metabolic rate and heart rate; (b) respiratory response i.e. mean skin temperature; and (c) perceptual response, including thermal sensation and comfort sensation. Eight eligible studies with a total of 83 subjects aged 23.4 ± 1.49 years, 40.96% male and 37.35% female and 21.69% in which gender was not reported, were investigated for the meta-analysis. Results show a significant improvement in changes in mean skin temperature and thermal sensation between the control and experimental groups via heating intervention ( p < 0.05), but results were not significant for changes in metabolic rate, heart rate, and comfort sensation ( p > 0.05). Regarding gender, thermal e-textiles significantly enhanced the changes in mean skin temperature in males and thermal sensation in both males and females ( p < 0.05). With regard to different body regions being heated, there were significant effects on changes in mean skin temperature, thermal sensation, and comfort sensation in heating the upper torso ( p < 0.05) and on changes in thermal sensation in heating the feet and toes ( p < 0.05). The results reported here may serve as reference points for the further development of smart heating textile technology.

In the field of human-computer interaction (HCI), recent years have witnessed an increasing interest in smart textiles with gesture recognition functions. This paper reports usability evaluations of a prototype gesture-controlled illuminative textile developed by the authors. This is an interactive woven POF textile system with computer vision-enabled mid-air gesture recognition.For the usability test, 25 participants (11 males and 14 females) aged between 19 and 56 (M = 30.85, SD = 10.8) were randomly recruited. The study was conducted by the means of the user experience questionnaire (UEQ) and the system usability scale (SUS). Results show that participants responded positively to our gesture-controlled illuminative textile in terms of its attractiveness, perspicuity and stimulation but were less positive about its efficiency. The results will be used to make targeted improvements to the existing product design.