⚡ Quick Summary
This study utilized artificial intelligence for early gait analysis in patients undergoing total knee arthroplasty (TKA), revealing significant improvements in gait characteristics and clinical outcomes within just six weeks post-surgery. The findings indicate a marked reduction in knee pain and enhanced functional mobility for patients with knee osteoarthritis (KOA).
🔍 Key Details
- 👥 Participants: 26 patients (4 males, 22 females) aged 57-85 years
- 🦵 Condition: Unilateral knee osteoarthritis (K-L grades III and IV)
- 📅 Study Duration: February 2023 to July 2023
- 📊 Analysis Tool: OpenPose for gait analysis
- 📝 Evaluation Metrics: WOMAC arthritis index and Knee Society Score (KSS)
🔑 Key Takeaways
- 📉 WOMAC score decreased significantly from (64.85±11.54) to (45.81±7.91) (P<0.001).
- 📈 KSS improved from (101.19±9.58) to (125.50±10.32) (P<0.001).
- 🚶♂️ Gait speed increased from (0.32±0.10) m·s-1 to (0.48±0.11) m·s-1 (P<0.05).
- 🔄 Stride frequency rose from (96.35±24.18) steps·min-1 to (104.20±22.53) steps·min-1 (P<0.05).
- 📏 Stride length improved from (0.72±0.14) m to (0.79±0.10) m (P<0.05).
- 🦵 Active knee bending angle decreased from (125.21±11.64)° to (120.01±13.35)° (P<0.05).
- 🧘♂️ Squatting ability improved, with more patients able to complete the task post-surgery.
- 📈 Maximum bending angles for crouching and hip flexion increased significantly.
📚 Background
Total knee arthroplasty (TKA) is a common surgical intervention for patients suffering from severe knee osteoarthritis (KOA). Postoperative recovery often involves assessing gait characteristics to evaluate functional improvements. Traditional methods of gait analysis can be subjective and may not capture the full extent of recovery. The integration of artificial intelligence in gait analysis offers a promising avenue for more accurate and objective assessments.
🗒️ Study
Conducted between February and July 2023, this study involved 26 patients with unilateral KOA who underwent TKA. Researchers employed the OpenPose framework to analyze various gait parameters before and six weeks after surgery. The study aimed to quantitatively assess the changes in gait characteristics and clinical outcomes, utilizing both video analysis and established clinical scoring systems.
📈 Results
The results demonstrated significant improvements in both clinical scores and gait parameters. The WOMAC score showed a substantial decrease, indicating reduced pain and improved function. Similarly, the KSS reflected enhanced knee function. Notably, gait speed, stride frequency, and stride length all improved significantly, showcasing the effectiveness of TKA in restoring mobility.
🌍 Impact and Implications
The findings of this study underscore the potential of AI-driven gait analysis as a reliable tool for evaluating postoperative recovery in TKA patients. By providing objective measurements of gait characteristics, healthcare professionals can better tailor rehabilitation programs and monitor patient progress. This approach not only enhances patient care but also contributes to the growing body of evidence supporting the integration of technology in orthopedic rehabilitation.
🔮 Conclusion
This study highlights the effectiveness of artificial intelligence in early gait analysis following TKA, demonstrating significant improvements in both clinical outcomes and gait characteristics. As we continue to explore the intersection of technology and healthcare, the potential for enhanced patient outcomes through innovative approaches like AI-driven analysis becomes increasingly evident. Further research in this area could pave the way for more personalized and effective rehabilitation strategies.
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[Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition].
Abstract
OBJECTIVE: To explore early postoperative gait characteristics and clinical outcomes after total knee arthroplasty (TKA).
METHODS: From February 2023 to July 2023, 26 patients with unilateral knee osteoarthritis (KOA) were treated with TKA, including 4 males and 22 females, aged from 57 to 85 years old with an average of (67.58±6.49) years old;body mass index (BMI) ranged from 18.83 to 38.28 kg·m-2 with an average of (26.43±4.15) kg·m-2;14 patients on the left side, 12 patients on the right side;according to Kellgren-Lawrence(K-L) classification, 6 patients with grade Ⅲ and 20 patients with grade IV;the courses of disease ranged from 1 to 14 years with an average of (5.54±3.29) years. Images and videos of standing up and walking, walking side shot, squatting and supine kneeling were taken with smart phones before operation and 6 weeks after operation. The human posture estimation framework OpenPose were used to analyze stride frequency, step length, step length, step speed, active knee knee bending angle, stride length, double support phase time, as well as maximum hip flexion angle and maximum knee bending angle on squatting position. Western Ontario and McMaster Universities (WOMAC) arthritis index and Knee Society Score (KSS) were used to evaluate clinical efficacy of knee joint.
RESULTS: All patients were followed up for 5 to 7 weeks with an average of (6.00±0.57) weeks. The total score of WOMAC decreased from (64.85±11.54) before operation to (45.81±7.91) at 6 weeks after operation (P<0.001). The total KSS was increased from (101.19±9.58) before operation to (125.50±10.32) at 6 weeks after operation (P<0.001). The gait speed, stride frequency and stride length of the affected side before operation were (0.32±0.10) m·s-1, (96.35±24.18) steps·min-1, (0.72±0.14) m, respectively;and increased to (0.48±0.11) m·s-1, (104.20±22.53) steps·min-1, (0.79±0.10) m at 6 weeks after operation (P<0.05). The lower limb support time and active knee bending angle decreased from (0.31±0.38) s and (125.21±11.64) ° before operation to (0.11±0.04) s and (120.01±13.35) ° at 6 weeks after operation (P<0.05). Eleven patients could able to complete squat before operation, 13 patients could able to complete at 6 weeks after operation, and 9 patients could able to complete both before operation and 6 weeks after operation. In 9 patients, the maximum bending angle of crouching position was increased from 76.29° to 124.11° before operation to 91.35° to 134.12° at 6 weeks after operation, and the maximum bending angle of hip was increased from 103.70° to 147.25° before operation to 118.61° to 149.48° at 6 weeks after operation.
CONCLUSION: Gait analysis technology based on artificial intelligence image recognition is a safe and effective method to quantitatively identify the changes of patients’ gait. Knee pain of KOA was relieved and the function was improved, the supporting ability of the affected limb was improved after TKA, and the patient’s stride frequency, stride length and stride speed were improved, and the overall movement rhythm of both lower limbs are more coordinated.
Author: [‘Zhang M’, ‘Sui YN’, ‘Wang C’, ‘Zhang HC’, ‘Cai ZW’, ‘Zhang QL’, ‘Zhang Y’, ‘Xia TT’, ‘Zu XR’, ‘Huang YJ’, ‘Huang CS’, ‘Li X’]
Journal: Zhongguo Gu Shang
Citation: Zhang M, et al. [Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition]. [Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition]. 2024; 37:855-61. doi: 10.12200/j.issn.1003-0034.20240321