Xiaohan Xiang, Yoji Yamada, Yasuhiro Akiyama, Ziliang Tao, and Naoki Kudo
Xiaohan Xiang*, Yoji Yamada, Yasuhiro Akiyama, Ziliang Tao, and Naoki Kudo
Department of Mechanical Systems Engineering, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya, 464-8603, JapanReceived Date: June 04, 2021; Accepted Date: June 18, 2021; Published Date: June 25, 2021
Citation: Xiang X, Yamada Y, Akiyama Y, Tao Z, Kudo N (2021) Validation of Lumbar Compressive Force Simulation in Forwarding Flexion Condition. Int J Anesth Pain Med Vol.7 No.4:45.
Safety requirements must be developed to enhance the social acceptability of lumbar-type physical assistant robots which are expected to reduce or mitigate the risk of Low Back Pain (LBP) e.g., for caregivers at clinical sites. In the associated International Safety Standard ISO 13482 [1], however, safety requirement is limited only to conceptual design guidelines stating as “A personal care robot shall be designed to minimize or reduce physical stress or strain to its user due to continuous use”. It is also true for the Japanese standard for lumbar-type physical assistant robots, JIS B 8456-1 [2], which simply requires a positive amount of maximum assist force to show effective, safe use of the robots.
However, it is easy to consider that the CF exerted at lumbar vertebra changes depending on the posture and motions of the caregivers. Therefore, safety requirements need to be rigorously made for checking whether such manners as caregivers transfer care receivers are safe enough with the lumbar-type robots worn. Even without raising a technical issue of whether or not such robots are operated with proper posture which is intended by the manufacture of the robots, caregivers at clinical sites desire to learn whether their ways of transferring care receivers are appropriate or not.
Since a comprehensive validation of a simulator in dynamic conditions has not been conducted, we discuss the validation of CF simulators in the study based on inverse dynamics computation. Taking into account that CF simulators can be easily constructed and combined with the moment arm proposed by Chaffin et al. [3], and considering that estimating the CF concerning the lifting motion in the sagittal plane substantially provides information regarding the peak CF estimation, an ergonomic simulator is validated through forwarding flexion invasive experiments.
We also compare the data estimated by one of the CF simulators and those obtained by the regression models proposed by Potvin et al. [4] and Merryweather et al. [5] with the results of previous invasive CF experiments [6-9]. The correspondence between the simulated and experimental Compressive Force (CF), as well as the CF, obtained using two existing models about the unified angle, is investigated. The results show that the CF error between the measurements and the simulator at a flexion angle of 30Ã? is 11.8% and is lower than those obtained for the other two models (16.8% and 20.6%). Linear regression shows that the invasive data and estimated CF are close (slope=1) in Merryweather’s model and CF simulator but not for Potvin’s model. We also evaluate the precision of the simulator by using the intraclass correlation coefficient method.
Merryweather’s model is moderately consistent with invasive measurements, with R–0.685 and 0.627 at 0 and 30Ã?, while the CF simulator shows good consistency with Merryweather’s model with R-0.879 and 0836 at 0 and 30Ã?.
We attempt to introduce the above simple dynamic simulators as well as the analytical models because they are promising enough to be simply applied to the estimation of lumbar burden at practical sites and to be standardized. We also studied injury risk curves to clarify the risk level of injury to the lumbar spine due to lumbar compressive force for individuals within a wide age range [10] to apply the verified compressive strength data which are age-dependent.
Ongoing work includes further investigation of estimated CF concerning lifting motions and introduction of EMG measurement to combine the output signals with the analytical model for CF estimation.