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This study presents a new method to estimate 3-D linear accelerations at tibial and femoral functional coordinate systems. The method combines the use of 3-D accelerometers, 3-D gyroscopes and reflective markers rigidly fixed on an exoskeleton and, a functional postural calibration method. Marker positions were tracked by a six-camera optoelectronic system (VICON 460, Oxford Metrics). The purpose of this study was to determine if this method could discriminate between medial osteoarthritic and asymptomatic knees during gait. Nine patients with osteoarthritic knees and nine asymptomatic control subjects were included in this study. Eighteen parameters representing maximal, minimal, and range of acceleration values were extracted during the loading and preswing to mid-swing phase periods, and were compared in both groups. Results show good discriminative capacity of the new method. Eight parameters were significantly different between both groups. The proposed method has the potential to be used in comprehending and monitoring gait strategy in patients with osteoarthritic knee. Index Terms--Accelerometer and gyroscope, biomechanics, exoskeleton, gait analysis, internal and external accelerations, knee osteoarthritis (OA).

The aim of this work is to develop an automatic computer method to distinguish between asymptomatic (AS) and osteoarthritis (OA) knee gait patterns using 3-D ground reaction force (GRF) measurements. GRF features are first extracted from the force vector variations as a function of time and then classified by the nearest neighbor rule. We investigated two different features: the coefficients of a polynomial expansion and the coefficients of a wavelet decomposition. We also analyzed the impact of each GRF component (vertical, anteroposterior, and medial lateral) on classification. The best discrimination rate (91%) was achieved with the wavelet decomposition using the anteroposterior and the medial lateral components. These results demonstrate the validity of the representation and the classifier for automatic classification of AS and OA knee gait patterns. They also highlight the relevance of the anteroposterior and medial lateral force components in gait pattern classification. Index Terms--Gait pattern, nearest neighbor classifier (NNC), osteoarthritis knee (OA), polynomial expansion, 3-D ground reaction forces (GRF), wavelet decomposition.