Necessity and feasibility of care training assistant robot (CaTARo) as shoulder complex joint with multi-DOF in elderly care education

Abstract

As the geriatric population expands, caregivers require more accurate training to handle and care for the elderly. However, students lack methods for acquiring the necessary skill and experience, as well as sufficient opportunities to practice on real human beings. To investigate the necessity and feasibility of care training assistant robots in care education, we developed a simulated robot as a shoulder complex joint with multi-DOF. In this study, five experts with years of experience in elderly care participated in the data-acquisition process, to acquire information on aspects such as the glenohumeral angle, as well as the sterno-clavicular joint and its torque. The experts performed three types of range-of-motion exercises: (i) elevation-depression of sterno-clavicular joint; (ii) extension and flexion of glenohumeral joint; (iii) lateral and medial rotation of glenohumeral joint. The experimental results showed that the quantitative results for all the exercises were significantly different between the experts. Moreover, we observed that even experienced professionals need consistent care education based on quantitative data and feedback. Thus, we confirmed the necessity and feasibility of the care training assistant robot for improving the skills required for elderly care.

More than surgical tools: a systematic review of robots as didactic tools for the education of professionals in health sciences

“…From these, many replicate just extremity joints such as the upper limb (e.g. (Lee et al, 2020a , b )) or the hip and knee (Frey et al, 2006 ). However, some studies like (Frey et al, 2006 ) complement the robotic construction with a non-actuated human mannequin to resemble the rest of the human body, and other multimodal feedback channels such as screens or voice synthesis.…”

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

“…Passive ROM exercise is a type of physical exercise that is used for improving the movement of joints, which is one of the most important tasks in elderly care because the elderly may experience limited joint movement in daily life due to the stiffness, contraction, or weakness of muscles. Considering a care training robot, we propose the use of CaTARo, which was developed as a method to effectively improve the care abilities of caregivers or students in preliminary studies ( Murata et al, 2017 ; Lee et al, 2019a ; Lee et al, 2020b ). As shown in Figure 2 , the upper limb of CaTARo consists of the glenohumeral, sternoclavicular, and elbow joint based on six degrees of freedom (DOF).…”

“…More detailed explanations of the hardware design and the way in which CaTARo reproduces the joint angle and torque of the elderly are described in ( Murata et al, 2017 ; Lee et al, 2019a ; Lee et al, 2020b ). In brief, according to the Human Body Properties Database ( NITE, 2019 accessed on 2019–05–06) in Japan, the statistics show that elderly people had the average upper arm and forearm lengths of 289 and 225 mm, respectively, and the average circumferences of the upper arm and forearm were 280 and 242 mm, respectively.…”

“…Huang et al ( Huang et al, 2014a ; Huang et al, 2014b ; Huang et al, 2015 ; Huang et al, 2016 ; Huang et al, 2017 ) proposed a robot for transfer training based on a voice feedback system that was used to enable the robot to receive nurses’ commands. Further, in our previous studies ( Murata et al, 2017 ; Lee et al, 2019a ; Lee et al, 2019b ; Lee et al, 2020a ; Lee et al, 2020b ), a graph-based care education program was developed, and this method was designed as a program with built-in guidance of experts (caregivers) and helps users to learn care skills using simulated robots based on the graphs displayed on the monitor. However, the existing graph-based method has the following limitations: it is difficult to recognize the emotional state of the simulated robot and it is difficult to receive feedback on the pain or stress the robot feels during care education, as shown in Figure 1 .…”

“…A preliminary version of this work has been introduced ( Murata et al, 2017 ; Lee et al, 2019a ; Lee et al, 2020b ); in this study, we provide additional functions that can provide the feedback on the practical skill with 3D facial pain expression compared to the previous work. In addition, this study proposes a visual-based feedback method to ensure amicable interactions between simulated robots and users.…”