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
张明 1眭亚楠 2王铖 3张浩冲 3蔡志威 3张权磊 4张宇 5夏天天 6祖潇然 4黄一健 4黄从书 6李想3
作者信息
- 1. 解放军总医院第四医学中心骨科医学部,北京 100048;解放军医学院,北京 100853
- 2. 清华大学,北京 100084
- 3. 解放军总医院第四医学中心骨科医学部,北京 100048
- 4. 解放军医学院,北京 100853
- 5. 滨州市人民医院,山东 滨州 256600
- 6. 中国人民解放军军事科学院军事医学研究院,北京 100039
- 折叠
摘要
目的:探讨全膝关节置换术(total knee arthroplasty,TKA)术后的早期步态特征及临床结果.方法:自2023年2月到2023年7月采用TKA治疗单侧膝骨关节炎(knee osteoarthritis,KOA)患者26例,男4例,女22例;年龄57～85(67.58±6.49)岁;身体质量指数(body mass index,BMI)为 18.83～38.28(26.43±4.15)kg·m-2;左膝 14 例,右膝 12 例;Kellgren-Lawrence分级,Ⅲ级6例,Ⅳ级20例;病程1～14(5.54±3.29)年.使用智能手机分别于术前、术后6周拍摄患者起立行走、行走侧拍、蹲起、仰卧屈膝的影像视频,通过人体姿势估计框架OpenPose分析步频、步长、步长时间、步速、膝关节主动屈膝角度、步幅、双下肢支撑相时间以及蹲姿中最大屈髋、屈膝角度.分别于术前及术后6周采用Western Ontario and McMaster 大学骨关节炎指数(Western Ontario and McMaster Universities Osteiarthritis Index,WOM-AC)评分和美国膝关节协会(Knee Society score,KSS)进行临床疗效评价.结果:所有患者获得随访,时间5～7(6.00±0.57)周.WOMAC 总分由术前的(64.85±11.54)分,减少至术后 6 周的(45.81±7.91)分(P＜0.001);KSS 由术前(101.19±9.58)分,提高至术后6周的(125.50±10.32)分(P＜0.001).患侧步速、步频、步幅分别由术前的(0.32±0.10)m.s-1、(96.35±24.18)步·分-1、(0.72±0.14)m,提高至术后的 6 周的(0.48±0.11)m·s-1、(104.20±22.53)步·分-1、(0.79±0.10)m(P＜0.05).双下肢支撑时间和主动屈膝角度由术前的(0.31±0.38)s、(125.21±11.64)°,减少至术后6周的(0.11±0.04)s、(120.01±13.35)°(P＜0.05).术前可以完成蹲起动作的11例,术后6周可以完成的13例,术前和术后6周同时可以完成的9例.9例蹲姿最大屈膝角度由术前的76.29°～124.11°提高至术后6周的91.35°～134.12°,最大屈髋角度由术前的103.70°～147.25°提高至术后6周的118.61°～149.48°.结论:基于人工智能影像识别步态分析技术是一种安全、有效的方法可以定量识别出患者步态的变化.KOA患者在行TKA后膝关节疼痛缓解,功能得以改善,TKA术后患肢的支撑能力有所改善,患者的步频、步幅、步速得到了提升,双下肢整体运动节律更为协调.
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引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据