Traditional evaluations of handwriting assistive devices have primarily relied on user satisfaction surveys. While recent advancements in computer technologies and digital devices have enabled more objective evaluations, these methods often lack comprehensiveness. This study introduces a scientific and systematic evaluation method for evaluating handwriting assistive devices used by individuals with upper limb dysfunction. The proposed method incorporates both writing and drawing tasks, utilizing advanced computer technology and sophisticated sensors in tablets and digital pens to measure key handwriting parameters across ten indicators. These indicators are synthesized into a comprehensive score using the entropy weight method (EWM). Additionally, objective scores were compared with subjective evaluations from participants. A strong positive correlation between objective and subjective evaluations confirms the reliability of our objective method. However, statistical analysis revealed a significant mean difference between the two scoring methods, indicating that the objective method provides a more standardized and quantifiable evaluation, effectively minimizing the influence of personal biases inherent in subjective evaluations. This comprehensive evaluation method not only offers a holistic evaluation of handwriting assistive devices but also addresses the limitations of existing objective methods that tend to focus on singular aspects of performance.

The half-sitting posture is essential for many functional tasks performed by industrial workers. Thus, passive lower-limb exoskeletons, known as wearable chairs, are increasingly used to relieve lower-limb loading in such scenarios. However, although these devices lighten muscle effort during half-sitting tasks, they can disrupt walking mechanics and balance. Moreover, rigorous biomechanical data on joint moments and contact forces during walking with such a device remain scarce. Therefore, this study conducted a biomechanical evaluation of level walking with a wearable chair to quantify its effects on gait and joint loading. Participants performed walking experiments with and without the wearable chair. An optical motion capture system and force plates collected kinematic and ground reaction data. Six-axis force sensors measured contact forces and moments. These measurements were fed into a Newton–Euler inverse dynamics model to estimate lower-limb joint moments and assess joint loading. The contact measurements showed that nearly all rotational load was absorbed at the thigh attachment, while the ankle attachment served mainly as a positional guide with minimal moment transfer. The inverse dynamics analysis revealed that the wearable chair introduced unintended rotational stresses at lower-limb joints, potentially elevating musculoskeletal risk. This detailed biomechanical evidence underpins targeted design refinements to redistribute loads and better protect lower-limb joints.