Resarch topics

Smart Coaching Technology

Human modeling group

The average life expectancy in Japan is about 85 years, and it is estimated that 40% of the population will be elderly by 2030. The gap between life expectancy and healthy life expectancy, which measures the ability to live independently, is about 10 years, and many older adults will require some form of assistance during that decade. One must continue exercise habits and highly efficient training after completing rehabilitation treatment at medical institutions to cope with this decline in physical function. Therefore, we are developing “AI smart coaching technology that promotes independent skill improvement” with the tasks of non-contact exercise sensing, AI identification of physical functions, and automatic adjustment of difficulty level and parameters to realize a “smart society that enjoys healthy longevity” using AI technology. We aim to develop a device that can be used in the medical, nursing, and healthcare fields. We are especially focusing on applications in the medical, nursing, and healthcare fields, and are conducting joint research with medical professionals.

Gymnastics Support Mobile AppーHiroshima University・Yuichi Kurita/HUMANMODEL Co.ー

Activities of Daily Living (ADL) Recording and Estimation System ーHiroshima University・Yuichi Kurita/HUMANMODEL Co.ー

Development of AI innovative coaching technology to promote proactive skill development

References

Shino Matsuura, Kazuhiko Hirata, Hiroaki Kimura, Yoshitaka Iwamoto, Makoto Takahashi, Yui Endo, Mitsunori Tada, Tsubasa Maruyama, Yuichi Kurita, Motion measurement and analysis for Functional Independence Measure, International Journal of Automation Technology, 2023
Priyanka Ramasamy, Gunarajulu Renganathan, Yuichi Kurita, Muscle Activity and Ground Reaction Force-Based Control Strategies for Actuating Soft Wearables Using Squat Motion, IEEE Humanoids 2022, WeD1.4, Okinawa, Japan, November 28-30, 2022.
Mayuko Minakata, Tsubasa Maruyama, Mitsunori Tada, Priyanka Ramasamy, Swagata Das, and Yuichi Kurita, Safe Walking Route Recommender Based on Fall Risk Calculation Using a Digital Human Model on a 3D Map, IEEE Access, Vol.10, pp.8424-8433, January 2022
Swagata Das, Wataru Sakoda, Priyanka Ramasamy, Ramin Tadayon, Antonio Vega Ramirez, and Yuichi Kurita, Feature Selection and Validation of a Machine Learning-Based Lower Limb Risk Assessment Tool: A Feasibility Study, Sensors, 21(19):6459, September 2021
Haruki Toda, Tsubasa Maruyama, Yuichi Kurita, and Mitsunori Tada, Individual Adjustment of Contraction Parameters for Effective Swing Assist Using a Pneumatic Artificial Muscle in the Elderly, Applied Sciences, Vol.11, No.9, 4308, May 2021.