Intuitive Control of a Hybrid Prosthetic Leg During Ambulation

项目摘要/摘要 大多数下肢截肢患者使用被动假肢，这种假肢不能提供能量来帮助 活动，如楼梯或坡道上升或从坐到站过渡。这限制了机动性，特别是对于那些 膝盖以上截肢。电动假肢可以改善老年人的行动能力和社区参与度 然而，这些设备很重，并且当前的控制系统需要用户手动 在不同的步行活动之间过渡，这是繁琐的。利用之前的R01资金，我们开发了 使用来自假体上的传感器的数据的自适应、分级模式识别控制系统，以及 结合来自用户的肌电(EMG)信号，取决于其可靠性，以确定用户 通过在行走活动之间自动、无缝地转换，实现安全的假肢控制。一个 移动应用允许快速调整假体，并使用户能够在手动或手动之间进行选择 自动转换。利用其他资金，我们开发了一种可以在被动模式下操作的新型假肢 -在水平地面行走或在活动模式下-在活动期间，如爬楼梯或坐到站 过渡。这种方法可以实现更小、更轻的发动机、变速器和电池，使我们的混合动力腿 与其他供电设备相比，它明显更轻、更安静。我们的长期目标是开发出临床上可行的 提高截肢者生活质量的技术。一种带保险箱的轻质动力假体， 直观的控制系统可能会增加流动性--促进就业、休闲和社区参与 运动--并减少低运动量对身体和心理造成的影响。我们将比较混合动力车 在实验室和家庭环境中，腿与受试者的被动设备。在目标1中，我们将转变我们的适应性 混合腿的控制系统，训练用户在实验者手动过渡时使用该设备行走 设备在活动模式之间切换，并收集传感器数据和肌电信号以创建特定于用户的模式 识别控制系统。然后我们将确定该系统的分类精度。目标2和目标3 共同构成一项随机临床试验，采用AB-BA设计，将杂交腿与受试者自己的腿进行比较 无源设备。在目标2中，我们将为受试者的被动行为提供高级社区活动训练 腿或混合腿，按随机顺序，以满足以下所需的特定科目和一般活动目标 社区步行，并完成步行活动的全面生物力学评估，如楼梯或 用那条腿做坡道上升/下降和坐立转换。在目标3中，受试者将使用相同的腿进行4 在他们的家里和社区呆上几周，那里的活动和社区参与将由一个定制的 基于智能手机的应用程序。我们将比较所采取的步骤数和活动之间的转换数 对于每台设备。我们预计控制系统将是安全的，分类错误率低，没有 可能导致摔倒的错误。此外，我们假设，使用混合腿，受试者将行走更多 活动之间的转换更频繁，生物力学更类似于非截肢者。

Project Summary/Abstract Most individuals with lower limb amputations use passive prostheses, which do not provide energy to assist with activities such as stair or ramp ascent or sit-to-stand transitions. This limits mobility, in particular for those with above-knee amputations. Powered leg prostheses could improve the mobility and community participation of such individuals; however, these devices are heavy, and current control systems require the user to manually transition between different ambulation activities, which is cumbersome. With prior R01 funding, we developed an adaptive, hierarchical pattern recognition control system that uses data from sensors on the prosthesis, and incorporates electromyographic (EMG) signals from the user, depending on their reliability, to determine user intent and enable safe prosthesis control with automatic, seamless transitions between ambulation activities. A mobile application allows for rapid tuning of the prosthesis and enables the user to choose between manual or automatic transitions. With other funding, we developed a novel prosthetic leg that can operate in passive mode —during level-ground walking or in active mode—during activities such as stair climbing or sit-to-stand transitions. This approach enables smaller, lighter motors, transmissions, and batteries, making our Hybrid Leg significantly lighter and quieter than other powered devices. Our long-term objective is to develop clinically viable technologies to improve the quality of life for lower limb amputees. A lightweight powered prosthesis with a safe, intuitive control system may increase mobility—facilitating employment, leisure, and community participation activities—and reduce the physical and psychological consequences of low activity. We will compare the Hybrid Leg with subjects' passive devices in both in-lab and home environments. In Aim 1, we will transition our adaptive control system to the Hybrid Leg, train users to walk with this device while the experimenter manually transitions the device between activity modes, and collect sensor data and EMG signals to create a user-specific pattern recognition control system. We will then determine the classification accuracy of this system. Aims 2 and 3 together constitute a randomized clinical trial, with AB-BA design, comparing the Hybrid leg with subjects' own passive devices. In Aim 2, we will provide advanced community-mobility training for either the subject's passive leg or the Hybrid leg, in random order, to meet both subject-specific and general activity goals necessary for community ambulation, and complete a full biomechanical assessment of ambulation activities such as stair or ramp ascent/descent and sit-to-stand transitions with that leg. In Aim 3, subjects will use the same leg for 4 weeks in their home and community, where activity and community participation will be monitored by a custom smartphone–based app. We will compare the number of steps taken and number of transitions between activities for each device. We expect that the control system will be safe, with a low classification error rate and without errors that may cause a fall. In addition, we hypothesize that, using the Hybrid leg, subjects will ambulate more and transition between activities more frequently, with biomechanics more similar to those of non-amputees.