###### Abstract  
This study aimed to investigate if voluntary participation in robot-assisted gait training leads to more concentrated muscle activity patterns and clinical measure improvements. A single-participant research design study was conducted with a gradual reduction in robotic assistance during robot-assisted gait training. A child with cerebral palsy participated in 20 robot-assisted gait training sessions and two assessment sessions across 99 days. The assistive force of the Lokomat gradually reduced during repeated training. The effects of reduced assistive force on muscle activity patterns were quantitatively analyzed using a clustering algorithm and electromyography. Improvements in overall gait quality and muscle strength were measured after robot-assisted gait training. The results also showed that the number of clustered representative patterns doubled and muscle activation patterns increased when the assistance decreased by 20%, whereas full robot assistance might have hindered active participation. Since assistive force modulation can be a key in robotic rehabilitation, the proposed protocol, involving gradual assistive force reduction, demonstrates promising efficacy and allows for in-depth analysis. Therefore, further randomized clinical trials based on this study can be possible for children with cerebral palsy.  
improved in cerebral palsy [20] as well as stroke [21]. Therefore, consistently effective protocols remain uncertain, and there is still a need for in-depth investigation into robotic assistance, muscle activation, and strength to identify valid protocols.  
The effectiveness of RAGT also depends on voluntary participation, which leads to stronger brain plasticity and superior training effects compared to minimal engagement [22]. It has been suggested that reducing robotic involvement enhances movement variability, a key element in motor learning [23; 24]. Variability allows patients to explore alternative motor control pathways and detect movement errors, which are critical for skill acquisition [24; 25]. In other words, one approach to investigating the effectiveness and contributing factors in RAGT could be to reduce the level of assistance by robotic devices, which can result in collisional participation with movement variability. To effectively apply RAGT in children with cerebral palsy, it is important to understand how changes in the parameters related to robotic assistance affect their participation. Muscle activity quantification during RAGT is also necessary to determine the effect of muscle activity on the generated movements. Despite this potential, few studies have systematically explored the effects of reduced robotic assistance on muscle activity and gait function in children with cerebral palsy.  
In this context, we aim to address the key gap in the literature, that of the unclear role of robotic assistance parameters, specifically the guidance force (GF), in optimizing rehabilitation outcomes. Unlike previous studies, which primarily focus on the dose of RAGT, our approach leverages the robot's ability to modulate assistance in order to maintain a high level of training intensity. We hypothesize that gradually reducing robotic assistance will enhance voluntary muscle activation, leading to improved muscle activity patterns and clinical outcomes.  
To test this hypothesis, we conducted 20 RAGT sessions using the Lokomat (Hocoma, Switzerland) with a protocol that gradually reduced the GF based on the participant's adaptation and rehabilitation progress. In addition to clinical measures, muscle activity patterns were quantitatively analyzed using a clustering algorithm of muscle activation data. By investigating how gradual GF reduction influences muscle activation and clinical outcomes, this study can provide a novel framework for protocol-optimizing RAGT for children with cerebral palsy.