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The Bone & Joint Journal
Vol. 100-B, Issue 1 | Pages 50 - 55
1 Jan 2018
Kono K Tomita T Futai K Yamazaki T Tanaka S Yoshikawa H Sugamoto K

Aims. In Asia and the Middle-East, people often flex their knees deeply in order to perform activities of daily living. The purpose of this study was to investigate the 3D kinematics of normal knees during high-flexion activities. Our hypothesis was that the femorotibial rotation, varus-valgus angle, translations, and kinematic pathway of normal knees during high-flexion activities, varied according to activity. Materials and Methods. We investigated the in vivo kinematics of eight normal knees in four male volunteers (mean age 41.8 years; 37 to 53) using 2D and 3D registration technique, and modelled the knees with a computer aided design program. Each subject squatted, kneeled, and sat cross-legged. We evaluated the femoral rotation and varus-valgus angle relative to the tibia and anteroposterior translation of the medial and lateral side, using the transepicodylar axis as our femoral reference relative to the perpendicular projection on to the tibial plateau. This method evaluates the femur medially from what has elsewhere been described as the extension facet centre, and differs from the method classically applied. . Results. During squatting and kneeling, the knees displayed femoral external rotation. When sitting cross-legged, femurs displayed internal rotation from 10° to 100°. From 100°, femoral external rotation was observed. No significant difference in varus-valgus angle was seen between squatting and kneeling, whereas a varus position was observed from 140° when sitting cross-legged. The measure kinematic pathway using our methodology found during squatting a medial pivoting pattern from 0° to 40° and bicondylar rollback from 40° to 150°. During kneeling, a medial pivot pattern was evident. When sitting cross-legged, a lateral pivot pattern was seen from 0° to 100°, and a medial pivot pattern beyond 100°. Conclusion. The kinematics of normal knees during high flexion are variable according to activity. Nevertheless, our study was limited to a small number of male patients using a different technique to report the kinematics than previous publications. Accordingly, caution should be observed in generalizing our findings. Cite this article: Bone Joint J 2018;100-B:50–5


The Bone & Joint Journal
Vol. 98-B, Issue 10_Supple_B | Pages 16 - 21
1 Oct 2016
Jones GG Kotti M Wiik AV Collins R Brevadt MJ Strachan RK Cobb JP

Aims

To compare the gait of unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) patients with healthy controls, using a machine-learning approach.

Patients and Methods

145 participants (121 healthy controls, 12 patients with cruciate-retaining TKA, and 12 with mobile-bearing medial UKA) were recruited. The TKA and UKA patients were a minimum of 12 months post-operative, and matched for pattern and severity of arthrosis, age, and body mass index.

Participants walked on an instrumented treadmill until their maximum walking speed was reached. Temporospatial gait parameters, and vertical ground reaction force data, were captured at each speed. Oxford knee scores (OKS) were also collected. An ensemble of trees algorithm was used to analyse the data: 27 gait variables were used to train classification trees for each speed, with a binary output prediction of whether these variables were derived from a UKA or TKA patient. Healthy control gait data was then tested by the decision trees at each speed and a final classification (UKA or TKA) reached for each subject in a majority voting manner over all gait cycles and speeds. Top walking speed was also recorded.