Papers
12
Total Citations
498
H-Index
10
About
Munkhjargal Gochoo is a multidisciplinary researcher whose work sits at the intersection of assistive robotics, human activity recognition, computer vision, and eldercare technology. With a body of work accumulating over 480 citations, Gochoo has established herself as a significant voice in developing intelligent systems that address real-world health and mobility challenges. Her contributions span several critical domains. In rehabilitation engineering, her systematic reviews on robotic assistive devices for upper limb recovery (71 citations) and foot drop rehabilitation (50 citations) have provided clinicians and engineers with rigorous comparative frameworks for emerging technologies. Her exploration of AI and cognitive training for aging populations (54 citations) reflects a sustained commitment to addressing the global eldercare crisis through technology. On the computational side, Gochoo has advanced human activity recognition through wearable sensor monitoring (66 citations) and deep learning architectures, including deep belief networks for healthcare pattern recognition (60 citations) and superpixel-based scene understanding (63 citations). Her privacy-preserving smart home research (48 citations) bridges ethical design with practical eldercare solutions. More recently, her work on YOLO-based emotion recognition (39 citations) and participation in the AI City Challenge demonstrates her expanding influence in real-time computer vision. Gochoo's research is unified by a humanistic drive: harnessing artificial intelligence and robotics to meaningfully improve quality of life for vulnerable populations.
Research Focus
Key Achievements
Top Papers
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- 6Trends and Technologies in Rehabilitation of Foot Drop: A Systematic Review50 citations · 2020
- 7Towards Privacy-Preserved Aging in Place: A Systematic Review48 citations · 2021
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- 10The 9th AI City Challenge16 citations · 2025