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Human-as-a-Sensor: Toward Autonomous Multimodal Sensing for Self-Determined Technology Engagement
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DOI：10.1109/MPRV.2026.3667609.png)
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Abstract
En 中文
Recent advancements in brain-computer interfaces (BCIs), e.g., Neuralink, have enabled seamless interaction and control across various applications, from assistive technologies to virtual environments. Traditional BCI applications treat users as control units that issue commands to interact with systems. In this work, we propose the novel concept of Human-as-a-Sensor (HaaS), where users function as seamless intelligent multimodal sensors and BCIs extract contextual sensing data from brain signals as they engage naturally with their environment. By tapping directly into neural activity and relaying information through neuronal feedback, HaaS reduces reliance on handheld sensors/screens, with fusion-first perception and feedback. We explore various HaaS-enabled opportunities for sensing applications and demonstrate how HaaS fosters self-determined technology engagement by supporting opt-in local monitoring and management. Moreover, we discuss critical challenges in realizing HaaS, including accuracy, real-world deployment, and privacy issues. Finally, we present a proof-of-concept evaluation that demonstrates the promise of HaaS for enabling natural interaction with sensing systems.
Keywords:
Sensors
Navigation
Intelligent sensors
Stress
Multimodal sensors
Electrodes
Data mining
Cognitive load
Smart phones
Regulation
Journal
I
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1.8
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26
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1.7K
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