Intuitive Control of a Hybrid Prosthetic Leg During Ambulation

混合假肢在行走过程中的直观控制

• 批准号: 10200864
• 负责人: Levi John Hargrove
• 金额: $ 58.7万
• 依托单位: REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-06 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10200864
• 关键词: Accelerometer; Algorithms; American; Amputation; Amputees; Ankle; Architecture; Artificial Leg; Award; Biomechanics; Car Phone; Cellular Phone; Classification; Clinic; Clinical; Communities; Community Participation; Custom; Data; Data Set; Development; Devices; Employment; Enrollment; Environment; Funding; Gait; Goals; Home; Home environment; Hybrids; Individual; Intuition; Knee; Knee Prosthesis; Laboratories; Learning; Leg; Leisures; Lower Extremity; Manuals; Monitor; Motor; Outcome; Participant; Patients; Pattern Recognition; Phase; Prosthesis; Protocols documentation; Quality of life; Ramp; Randomized; Randomized Clinical Trials; Research; Safety; Signal Transduction; System; Technology; Testing; Torque; Training; Walking; Work; base; design; experience; falls; foot; improved; improved mobility; innovation; light weight; limb amputation; mobile application; novel; powered prosthesis; prosthesis control; psychologic; secondary outcome; sensor; transmission process; week trial

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.

项目概要/摘要 大多数下肢截肢者使用被动假肢，这种假肢不能提供能量来协助 诸如楼梯或坡道上升或从坐到站的转换等活动。这限制了行动能力，特别是对于那些患有 膝上截肢。动力腿假肢可以改善患者的活动能力和社区参与度 此类个人；然而，这些设备很重，并且当前的控制系统需要用户手动 不同的行走活动之间的转换很麻烦。利用之前的 R01 资金，我们开发了 自适应分层模式识别控制系统，使用来自假肢传感器的数据，以及 结合来自用户的肌电图 (EMG) 信号，根据其可靠性来确定用户 意图并通过步行活动之间的自动、无缝转换实现安全的假肢控制。一个 移动应用程序允许快速调整假肢，并使用户能够选择手动或 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运行的新型假肢 —在平地行走或处于主动模式期间 —在爬楼梯或坐站等活动期间 过渡。这种方法可以实现更小、更轻的电机、变速箱和电池，从而使我们的混合腿 比其他供电设备更轻、更安静。我们的长期目标是开发临床上可行的 改善下肢截肢者生活质量的技术。一种轻型动力假肢，具有安全、 直观的控制系统可以增加流动性——促进就业、休闲和社区参与 活动——并减少低活动对身体和心理的影响。我们将比较混合动力 在实验室和家庭环境中放置受试者无源设备的腿。在目标 1 中，我们将转变我们的适应性 混合腿的控制系统，训练用户使用该设备行走，同时实验者手动转换 设备在活动模式之间切换，并收集传感器数据和 EMG 信号以创建用户特定的模式 识别控制系统。然后我们将确定该系统的分类准确性。目标 2 和 3 一起构成一项随机临床试验，采用 AB-BA 设计，将混合腿与受试者自己的腿进行比较 无源器件。在目标 2 中，我们将为受试者的被动型或被动型提供高级社区流动性培训。 腿或混合腿，按随机顺序，以满足特定主题和一般活动目标所需的 社区步行，并完成步行活动的完整生物力学评估，例如爬楼梯或 用该腿进行斜坡上升/下降以及从坐到站的过渡。在目标 3 中，受试者将使用同一条腿 4 次 在他们的家中和社区中度过数周，其中的活动和社区参与将由定制人员进行监控 基于智能手机的应用程序。我们将比较所采取的步数和活动之间的转换次数 对于每个设备。我们期望控制系统是安全的，分类错误率低，并且没有 可能导致跌倒的错误。此外，我们假设，使用混合腿，受试者会走动更多 活动之间的转换更加频繁，生物力学与非截肢者更加相似。