Wang Liping, Li Xin, Peng Yiying, Han Jianda, Zhang Juanjuan
Tianjin Key Laboratory of Intelligent Robotics, Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300350, China.
College of Artificial Intelligence, Nankai University, Tianjin 300350, China.
Bioengineering (Basel). 2024 Apr 16;11(4):386. doi: 10.3390/bioengineering11040386.
The impairment of walking balance function seriously affects human health and will lead to a significantly increased risk of falling. It is important to assess and improve the walking balance of humans. However, existing evaluation methods for human walking balance are relatively subjective, and the selected metrics lack effectiveness and comprehensiveness. We present a method to construct a comprehensive evaluation index of human walking balance. We used it to generate personal and general indexes. We first pre-selected some preliminary metrics of walking balance based on theoretical analysis. Seven healthy subjects walked with exoskeleton interference on a treadmill at 1.25 m/s while their ground reaction force information and kinematic data were recorded. One subject with Charcot-Marie-Tooth walked at multiple speeds without the exoskeleton while the same data were collected. Then, we picked a number of effective evaluation metrics based on statistical analysis. We finally constructed the Walking Balance Index (WBI) by combining multiple metrics using principal component analysis. The WBI can distinguish walking balance among different subjects and gait conditions, which verifies the effectiveness of our method in evaluating human walking balance. This method can be used to evaluate and further improve the walking balance of humans in subsequent simulations and experiments.
行走平衡功能的损害严重影响人类健康，并将导致跌倒风险显著增加。评估和改善人类的行走平衡非常重要。然而，现有的人类行走平衡评估方法相对主观，所选指标缺乏有效性和全面性。我们提出了一种构建人类行走平衡综合评估指标的方法。我们用它来生成个人指标和综合指标。我们首先基于理论分析预先选择了一些行走平衡的初步指标。七名健康受试者在跑步机上以1.25米/秒的速度穿着外骨骼进行行走，同时记录他们的地面反作用力信息和运动学数据。一名患有夏科-马里-图斯病的受试者在不穿外骨骼的情况下以多种速度行走，同时收集相同的数据。然后，我们基于统计分析挑选了一些有效的评估指标。我们最终使用主成分分析将多个指标相结合构建了行走平衡指数（WBI）。WBI能够区分不同受试者和步态条件下的行走平衡，这验证了我们的方法在评估人类行走平衡方面的有效性。该方法可用于在后续的模拟和实验中评估并进一步改善人类的行走平衡。
