Effect of practice on similar and dissimilar skills in patient transfer through training with a robot patient

Multi-Flexible Body Dynamics Modeling and Experimental Study of the Patient Rehabilitation Transfer Device

Objectives

The patient rehabilitation transfer device is a typical personnel transfer equipment, which is mainly composed of outriggers, support arm, lifting arms, hooks, handrails, hydraulic cylinders, and other components. The existing research on the device is mainly focused on the configuration design and transfer mode, and the research on its dynamic characteristics during the transfer process has not been thoroughly discussed. Methodology. Based on the existing research, a portable hydraulic rehabilitation patient transfer device has been developed. Then the multi-rigid body dynamic and finite element flexible body models were established. Next, the dynamic characteristic difference between the two models of the device was studied.

Results

As shown in the results, the finite element multi-flexible body model has obvious flexible vibration in the lifting stage, and the amplitude reaches 16 mm in the motion startup stage due to the influence of rigid-flexible coupling. The tip acceleration of the flexible body model was also influenced by the vibration, and the maximum acceleration value reaches 0.06 m/s². According to the test results, the maximum acceleration of the terminal reaches 0.05 m/s², which is close to the finite-element multi-flexible model simulation results. The experimentally measured natural frequency of the device is 3.1 Hz, which is also close to 3.2 Hz calculated by the simulation. Because the flexible component in the flexible model is only the lift arm, the natural frequency is slightly larger than the experimental value.

Conclusion

According to the stress value of the finite element multi-body model motion process, the maximum stress appears at the moment when the motion reaches the top end, and the instantaneous stress reaches 206 Mpa, which is in line with the allowable stress range of the material design. The data obtained in this study will provide help for the follow-up clinical rehabilitation and intelligent device research.

3D Facial Pain Expression for a Care Training Assistant Robot in an Elderly Care Education Environment

As the elderly population increases, the importance of the caregiver’s role in the quality of life of the elderly has increased. To achieve effective feedback in terms of care and nursing education, it is important to design a robot that can express emotions or feel pain like an actual human through visual-based feedback. This study proposes a care training assistant robot (CaTARo) system with 3D facial pain expression that simulates an elderly person for improving the skills of workers in elderly care. First, in order to develop an accurate and efficient system for elderly care training, this study introduces a fuzzy logic–based care training evaluation method that can calculate the pain level of a robot for giving the feedback. Elderly caregivers and trainees performed the range of motion exercise using the proposed CaTARo. We obtained quantitative data from CaTARo, and the pain level was calculated by combining four key parameters using the fuzzy logic method. Second, we developed a 3D facial avatar for use in CaTARo that is capable of expressing pain based on the UNBC-McMaster Pain Shoulder Archive, and we then generated four pain groups with respect to the pain level. To mimic the conditions for care training with actual humans, we designed the system to provide pain feedback based on the opinions of experts. The pain feedback was expressed in real time by using a projector and a 3D facial mask during care training. The results of the study confirmed the feasibility of utilizing a care training robot with pain expression for elderly care training, and it is concluded that the proposed approach may be used to improve caregiving and nursing skills upon further research.