Wearable 3.0: From Smart Clothing to Wearable Affective Robot

With the rapid development of science and technology and the accelerating pace of life, people's mental health problems have become increasingly prominent. Besides, traditional wearable technologies and affective computing technologies (i.e., Wearable 2.0 based on smart clothing) have been unable to meet the requirements brought by computation-intensive affective analysis and latency-sensitive affective interaction. Therefore, in this article, Wearable 3.0, which integrates brain wearable devices, intelligent affective interaction robots, and intelligent tactile devices, is proposed. Wearable 3.0 can provide users with more personalized mental health monitoring services by collecting EEG data, speech emotion data, and tactile behavioral perception data. Also, the advantages of Wearable 3.0 and performance comparison with Wearable 2.0 are given in this article. Two typical application cases of Wearable 3.0, namely, wearable affective robot and CreativeBioMan, are introduced. Moreover, the detailed architecture design and realization of Wearable 3.0 are also given, which show that our proposed user mental healthcare system based on Wearable 3.0 has deeper cognitive intelligence and provides more flexible affective interaction.

Introduction

With the arrival of the information era and the rapid development of technology, the pace of life continues to accelerate, as well as the growing pressure of survival. People's psychological sub-health and pathosis have become a general trend, including depression, anxiety, insomnia, and so on. People often suffer from these diseases at an earlier age, which leads to a series of social health and safety problems. According to the statistics from 2016 released by the World Health Organization, there are about 450 million people suffering from mental illness in the world, among whom more than 350 million suffer from depression; about 21 million people suffer from schizophrenia; and in China, more than 100 million people suffer from mental illness [1]. Among all mental diseases, depression is the main cause of suicide, and also brings significant economic losses to both individuals and society [2]. In addition, emotion has become the main indicator of mental health problems, especially for empty nesters, autistic children, recovered patients, as well as drivers. However, due to insufficient numbers of psychologists in China, it is hard to meet the needs of people with mental illness. Thus, how to take care of the emotions of people effectively with the help of highly developed artificial intelligence, robots, and wearable technology [3]–[5] is becoming more and more important. Currently, typical wearable equipment for user mental healthcare and treatment face the following challenges: •

Shallow value: Due to the diverse sources of user data and limited data quantity, the existing systems have failed to mine deeper value.

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Single-modal data: The existing systems analyze only a certain type of data, so the potential of user physiological data and social emotion data cannot be found.

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Static affective interaction: The current emotion monitoring systems take user mobility and comfort as a price. At the same time, they lack a real-time and effective communication mechanism between terminals, which makes real-time diagnosis and treatment impossible.