Specialists globally employ various clinical scales and instruments to assess balance, gait, and motor functions in children with cerebral palsy (CP). Selecting appropriate assessment tools is essential for planning studies, developing effective treatment strategies, and tracking clinical outcomes. Given the diversity in assessment needs – whether evaluating dynamic, functional, or static balance – there is a need to identify the most suitable tools for each aspect. Therefore, the primary objective of this review is to critically analyze current clinical and instrument-based assessment methods in the literature to determine the most effective approaches for pediatric CP. This systematic review retrieved 1,812 papers, of which only 23 met the inclusion criteria and presented assessment methods for evaluating balance and motor functions in pediatric CP. These methods were further organized into clinical and instrument-based assessment groups. Among clinical examinations, the Pediatric Balance Scale and Gross Motor Function Measures were considered gold standards and featured in eight studies. In contrast, postural sway measured with the Biodex Balance System, Gait Stability Indices from the GAITRite system, and EMG sensing were the predominant instrument-based observations. Despite this variety, a consensus on the best assessment methods remains lacking. This review highlights the potential of integrating AI-driven metrics that combine clinical and instrument-based data to enhance precision and individualized care. Future research should focus on creating integrated, individualized profiles to better capture the unique capabilities of children with CP, enabling more personalized and effective intervention strategies.

Lower limb rehabilitation robots based on linkage-based mechanisms have recently drawn significant attention in the field due to their numerous advantages. The control of previously proposed linkage-based gait rehabilitation robotic orthoses has been achieved using constant speed control without consideration for the interaction forces. However, such an approach can be harmful to people with stroke since the level of disability varies among individuals, and it may cause potential injuries when excessive force is applied by the robot. To overcome this limitation and improve the rehabilitation process, it is necessary to recognize the force exerted by the person during walking and adjust the robot’s assistive torque accordingly, to provide synchronized motion. Thus, in this work, a human-cooperative approach based on a stiffness control strategy for the six-bar linkage-based gait rehabilitation robot is presented. The proposed methodology can serve as a solid foundation for developing a human-cooperative approach for linkage-based lower limb rehabilitation robotic orthoses. The control was validated and tested with eight healthy human subjects. As a result, customized robotic assistance with this mechanism can be provided during training to meet the individual needs of stroke patients, which can lead to increased engagement and contribution, thus improving treatment outcomes.