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Digital twin, a new emerging and fast-growing technology which is one of the most promising technologies for smart design and manufacturing, has attracted much attention worldwide recently. With the application of digital twin, product performance evaluation has entered the data-driven era. However, traditional methods for evaluation mainly place emphasis on structure analysis in the stage of manufacturing and service in digital twin. They cannot synthesize multi-source information and take the high-level emotional response into consideration in the design stage. To overcome these disadvantages, a digital twin-driven method is proposed evaluating product design schemes in this study. It enables the acquisition of electroencephalogram (EEG) data, physical data, and emotional feedback. Human factors are systematically considered in the evaluation process to establish the information association …