Gait asymmetry, a consequence of various neurological or physical conditions such as aging and stroke, detrimentally impacts bipedal locomotion, causing biomechanical alterations, increasing the risk of falls and reducing quality of life. Addressing this critical issue, this paper introduces a novel diagnostic method for gait symmetry analysis through the use of an assistive robotic Smart Walker equipped with an innovative asymmetry detection scheme. This method analyzes sensor measurements capturing the interaction torque between user and walker. By applying a seasonal-trend decomposition tool, we isolate gait-specific patterns within these data, allowing for the estimation of stride durations and calculation of a symmetry index. Through experiments involving 5 experimenters, we demonstrate the Smart Walker's capability in detecting and quantifying gait asymmetry by achieving an accuracy of 84.9% in identifying asymmetric cases in a controlled testing environment. Further analysis explores the classification of these asymmetries based on their underlying causes, providing valuable insights for gait assessment. The results underscore the potential of the device as a precise, ready-to-use monitoring tool for personalized rehabilitation, facilitating targeted interventions for enhanced patient outcomes.

翻译：步态不对称是衰老、中风等多种神经或生理状况导致的后果，它会对双足运动产生不利影响，引发生物力学改变，增加跌倒风险并降低生活质量。针对这一关键问题，本文提出了一种通过配备创新不对称检测方案的辅助型智能助行机器人进行步态对称性分析的新型诊断方法。该方法通过分析捕捉用户与助行器之间交互扭矩的传感器测量数据，运用季节性趋势分解工具分离出数据中的步态特异性模式，从而实现对步态周期时长的估计及对称性指数的计算。通过对5名实验者进行的实验，我们在受控测试环境中实现了84.9%的不对称案例识别准确率，证明了该智能助行器在检测和量化步态不对称方面的能力。进一步的分析探索了基于潜在原因对这些不对称性进行分类的方法，为步态评估提供了有价值的见解。研究结果凸显了该设备作为一种精确、即用型监测工具在个性化康复中的潜力，有助于实施针对性干预以改善患者预后。