14:02 〜 14:17
[HCG25-02] Utilization of Robotics and Digital Human Simulation Technologies for the Design and Evaluation of Sensor Wear and Motion Assistive Devices in Rehabilitation and Care Support
★Invited Papers
キーワード：支援ロボット、装着型ロボット、デジタルヒューマンシミュレーション、QOL
As society ages, the burden of rehabilitation and caregiving services continues to increase, but there are not enough caregivers due to labor shortages. To address this problem, assistive technologies are becoming more important.
In this presentation, I will introduce various approaches to advancing assistive technology, including sensor wear design based on simulations using digital human models, motion measurement integrated with machine learning, optimization of assistive robot movement, and field tests of gait-assistive suits for the elderly, as well as devices designed to reduce the physical burden on caregivers.
For instance, a wearable system with strain sensors was developed to measure upper limb motion for remote rehabilitation support, and a model was constructed to estimate joint angles using machine learning. To overcome the challenges of conventional trial-and-error sensor placement design, an analytical method utilizing a digital human model was introduced to enhance measurement accuracy. Through improvements to the suit, the accuracy of joint angle estimation was verified, demonstrating its applicability to motion assessment in remote environments.
Digital simulation models were also utilized in the design optimization of a robotic care device intended to assist the elderly in standing up. By analyzing joint torques and contact forces using a digital human model and device model, the physical burden was quantitatively evaluated, and a motion trajectory for the robot was proposed based on the simulation results.
Furthermore, a common concern regarding the use of assistive devices is the potential decline in the user's own physical abilities. To assess this impact, we evaluated assistive devices designed to reduce the physical burden on caregivers in a real-world environment. A four-week monitoring test was conducted on 30 caregivers at a nursing home, measuring subjective fatigue and physical performance. The results confirmed that short-term use of assistive wear during normal work reduced subjective fatigue but did not lead to a decline in physical performance.
With these studies, we aim to establish systematic design and evaluation methods for rehabilitation and care-assistive devices that leverage robotics and digital human simulation technologies, helping to develop more effective and efficient assistive technologies.
In this presentation, I will introduce various approaches to advancing assistive technology, including sensor wear design based on simulations using digital human models, motion measurement integrated with machine learning, optimization of assistive robot movement, and field tests of gait-assistive suits for the elderly, as well as devices designed to reduce the physical burden on caregivers.
For instance, a wearable system with strain sensors was developed to measure upper limb motion for remote rehabilitation support, and a model was constructed to estimate joint angles using machine learning. To overcome the challenges of conventional trial-and-error sensor placement design, an analytical method utilizing a digital human model was introduced to enhance measurement accuracy. Through improvements to the suit, the accuracy of joint angle estimation was verified, demonstrating its applicability to motion assessment in remote environments.
Digital simulation models were also utilized in the design optimization of a robotic care device intended to assist the elderly in standing up. By analyzing joint torques and contact forces using a digital human model and device model, the physical burden was quantitatively evaluated, and a motion trajectory for the robot was proposed based on the simulation results.
Furthermore, a common concern regarding the use of assistive devices is the potential decline in the user's own physical abilities. To assess this impact, we evaluated assistive devices designed to reduce the physical burden on caregivers in a real-world environment. A four-week monitoring test was conducted on 30 caregivers at a nursing home, measuring subjective fatigue and physical performance. The results confirmed that short-term use of assistive wear during normal work reduced subjective fatigue but did not lead to a decline in physical performance.
With these studies, we aim to establish systematic design and evaluation methods for rehabilitation and care-assistive devices that leverage robotics and digital human simulation technologies, helping to develop more effective and efficient assistive technologies.