Chang WR Falls Prevention, LLC, Arlington, VA 22209, USA.
Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC 27695, USA.
Appl Ergon. 2018 Jan;66:32-40. doi: 10.1016/j.apergo.2017.08.004. Epub 2017 Aug 15.
Kinematics at heel strike instant (HSI) has been used to quantify slip severity. However, methods to identify HSI remain ambiguous and have not been evaluated under slippery conditions. A glass force plate was used to observe the contact interface between shoe and floor under slippery conditions. HSIs identified from the video captured beneath the force plate and from the force plate and kinematics were compared. The results showed that HSIs identified with the video were closer to those identified with the normal force threshold (NFT) (9.0 ms ± 5.5 ms) than were most of those identified with kinematics. Slips with a longer distance travelled between NFT HSI and video HSI had a larger heel horizontal velocity (>0.8 m/s) and a smaller foot angular velocity (<100deg/s) at the NFT instant, and were still part of the forward swing. The results show that improved methods are needed over NFT to identify HSI, especially under slippery conditions.
在跟部触地瞬间(HSI)的运动学已被用于量化滑动严重程度。然而,用于识别 HSI 的方法仍然存在歧义,并且尚未在湿滑条件下进行评估。使用玻璃测力板在湿滑条件下观察鞋和地板之间的接触界面。比较了从测力板下方拍摄的视频中以及从测力板和运动学中识别的 HSI。结果表明,与运动学相比,通过视频识别的 HSI 更接近通过正压力阈值(NFT)(9.0ms±5.5ms)识别的 HSI。在 NFT HSI 和视频 HSI 之间移动距离较长的滑动在 NFT 瞬间具有更大的脚跟水平速度(>0.8m/s)和更小的足部角速度(<100deg/s),并且仍然是前摆的一部分。结果表明,需要改进 NFT 来识别 HSI 的方法,尤其是在湿滑条件下。