The Study Of Product Design And User Experience Based On Psychophysiological Data

In recent years,with the development of internet technologies,affective computing,artificial identification,wireless networks,microsensors,and physiological signal recording devices,the design of products or systems based on human physiological signals has moved from traditional scientific research to people’s daily lives,which has a broad market prospects.Currently,physiological signal sensors can be built into clothes,hats,shoes,gloves,beds,game pads,and other terminals for long-term user perception and feedback.For example,the affective computing team at the MIT Media Lab has many business applications,such as emotional teaching system,emotional ornaments,emotional toys,emotional glasses,emo-tional carpets,emotional CDs,and emotional mice.Products based on physiological signals can also monitor the user’s mental state(such as stress,etc.)in real time,so as to give users reasonable advice or feedback.It also can be used in online learning by monitoring students’emotional status,and gives teachers feedback.Moreover,police can monitor the emotional state of suspicious objects at the airport or customs,and then avoid terrorist attacks.It can be predicted that innovative product design based on physiological signals has important application value and practical significance.In addition,emotion is an indispensable factor in the process of interaction between people and products.To a certain extent,people’s demand for product emotions even exceeds the basic functions and ease of use of the products.In recent years,because physiological signals are directly controlled by the human autonomic nervous system and endocrine system,they are not subjectively influenced by users.So it can reflect the emotional state of people more objectively and truly,and even speculate that the users themselves are not aware of the recessive demand.Nowadays,more and more domestic and foreign researchers adopt physiological signal measurement methods to collect emotional reactions in the interaction process between users and products to improve the user experience.The core issue of product design and user experience evaluation based on physiological signals is to find a relationship model between the user’s emotions and physiological signal changes,ie,how to obtain emotion-related feature sets from the original physiological signals,and how to use these characteristics for data mining.Then we can establish a corresponding psycho-physiological model for product design or user experience assessment.This paper is based on the work of the Chinese Academy of Engineering Knowledge Ser-vice Center’s Innovation Design Knowledge Service System and the National Natural Science Foundation of China(No.61303137,61402141)to discover the emotional characteristics and combinations based on physiological signals,and establish a emotional calculation model for emotional design and user experience assessment.Based on the latest literatures in psy-chology,neuroscience,affective computing,design science,signal processing,and artificial intelligence,this article studies the following aspects:(1)This paper presents theoretical and methodological approaches for the identification of physiological signals in the academia and industry at home and abroad.In addition,it summarizes the emotional design theory model,emotion-related physiological signal charac-teristics,emotion inducing methods,feature extraction methods,and commonly used pattern recognition methods.It also laid a solid foundation for the subsequent use of statistical anal-ysis and machine learning methods for emotional recognition.(2)By comparing and analyzing existing product design theories,we propose an emo-tional product design and user experience assessment model based on physiological signals,which lays a foundation for future product design,user experience and services based on physiological signals.(3)According to the specific personalized music recommendation scenario,a relatively complete and objective music emotional database was established,and physiological signals such as GSR,pulse,respiration,skin temperature,and pupil diameter were collected.Fea-tures were extracted to obtain the physiological signal feature set,and the optimal feature set was established through feature selection and feature dimensionality reduction.Pattern recognition of multiple machine learning algorithms was performed.The music emotion perception model based on NuSVR algorithm is applied to the personalized music emo-tion recommendation system.This case study can be provided for researchers who design products or systems based on physiological signals.(4)According to the remote MOOC learning scenario,the emotional music clips are used as emotional stimuli.Multi-layer Perceptron,Kstar and SVM algorithms are used for the pupil response information of the subjects and the scores of the valence-arousal.An emotion-cognitive model of the SVM algorithm is proposed and an application based on this model was developed.It can improve the learning efficiency of the MOOCs.It can monitor the learner’s pupil diameter in real time and convert this feature into an emotional state feedback to the MOOC’s teachers and teachers can make adjustments or remind students based on the students’ emotional status,thus improving the barriers of inconvenience on the Internet.This case study can be provided for researchers who design products or systems based on physiological signals.(5)According to the user’s five interaction stages of the two tea products,subjective mea-surement methods and objective measurement methods were applied to analyze the people’s sensory and emotional experiences.It indicates that the product experience is dynamically changing and shows different changes of the importance of senses and emotions.In addi-tion,physiological signals such as GSR can be used as an objective evaluation index of the user’s emotional experience.This study not only theoretically understands the importance of sensory and emotional feedback in the product experience,but also has a reference value for measuring user experience using physiological signals.The product design and user experience evaluation model based on physiological data proposed in this paper will effectively solve the difficult issues of emotional information acquisition,expression and modeling,emotion analysis and product design.The closed-loop model allows designers to develop emotional products or systems by analyzing the characteristics of physiological signals,and allows researchers to measure the user experience of existing products or systems based on physiological signals.The research work in this paper has important guiding significance for the theoreti-cal perfection and technical development of signal processing,pattern recognition,human-computer interaction,multimedia technology,artificial intelligence,intelligent product de-sign,user experience and other fields.In addition,due to the emotional factors commonly existing in the field of creativity and design,this study can also be used as a reference for re-search on apparel design,music composition,animation design,display design,game design,and choreography.