Ryo SUGAI
Papers
1
Total Citations
8
H-Index
1
About
Dr. Ryo Sugai is a pioneering researcher at the intersection of rehabilitation engineering and deep learning, with a primary focus on developing accessible, markerless motion capture technologies for clinical gait analysis. His most notable contribution is the development of a novel LSTM network-based framework that accurately estimates ground reaction forces (GRFs) during walking in stroke patients using only the low-cost Azure Kinect sensor. This work, published in 2023 and already garnering 8 citations, addresses a critical barrier in rehabilitation by eliminating the need for expensive force plates or wearable sensors. By demonstrating that deep learning can bridge the gap between simple video data and complex biomechanical metrics, Dr. Sugai’s research has significant implications for democratizing gait assessment in clinical settings, enabling more frequent and cost-effective monitoring of stroke recovery. His work stands out for its practical, patient-centered approach, directly tackling the challenge of measuring walking ability in populations with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1