Accurate event detection is key to the successful design of semi-passive and powered prosthetics. Kinematically, the natural knee is complex, with translation and rotation components that have a substantial impact on gait characteristics. When simplified to a pin joint, some of this behaviour is lost. This study investigates the role of cruciate ligament stretch in event detection. A bicondylar knee design was used, constrained by analogues of the anterior and posterior cruciate ligaments. This offers the ability to characterize knee kinematics by the stretch of the ligaments. The ligament stretch was recorded using LVDTs parallel to the ligaments of the Russell knee on a bent knee crutch. Which was used to capture data on a treadmill at 3 speeds. This study finds speed dependence within the stretch of the cruciate ligaments, prominently around 5\% and 80\% of the gait cycle for the posterior and anterior. The cycle profile remains consistent with speed; therefore, other static events such as the turning point feature at around 90\% and 95\% of the cycle, for the posterior and anterior, respectively, could be used as a predictive precursor for initial contact. Likewise at 90\% and 95\%, another pair of turning points that in this case could be used to predict foot flat. This concludes that the use of a bicondylar knee design could improve the detection of events during the gait cycle, and therefore could increase the accuracy of subsequent controllers for powered prosthetics.

翻译：准确的事件检测是半被动式和动力式假肢成功设计的关键。从运动学角度看，自然膝关节结构复杂，其平移与旋转分量对步态特征具有显著影响。当简化为铰接关节时，部分运动特性会丢失。本研究探讨了十字韧带拉伸在事件检测中的作用。采用双髁膝关节设计，并通过模拟前、后十字韧带的约束结构进行限位。该方法能够通过韧带拉伸特征来表征膝关节运动学。在弯曲膝拐杖的Russell膝关节上，使用与韧带平行的线性可变差动变压器记录韧带拉伸数据，并在跑步机上以三种速度采集数据。研究发现十字韧带拉伸存在速度依赖性，后十字韧带和前十字韧带分别在步态周期约5%和80%处表现显著。周期轮廓随速度保持一致性，因此其他静态事件（如后十字韧带约90%和前十字韧带约95%处的转折点特征）可作为初始触地的预测前兆。同样在90%和95%处存在的另一对转折点，可用于预测足部放平。研究表明，采用双髁膝关节设计可提升步态周期事件检测能力，从而提高动力假肢后续控制器的准确性。