Background: Flexible flatfoot impairs gait and posture by weakening arch support, potentially leading to musculoskeletal dysfunction. Strengthening exercises, such as the short foot exercise (SFE), have shown promise in correcting this condition. Objectives: This study aimed to investigate the effects of SFE with visual feedback on medial arch height and foot function in adults with flexible flatfoot. Design: Experimental research. Methods: Adults diagnosed with flexible flatfoot were randomly assigned to either an experimental or control group. The experimental group performed SFE with visual feedback, whereas the control group performed the same exercises without feedback. Both groups trained three times per week for five weeks. Outcome measures included the Navicular Drop Test (NDT), YBalance Test (YBT), and Tetrax postural analysis. Results: In the NDT, both groups showed significant improvements (P<.05), while in the YBT, only the experimental group showed a significant improvement (P<.05). In contrast, there were no significant changes in the Weight Distribution Index (WDI) and Stability Test (ST) areas of the Tetrax system in either group (P>.05). Conclusion: SFE effectively improved arch height regardless of visual feedback, though only the visual feedback group showed significant improvements in dynamic balance. However, between-group differences were not statistically significant, suggesting that visual feedback provides subtle rather than substantial additional benefits. Further research with larger samples is needed to establish the clinical value of adding visual feedback to SFE protocols.

Background: The Functional Movement Screen (FMS) is widely used for movement assessment but suffers from subjective scoring that leads to inconsistent evaluations. While previous studies have focused on reliability, the validity of AI-supported assessment remains unexplored. Objectives: To evaluate the reliability and validity of an AI-based motion analysis system using MediaPipe for three FMS movements. Design: Prospective reliability and validity study with repeated measures. Methods: Thirty healthy adults (age 23.4±2.8 years) performed three FMS tests (Deep Squat, Hurdle Step, Inline Lunge) recorded on video. Three evaluators (two experienced physical therapists and one novice) assessed recordings in three phases: Phase 1 involved traditional assessment by experts only to establish criterion reference, Phase 2 had all evaluators using AI support, and Phase 3 consisted of repeated AI-supported assessment. The AI system provided real-time visual feedback of joint angles and alignment through MediaPipe skeletal tracking. Results: Criterion validity showed strong agreement between traditional expert assessment and AI-supported assessment (r=0.94, P<.05). Inter-rater reliability improved from good (ICC=0.89) to excellent (ICC=0.91) with AI support. The novice evaluator achieved immediate expert-level performance with only 0.05 points difference from experts. Intra-rater reliability was excellent for all evaluators (ICC=0.84-0.89). Conclusion: The AI-based system demonstrated strong validity and improved reliability for fundamental movement assessment. While AI support enabled novice evaluators to achieve expert-level performance immediately, it may increase sensitivity to subtle movement variations. This technology shows promise for standardizing movement screening, though current limitations restrict its application to standing movements.

Background: Neck discomfort and movement limitations are common musculoskeletal problems among modern people. While cervical and thoracic joint mobilization are widely used interventions for cervical dysfunction, research comparing their immediate effectiveness in adults with asymmetrical cervical rotation is limited. Objectives: To compare the immediate effects of cervical versus thoracic joint mobilization in adults with adults with asymmetrical cervical rotation and discomfort. Design: Randomized controlled trial. Methods: Thirty adults with left-right differences in cervical rotation of more than 5 degrees were randomly assigned to a cervical mobilization group (CMG, n=15) or thoracic mobilization group (TMG, n=15). Both groups received Grade III mobilization for 15 minutes. Range of motion (ROM), pain (VAS), and neck disability index (NDI) were measured before and after intervention. Results: Both groups showed significant increases in ROM after intervention (P<.001). Within-group analysis revealed that the TMG showed significant pain reduction (P<.01) and significant reduction in left-right rotation asymmetry (P<.001), while the CMG showed improvement in ROM but no significant changes in asymmetry or pain (P>.05). Neither group showed significant changes in NDI. Between-group comparisons showed no significant differences in any outcome measures. Conclusion: Both cervical and thoracic joint mobilization increased cervical range of motion in adults with asymmetrical cervical rotation discomfort. The TMG demonstrated significant within-group improvements in left-right rotation asymmetry and pain reduction, suggesting potential clinical benefits of thoracic mobilization for certain aspects of cervical dysfunction.

Background: Automated classification systems using Artificial Intelligence (AI) and Machine Learning (ML) can enhance accuracy and efficiency in diagnosing pet skin diseases within veterinary medicine. Objectives: This study created a system that classifies pet skin diseases by evaluating multiple ML models to determine which method is most effective. Design: Comparative experimental study. Methods: Pet skin disease images were obtained from AIHub. Models, including Multi-Layer Perceptron (MLP), Boosted Stacking Ensemble (BSE), H2O AutoML, Random Forest, and Tree-based Pipeline Optimization Tool (TPOT), were trained and their accuracy assessed. Results: The TPOT achieved the highest accuracy (94.50 percent), due to automated pipeline optimization and ensemble learning. H2O AutoML also performed well at 94.25 percent, illustrating the effectiveness of automated selection for intricate imaging tasks. Other models scored lower. Conclusion: These findings highlight the potential of AI-driven solutions for faster and more precise pet skin disease diagnoses. Future investigations should incorporate broader disease varieties, multimodal data, and clinical validations to solidify the practicality of these approaches in veterinary medicine.

Background: Patients who underwent rotator cuff repair (RCR) require management to control pain and prevent re tear and stiffness. Thoracic mobilization has been applied for the improvement of vertebra and shoulder movements and pain reduction. Also, core stability exercise is an intervention necessary for rehabilitation after shoulder surgery. Objectives: To examine the short term benefits of thoracic mobilization and core stability exercise for patients after RCR. Design: Randomized controlled trial with multi arm parallel group and single blind assessor. Methods: 30 participants after RCR were recruited. Participants were categorized into conventional physical therapy (CPT) group, thoracic mobilization (TM) group, and core stability exercise (CSE) group according to the randomization program. Each treatment, transcutaneous electrical nerve stimuli (TENS), TM, and CSE was applied to each group. 3 physical therapists only conducted evaluations; VAS (visual analogue scale), ROM (range of motion), and Korean version of Shoulder Pain and Disability Index (SPADI). Results: VAS and SPADI were statistically reduced, and ROM was statistically improved in all 3 groups. In between three group comparisons of changes in outcome variables, there was not a significant difference in VAS, but there was a significant difference in ROM and SPADI. In the post hoc test, ROM and SPADI showed a significant difference in TM and CSE compared to CPT. Conclusion: TM according to Maitland concept and CSE had beneficial effects compared to CPT in patients after RCR.