The aim of this study was to develop suits for upper-body wearable robots that can satisfy the needs of industrial workers. Firstly, a preference survey was conducted to understand the workers’ preferences in terms of design and functions. Secondly, designs were developed and prototyped after performance tests of the materials used, including washing dimension-change rates and resilience for the stability of sensors and actuators. Thirdly, a satisfaction survey was conducted to evaluate the developed designs. The major results were as follows: (a) the most preferred function was assisting movements while lifting heavy objects or patients from the floor or at lower levels below the waist; (b) the preferred design features included waist-length shirts without collars, a style that can be worn outside, black or blue designs, wicking fabrics, and flexible materials; (c) four designs were developed and prototyped after confirming the fabric and clothing performance tests; (d) upon evaluating design and function satisfaction, more than 73% of participants were satisfied with the four designs, and 85% wanted to wear them. Design D was the most satisfactory in terms of material mapping details (featuring seams along muscular body lines and added three-dimensional (3D) patterns on the elbows). Design B was the most satisfactory regarding purchase and use/wearing. This was the design with tapered lines for raglan sleeves and horizontally cut lines on the shoulders. Participants expected Design C, with seams along muscular body lines and 3D patterns on the elbows, to easily suit patients and nurses. This research will be helpful when developing suits for upper-body movement-assistive wearable robots.

PurposeThis research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable robots that were frequently used by and exposed to people and (2) analyzing relationships among those key terms.Design/methodology/approachTextom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot.FindingsThe frequency-inverse document frequency, term frequency and central analyses were investigated, and the major key terms related to wearable robots and their connectivity were identified. After performing network analysis and convergence of iterated correlations analyses using UCINET and NetDraw programs, the major key term categories were identified.Originality/valueIt is important to understand how people think and perceive about wearable robots before developing wearable robots. The results of the research are expected to be helpful to better understand how people perceive and what key terms are mainly discussed by people in both countries and ultimately help when developing wearable robots with better market targeting approach methods.

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