中国骨伤2024，Vol.37Issue(9)：855-861,7.DOI:10.12200/j.issn.1003-0034.20240321
基于人工智能动态影像识别的全膝关节置换术后早期步态分析研究
Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition
摘要
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 in-dex(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 pa-tients 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 op-eration to(45.81±7.91)at 6 weeks after operation(P＜0.001).The total KSS was increased from(101.19±9.58)before opera-tion 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)sand(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 pa-tients'gait.Knee pain of KOA was relieved and the function was improved,the supporting ability of the affected limb was im-proved 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.关键词
全膝关节置换术/人工智能/膝骨关节炎Key words
Total knee arthroplasty/Artificial intelligence/Knee osteoarthriti分类
医药卫生引用本文复制引用
张明,黄一健,黄从书,李想,眭亚楠,王铖,张浩冲,蔡志威,张权磊,张宇,夏天天,祖潇然..基于人工智能动态影像识别的全膝关节置换术后早期步态分析研究[J].中国骨伤,2024,37(9):855-861,7.基金项目
国家自然科学基金(编号:U22A2052)National Natural Science Foundation of China(No.U22A2052) （编号:U22A2052）
