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A review of next-generation sensor technologies for human-machine interaction

Xiangyu Guo, Tai Fei*, Zican Wang, Xiao Xu, Subhas Mukhopadhyay, Amit Bhardwaj, Zhi Jin*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Advances in sensor technologies have substantially reshaped human-machine interaction (HMI), enabling more intuitive, robust, and efficient interactions across diverse application domains, including healthcare, robotics, and industrial automation. This review systematically covers next-generation sensing approaches essential to future HMI systems, addressing radar-based sensing, vision-based techniques, haptic feedback and teleoperation, as well as wearable sensors and wireless sensor networks (WSNs). Radar sensors are discussed for their reliability in challenging conditions and suitability for gesture and vital-sign monitoring. Vision-based sensors, incorporating monocular, stereo, near infrared (NIR), and thermal imaging, provide detailed spatial and semantic information vital for gesture tracking and remote physiological monitoring. Moreover, haptic sensors and AI-driven teleoperation techniques are examined for their pivotal roles in enabling safe, precise remote interactions in medical and industrial contexts. This article further explores the Internet-of-Things (IoT)-enabled wearable sensors and WSNs, highlighting their application in continuous health monitoring and personalized healthcare. Sensor fusion strategies are discussed, emphasizing their potential to integrate complementary data streams effectively. Cross-cutting challenges, such as computational efficiency, sensor integration, ethical considerations, and sustainability, are identified and analyzed. By consolidating recent progress and discussing practical implementation issues, this review offers insights into current research trends and outlines key directions for future advancements in sensor-driven HMI systems.

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Original languageEnglish
Pages (from-to)14252-14269
Number of pages18
JournalIEEE Sensors Journal
Volume26
Issue number10
Early online date30 Dec 2025
DOIs
Publication statusPublished - 15 May 2026

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