Papers
2
Total Citations
16
H-Index
2
About
Zeqiang Zhu is a researcher at the intersection of assistive robotics, smart home technologies, and rehabilitation engineering. Their work focuses on developing intelligent systems that enhance quality of life for aging populations and stroke survivors. Zhu’s most cited paper, “CBASH: A CareBot-Assisted Smart Home System Architecture to Support Aging-in-Place” (2023, 9 citations), proposes an integrated framework combining IoT-enabled smart homes with homecare robots to overcome limitations in event perception and timely response—a critical step toward truly autonomous aging-in-place solutions. In a second highly cited study, “Vision-based Automatic Detection of Compensatory Postures of after-Stroke Patients During Upper-extremity Robot-assisted Rehabilitation” (2020, 7 citations), Zhu pioneered a machine learning approach using kinematic data to automatically detect maladaptive compensatory movements during robot-assisted therapy. This work offers a scalable, non-invasive method to improve rehabilitation outcomes by providing real-time feedback. Together, these contributions demonstrate Zhu’s commitment to bridging robotics, computer vision, and human-centered design, with direct applications in healthcare and independent living. Their research is increasingly recognized for its potential to transform home-based care and neurorehabilitation.
Research Focus
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Top Papers
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