Measurement of Human Gait Symmetry using Body Surface Normals Extracted from Depth Maps.

In this paper, we introduce an approach for measuring human gait symmetry where the input is a sequence of depth maps of subject walking on a treadmill. Body surface normals are used to describe 3D information of the walking subject in each frame. Two different schemes for embedding the temporal factor into a symmetry index are proposed. Experiments on the whole body, as well as the lower limbs, were also considered to assess the usefulness of upper body information in this task. The potential of our method was demonstrated with a dataset of 97,200 depth maps of nine different walking gaits. An ROC analysis for abnormal gait detection gave the best result ( AUC = 0.958 ) compared with other related studies. The experimental results provided by our method confirm the contribution of upper body in gait analysis as well as the reliability of approximating average gait symmetry index without explicitly considering individual gait cycles for asymmetry detection.

Human gait symmetry assessment using a depth camera and mirrors.

It is proposed in this paper a reliable approach for human gait symmetry assessment using a Time-of-Flight (ToF) depth camera and two mirrors. The setup formed from these devices provides a sequence of 3D point clouds that is the input of our system. A cylindrical histogram is estimated for describing the posture in each point cloud. The sequence of such histograms is then separated into two sequences of sub-histograms representing two half-bodies. A cross-correlation technique is finally applied to provide values describing gait symmetry indices. The evaluation was performed on 9 different gait types to demonstrate the ability of our approach in assessing gait symmetry. A comparison between our system and related methods, that employ different input data types, is also provided.

Skeleton-Based Abnormal Gait Detection.

Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%.

Population pharmacokinetic and pharmacodynamic modeling of acetazolamide in peritoneal dialysis patients and healthy volunteers.

PURPOSE: To characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of acetazolamide (ACTZ) in peritoneal dialysis patients, ACTZ 500 mg was administered intravenously to 7 healthy subjects (HV) and 8 peritoneal dialysis patients (CAPD). METHODS: Population PK/PD modeling was performed with ACTZ serum (total and unbound), urine and dialysate concentrations, intra-ocular pressure (IOP) and covariates. A multi-compartment PK model (accounting for non-linear protein binding) and an inhibitory Emax (maximal change in IOP) PD model were selected. RESULTS: As expected, renal clearance (which almost equals total body clearance) was severely decreased in CAPD (1.2 vs 80.3 L/h) and the elimination half-life of total ACTZ was prolonged (20.6 vs 3.4 hours). The protein binding was significantly altered with a mean free fraction 4.2% in HV and 8.6% in CAPD. Moreover protein binding of ACTZ was concentration dependent in both HV and CAPD. Despite a higher free fraction of ACTZ, the Emax was lower in CAPD: 4.4±1.4 vs 7.4±2.8 mmHg. CONCLUSION: Both PK and PD are significantly altered in dialysis patients.