OS-ELM Based Emotion Recognition for Empathetic Elderly Companion

Yang, Zixiaofan; Wu, Qiong; Leung, Cyril; Chen, Miao

doi:10.1007/978-3-319-14066-7_32

Cited by 5 publications

(4 citation statements)

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“…This reality is believed to increase both the economic and social pressure, as there is a rise in public health expenditure ( Chen and Schulz, 2016 ; Fang and Chang, 2016 ; Segercrantz and Forss, 2019 ), a permanent need for improved healthcare assistance and assistive living, and a scarce of providers ( Hofmann, 2013 ; Bassi et al, 2021 ). Low income and high workload generate a shortage of caregivers ( Yang et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

“…Technology is undoubtedly perceived as being the solution for improving healthcare. Scholars that develop chatbots talk about the need of designing empathetic virtual companions to alleviate isolation and loneliness ( Da Paixão Pinto et al, 2021 ) and to fulfill the emotional needs of the aging adults and to increase likeability and trustworthiness towards machines ( Yang et al, 2015 ). As the main motivation to use chatbot is productivity, together with entertainment and socialization, chatbots should be equally built as a tool, a toy, and a friend ( Brandtzaeg and Følstad, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

“…Although AI developments in assistive technology are advanced, there is still work to be done for achieving a proper chatbot for end aging users ( De Arriba-Pérez et al, 2021 ). Thus, the existing studies refer to presenting, designing, and testing prototypes of conversational agents with meaningful, empathetic emotional, and friendship capabilities ( Yang et al, 2015 ; Bassi et al, 2021 ), with personalized entertainment content access ( De Arriba-Pérez et al, 2021 ), with workplace environment facilities ( Bächle et al, 2018 ), with capabilities to promote healthy habits through a coaching model ( Justo et al, 2021 ), with public administration abilities ( Miliani et al, 2021 ), with virtual caregiving attributions ( Su et al, 2017 ; Ryu et al, 2020 ; Valtolina and Hu, 2021 ; Miura et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Interacting with chatbots later in life: A technology acceptance perspective in COVID-19 pandemic situation

Iancu

2023

Front. Psychol.

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IntroductionWithin the technological development path, chatbots are considered an important tool for economic and social entities to become more efficient and to develop customer-centric experiences that mimic human behavior. Although artificial intelligence is increasingly used, there is a lack of empirical studies that aim to understand consumers’ experience with chatbots. Moreover, in a context characterized by constant population aging and an increased life-expectancy, the way aging adults perceive technology becomes of great interest. However, based on the digital divide (unequal access to technology, knowledge, and resources), and since young adults (aged between 18 and 34 years old) are considered to have greater affinity for technology, most of the research is dedicated to their perception. The present paper investigates the way chatbots are perceived by middle-aged and aging adults in Romania.MethodsAn online opinion survey has been conducted. The age-range of the subjects is 40–78 years old, a convenience sampling technique being used (N = 235). The timeframe of the study is May–June 2021. Thus, the COVID-19 pandemic is the core context of the research. A covariance-based structural equation modelling (CB-SEM) has been used to test the theoretical assumptions as it is a procedure used for complex conceptual models and theory testing.ResultsThe results show that while perceived ease of use is explained by the effort, the competence, and the perceive external control in interacting with chatbots, perceived usefulness is supported by the perceived ease of use and subjective norms. Furthermore, individuals are likely to further use chatbots (behavioral intention) if they consider this interaction useful and if the others’ opinion is in favor of using it. Gender and age seem to have no effect on behavioral intention. As studies on chatbots and aging adults are few and are mainly investigating reactions in the healthcare domain, this research is one of the first attempts to better understand the way chatbots in a not domain-specific context are perceived later in life. Likewise, judging from a business perspective, the results can help economic and social organizations to improve and adapt AI-based interaction for the aging customers.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interacting with chatbots later in life: A technology acceptance perspective in COVID-19 pandemic situation

Iancu

2023

Front. Psychol.

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“…Farid et al proposed an ensemble classification algorithm based on instances weighting mechanism [13], in order to detect outliers, the algorithm combines with the clustering algorithm, if a data point does not belong to any existed cluster in the system, the class of the data will be thought as a new concept, and then the algorithm counts the data information in leaf nodes to further confirm the result. Liang et al proposed an online sequential learning algorithm called OS-ELM [14][15][16][17], OS-ELM is a development of the extreme learning machine (ELM) algorithm [18][19][20][21][22]; when a new data block coming, OS-ELM uses new data to incrementally update the structures of the single hidden feedforward neural networks; by the mean of the online sequential learning mechanism, OS-ELM can effectively deal with concept drift in data stream environment.…”

Section: Introductionmentioning

confidence: 99%

An Ensemble Classification Algorithm Based on Information Entropy for Data Streams

Wang

Duan

et al. 2019

Neural Process Lett

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Data stream mining problem has caused widely concerns in the area of machine learning and data mining. In some recent studies, ensemble classification has been widely used in concept drift detection, however, most of them regard classification accuracy as a criterion for judging whether concept drift happening or not. Information entropy is an important and effective method for measuring uncertainty. Based on the information entropy theory, a new algorithm using information entropy to evaluate a classification result is developed. It uses ensemble classification techniques, and the weight of each classifier is decided through the entropy of the result produced by an ensemble classifiers system. When the concept in data streams changing, the classifiers' weight below a threshold value will be abandoned to adapt to a new concept in one time. In the experimental analysis section, six databases and four proposed algorithms are executed. The results show that the proposed method can not only handle concept drift effectively, but also have a better classification accuracy and time performance than the contrastive algorithms.

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