Wearable Interactive Lower-limb Exoskeleton Robotic Device for Gait Training of Post-stroke Patients on Different Walking Conditions
试验速览
- 阶段
- 不适用
- 入组人数
- 64
- 试验地点
- 1
- 主要终点
- Functional Ambulatory Category (FAC)
研究概览
简要总结
A new lower-limb training system is introduced to enhance the clinical service for post-stroke lower limb rehabilitation and to assist the establishment of public clinical trial in different settings and share experiences on the robot-assisted functional training.
详细描述
Stroke is caused by intracranial haemorrhage or thrombosis, which cuts off arterial supply to brain tissue and usually damages the motor pathway of the central nervous system affecting one side of the body. Reduced descending neural drive to the affected side could lead to hemiplegia, which significantly influences the activity of daily living (ADL) of stroke survivors (Singam, Ytterberg, Tham & von Koch, 2015). While the upper-limb motor impairment could be compensated using the contralateral side for picking up or manipulating objects, the loss of motor functionality on the lower limb would substantially limit the mobility and body balance. Many stroke survivors are dependent on walking aids or manual support from caregivers for standing and walking, otherwise they would have great risk of falling with serious consequences (Tasseel-Ponche, Yelnik & Bonan, 2015).
Recent studies suggest stroke patients could relearn walking ability by developing alternative neural circuitries through long-term adaptation process, known as neuroplasticity. High-intensity, repetitive, and task-specific gait training is the key to enhance gait recovery of hemiplegic stroke patients (Kreisei, Hennerici & Bäzner, 2007; Kleim & Jones, 2008). The development of robot-assisted lower-limb exoskeleton devices has great clinical potential in stroke rehabilitation. Many lower-limb exoskeleton robots are clinically-available for non-ambulatory stroke patients to practice walking with passive assistance on body-weight-supported treadmill training (BWSTT) (Morone, et al., 2017).
Existing robot-assisted gait training (RAGT) such as Lokomat and electromechanical Gait Trainer provide automatic, rhythmic, and repetitive powered assistance to major lower-limb joints at hips and knees bilaterally (Poli, Morone, Rosati & Masiero, 2013). Large-scale randomized controlled trials (RCT) of these RAGT in combination with conventional therapies show significantly more chronic stroke patients improved functional gait independency and ADL than receiving conventional therapies alone (Pohl, et al., 2007; Schwartz, et al., 2009; Hidler, et al., 2009; Mehrholz, et al., 2013). However, Hesse, Schmidt, Werner & Bardeleben (2003) suggest the integration of robots into gait rehabilitation could merely be an auxiliary tool for therapists to enhance training intensity and safety without increasing their workload. Most clinically-available RAGT are bounded to treadmill with passive assistance (van Peppen, et al., 2004; Morone, et al., 2017), but researches show task-variations and active participation in gait training could improve retention of newly-learnt skills and could promote generalization of training effects (Salbach, et al., 2004; Kwon, Woo, Lee & Kim, 2015). Portable RAGT that allows active over-ground gait training would be more promising especially for ambulatory stroke patients.
Robot-assisted ankle foot orthosis (AFO) and knee brace are good candidates of portable exoskeleton devices for RAGT of hemiplegic stroke patients (Duerinck, et al., 2012; Zhang, Davies & Xie, 2013; Mehrholz, et al., 2017). Conventional AFO is mainly designed for treating foot drop gait abnormality with passive support in ankle dorsiflexion for foot clearance in swing phase and shock absorption in loading response. Conventional knee brace is mainly designed for body support in stance phase. The integration of robot assistance in the affected ankle and/or knee joint could provide active power assistance that synchronises to patients' voluntary residual ankle and/or knee movement. Long-term active power assistance might stimulate experience-driven gait recovery or develop compensatory gait pattern to facilitate gait (Kleim & Jones, 2008).
In order to translate robotic rehabilitation research into clinical application, evidence-based clinical research should be carried out to test the safety and effectiveness of the new devices or interventions on stroke patients (Backus, Winchester & Tefertiller, 2010). Many designs of robot-assisted AFO and knee braces have been proposed by different research groups, but most of them reported only the results of feasibility tests, mainly on healthy subjects with small sample sizes (Dollar & Herr, 2008; Shorter, et al., 2013; Alam, Choudhury & Bin Mamat, 2014). Majority of previous studies concerned about the immediate effects of wearing the robot-assisted AFOs and knee braces during walking, but few studies investigated the long-term therapeutic effects of wearing the devices for RAGT of stroke patients (Lo, 2012). In particular, systematic review by Mehrholz, et al. (2017) shows only one RCT has evaluated the efficacy of ankle training using robot-assisted AFO but in seated position, no RCT evaluated gait training using robot-assisted AFO on both over-ground walking and stair ambulation.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Treatment
- 盲法
- Double (Participant, Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •First episode of stroke,
- •Hemiparesis resulting from a unilateral ischemic or hemorrhagic stroke,
- •Functional Ambulation Category (FAC) > 2 out of 6, i.e. have ability to walk on the ground independently or under supervision, with or without assistive device,
- •Have sufficient cognition to follow instructions and to understand the content and purpose of the study.
排除标准
- •Uncontrolled cardiovascular or respiratory disorders,
- •Moderate to serve contractures in the lower extremities,
- •Orthopedic problems or muscle diseases that impair mobility,
- •Difficulty to comply with the study protocol and the gait training schedule, i.e. at least 2 sessions per week.
研究组 & 干预措施
Knee Sham group
Subjects will wear the Knee Robot during 20-session gait training, but no power assistance will be provided from the motor to the knee joint.
干预措施: Robotic knee system (Device)
Health Control
Healthy subjects will wear the Ankle Robot and/or Knee Robot during walking tasks (with or without power assistance), to collect control data for investigating if there are any effects of the robotic assistance on normal gait pattern.
Ankle Sham group
Subjects will wear the Ankle Robot during 20-session gait training, but no power assistance will be provided from the motor to the ankle joint.
干预措施: Robotic ankle system (Device)
Robotic ankle system
Subjects will wear the Ankle Robot during 20-session gait training, power assistance will be provided from the motor to the ankle joint.
干预措施: Robotic ankle system (Device)
Robotic knee system
Subjects will wear the Knee Robot during 20-session gait training, power assistance will be provided from the motor to the knee joint.
干预措施: Robotic knee system (Device)
结局指标
主要结局
Functional Ambulatory Category (FAC)
时间窗: Baseline, Post-Training, 3-month follow up
Functional Ambulatory Category (FAC) is a reliable measurement of independent walking ability on level-ground walking and stair ambulation, which is a good prediction of independent community walking post-stroke (Mehrholz, et al., 2007). FAC consists of 6-level scale: patients with FAC=4 requires supervision in level ground walking, FAC=5 requires supervision only when walking on non-level surface such as stairs.
次要结局
- Berg Balance Scale (BBS)(Baseline, Post-Training, 3-month follow up)
- Fugl-Meyer Assessment for Lower-Extremity (FMA-LE)(Baseline, Post-Training, 3-month follow up)
- Modified Ashworth Scale (MAS)(Baseline, Post-Training, 3-month follow up)
- Timed 10-Meter Walk Test (10mWT)(Baseline, Post-Training, 3-month follow up)
- 6-minute Walk Test (SMWT)(Baseline, Post-Training, 3-month follow up)
研究者
Raymond KY Tong
Professor
Chinese University of Hong Kong
