Precision Gait Retraining for Children With Cerebral Palsy
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- Altec Inc.
- 入组人数
- 10
- 试验地点
- 3
- 主要终点
- Rating of Perceived Difficulty
研究概览
简要总结
This project will develop the first sensor-based mobile Pelvic Assist Device (mPAD) that can deliver precise, adaptable, pelvic control to restore natural coordination of upper- and lower-limb movements during gait in children with Cerebral Palsy
详细描述
Gait impairments hinder mobility for more than 760,000 children and adults living with cerebral palsy (CP) in the US. Motor relearning is possible for these individual but typically requires numerous training sessions with a team of physical therapists and assistants to restore coupling between upper- and lower-body segments while assisting spastic uncoordinated limb movement to improve gait kinematics. This clinical trial will meet the overall objective of testing the feasibility of developing a smart-robotic exoskeleton that is effective at providing guided pelvic assistance and support while biofeedback mediated training is facilitated under the supervision of a physiotherapist. The project will test a novel tethered Pelvic Assist Device (TPAD) with integratable electromyographic (EMG) and inertial (IMU) biofeedback that is uniquely capable of delivering precise, adaptable, multi-degree-of-freedom pelvic control to promote natural intersegmental coupling, restore coordination of upper- and lower-limb movement, and improve normal gait kinematics in children with CP. Because of its proximity to the center of mass and critical role in coordinating upper- and lower-limb control, the pelvis provides an ideal access point for physiotherapists to manually improve gait. The investigators will test the hypothesis that accurate sensor-based metrics of gait can be derived from EMG and IMU wearable sensors to develop a biofeedback system for motor learning that are integratable with TPAD to develop a new mobile mPAD device that is compliant with the target population.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 6 Years 至 —(Child, Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- 未提供
排除标准
- 未提供
结局指标
主要结局
Rating of Perceived Difficulty
时间窗: 1 day
Structured interviews will be used to grade the perception of difficulty in using the technology
Knee Range of Motion During Walking
时间窗: 1 day
Difference (in degrees) between knee range of motion during walking as detected by wearable sensors and motion capture
Gait Metric Accuracy
时间窗: 1 day
Measures the accuracy of identifying heel strike and toe off timing in % error when comparing measures from wearable sensors vs. motion capture
Pelvis Range of Motion During Walking
时间窗: 1 day
Difference (in degrees) between pelvis range of motion during walking as detected by wearable sensors and motion capture
Muscle Activation During Walking
时间窗: 1 day
Measures electromyographic (EMG) signals of trunk and lower limb muscles during gait which are necessary for designing and implementing a mobile pelvic assist device (mPAD) system with biofeedback
Trunk Range of Motion During Walking
时间窗: 1 day
Difference (in degrees) between trunk range of motion during walking as detected by wearable sensors and motion capture
Hip Range of Motion During Walking
时间窗: 1 day
Difference (in degrees) between hip range of motion during walking as detected by wearable sensors and motion capture
次要结局
未报告次要终点
