Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions

The emerging paradigm of "fusion of lifeforms" represents a transformative shift from conventional human-machine interfaces toward deeply integrated symbiotic systems, where biological and artificial components co-adapt structurally, energetically, informationally, and cognitively. This review systematically classifies multi-level perception systems within fusion of lifeforms into four functional categories: sensory and functional restoration, beyond-natural sensing, endogenous state sensing, and cognitive enhancement. We survey recent advances in neuroprosthetics, sensory augmentation, closed-loop physiological monitoring, and brain-computer interfaces, highlighting the transition from substitution to fusion. Despite significant progress, critical challenges remain, including multi-source heterogeneous integration, bandwidth and latency limitations, power and thermal constraints, biocompatibility, and system-level safety. We propose future directions such as layered in-body communication networks, sustainable energy strategies, advanced biointerfaces, and robust safety frameworks. Ethical considerations regarding self-identity, neural privacy, and legal responsibility are also discussed. This work aims to provide a comprehensive reference and roadmap for the development of next-generation fusion of lifeforms, ultimately steering human-machine integration from episodic functional repair toward sustained, multi-level symbiosis between biological and artificial systems.

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Publication Details

Journal
Sensors
Published
2026-01-15
DOI
https://doi.org/10.3390/s26020576
Primary Topic
Neuroscience and Neural Engineering
Type
article
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article

Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions

Y. P. Liu, Jingjing Xu, Bingao Zhang, Xinyan You et al.
Sensors
Neuroscience and Neural Engineering
article

Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions

Y. P. Liu, Jingjing Xu, Bingao Zhang, Xinyan You, Shengyong Xu
article en

Abstract

The emerging paradigm of "fusion of lifeforms" represents a transformative shift from conventional human-machine interfaces toward deeply integrated symbiotic systems, where biological and artificial components co-adapt structurally, energetically, informationally, and cognitively. This review systematically classifies multi-level perception systems within fusion of lifeforms into four functional categories: sensory and functional restoration, beyond-natural sensing, endogenous state sensing, and cognitive enhancement. We survey recent advances in neuroprosthetics, sensory augmentation, closed-loop physiological monitoring, and brain-computer interfaces, highlighting the transition from substitution to fusion. Despite significant progress, critical challenges remain, including multi-source heterogeneous integration, bandwidth and latency limitations, power and thermal constraints, biocompatibility, and system-level safety. We propose future directions such as layered in-body communication networks, sustainable energy strategies, advanced biointerfaces, and robust safety frameworks. Ethical considerations regarding self-identity, neural privacy, and legal responsibility are also discussed. This work aims to provide a comprehensive reference and roadmap for the development of next-generation fusion of lifeforms, ultimately steering human-machine integration from episodic functional repair toward sustained, multi-level symbiosis between biological and artificial systems.

SensorsVol. 26(2)
Shandong University (CN), Peking University (CN), Beihang University (CN)
Responsible consumption and production
Openalex Percentile: Top 88%
Neuroscience and Neural Engineering
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Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions — Y. P. Liu, Jingjing Xu, et al. · Sensors (2026) | TGRS Research Map | TGRS