Echoes of Empathy: A Symbiotic IoT-Based Emotion Feedback Framework for Psychological Interventions via Large Language Model

Large AI models, connected to terminal devices via high-speed mobile communication networks, enable task collaboration and resource sharing, forming an intelligent framework for the Symbiotic Internet of Things (SIoT) paradigm in industry applications. Despite large language models hold significant potential for psychological intervention, their emotional interaction capabilities remain limited. This paper introduces a SIoT framework for psychological intervention and proposes an emotion-enhanced human-machine interaction architecture incorporating behavioral information captured by IoT devices. The system leverages ubiquitous sensing devices such as cameras and microphones, along with technologies like speech recognition and generation, as well as hyper-realistic digital humans, to create a natural interaction interface. Additionally, we introduce the end-of-utterance detection method and the behavior pattern control algorithm to facilitate smoother and more goal-oriented conversations. The proposed methods and prototype system have been validated through subjective and objective experiments, with results demonstrating their feasibility and suggesting that this approach could become one of the primary forms of humanmachine interaction for psychological intervention in the future.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-06-02
DOI
https://doi.org/10.1109/jiot.2025.3575085
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
6.35

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article

Echoes of Empathy: A Symbiotic IoT-Based Emotion Feedback Framework for Psychological Interventions via Large Language Model

Zhaolong Ning, Hao Shen, Chengsheng Mao, Minqiang Yang et al.
3 citations
IEEE Internet of Things Journal
Mental Health Research Topics
6.35
article

Echoes of Empathy: A Symbiotic IoT-Based Emotion Feedback Framework for Psychological Interventions via Large Language Model

Zhaolong Ning, Hao Shen, Chengsheng Mao, Minqiang Yang, Bin Hu, Changsheng Ma, Zhichao Yang
article en
3 citations

Abstract

Large AI models, connected to terminal devices via high-speed mobile communication networks, enable task collaboration and resource sharing, forming an intelligent framework for the Symbiotic Internet of Things (SIoT) paradigm in industry applications. Despite large language models hold significant potential for psychological intervention, their emotional interaction capabilities remain limited. This paper introduces a SIoT framework for psychological intervention and proposes an emotion-enhanced human-machine interaction architecture incorporating behavioral information captured by IoT devices. The system leverages ubiquitous sensing devices such as cameras and microphones, along with technologies like speech recognition and generation, as well as hyper-realistic digital humans, to create a natural interaction interface. Additionally, we introduce the end-of-utterance detection method and the behavior pattern control algorithm to facilitate smoother and more goal-oriented conversations. The proposed methods and prototype system have been validated through subjective and objective experiments, with results demonstrating their feasibility and suggesting that this approach could become one of the primary forms of humanmachine interaction for psychological intervention in the future.

IEEE Internet of Things JournalVol. 12(20)
Chongqing University of Posts and Telecommunications (CN), Northwestern University (US), Lanzhou University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 4%
Mental Health Research Topics
6.35
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