Papers
13
Total Citations
139
H-Index
7
About
Masako Kanai-Pak is a pioneering researcher at the intersection of robotics and nursing education, whose work has fundamentally advanced how healthcare professionals are trained in patient transfer skills. Over more than a decade of sustained inquiry, she has led the design, development, and evaluation of sophisticated robot patients — humanoid simulators capable of mimicking diverse patient conditions, including paralysis, pain sensitivity, and cooperative movement — to address critical gaps in clinical training environments where access to real patients is limited. Her landmark contributions include the development of robot patient systems equipped with inertial measurement units and angular position sensors to objectively evaluate nurses' transfer techniques, replacing subjective assessments with quantifiable biomechanical data. Her most cited works, including her 2016 study on simulation training impact (29 citations) and her 2015 robot patient design evaluation (23 citations), demonstrate both the technical sophistication and practical value of her innovations. Kanai-Pak's research is particularly significant given global nursing faculty shortages and aging populations demanding higher care standards. By enabling self-directed, repeatable practice on programmable robot patients, she has helped transform nursing education into a more accessible, evidence-based discipline. Her cumulative body of work has garnered over 130 citations, establishing her as a leading voice in robotics-assisted healthcare training.
Research Focus
Key Achievements
Top Papers
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- 3Robot Patient Design to Simulate Various Patients for Transfer Training16 citations · 2017
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- 9Design of a robot for patient transfer training7 citations · 2013
- 10Robotics as a Tool in Fundamental Nursing Education6 citations · 2014