Background: Multiple fractures, particularly femoral fractures, are increasingly prevalent and associated with high mortality rates and significant functional impairments. This highlights the urgent need for effective rehabilitation strategies, such as robot-assisted training, to enhance recovery and improve quality of life. Objectives: This study aimed to evaluate the clinical effectiveness of robotassisted rehabilitation for multiple femoral fractures. Design: Single-subject design. Methods: A 15-day A-B-A' single-subject design was employed. A man in his 30s with multiple fractures underwent standard rehabilitation during the baseline (A) and regression baseline (A') phases, with robotic therapy introduced during the intervention phase (B). Daily assessments of mobility and balance were analyzed using the two-standard deviation method. Results: Robotic therapy led to significant improvements: the TUG test time decreased from 16.21±0.64 seconds (A) to 10.63±0.46 seconds (B) and 9.64±0.35 seconds (A'). The 10 MWT time improved from 6.31±0.64 seconds (A) to 5.41±0.17 seconds (B) and 5.01±0.12 seconds (A'). LOS increased from 364.01±35.83 cm² (A) to 484.67±29.97 cm² (B) and 518.03±18.82 cm² (A'). Plantar pressure imbalance (59.2% right, 40.8% left in A) was corrected to nearly equal distribution in B (49.4%/50.6%) and A' (50.8%/49.2%). Conclusion: Robotic rehabilitation therapy improves balance and weightbearing capacity in patients with multiple fractures, suggesting its effectiveness as an early intervention following bone union.

Near Infra-red (NIR) analytical method was applied to quantify fat, moisture, protein, and salt in meat products. To ensure an accurate analysis, the NIR analysis method was compared with Korean food standard codex method. Correlation coefficients were 0.961-0.997, and the ratio of standard error of prediction (SEP) with standard error of laboratory (SEL) were 1.01-1.32. Z-score and Q score were −0.02-0.95 and −0.27-0.15, respectively. A control chart was conducted for three meat products. Each control chart data consisted of fat, moisture, protein, and salt, and it was produced by NIR analysis. The control chart of meat products was used for quality control.