Hand acceleration measurement by Kinect for rehabilitation applications

Abstract

Abstract. A ordable motion sensors that are recently developed for video gaming have formed a budding line of research in the eld of physical rehabilitation. These sensors have been used in many task-based applications to analyze the patients' status based on their completion of assigned tasks. However, as the accuracy of such sensors is lower than that of the clinical ones, their measured data has had very limited use in quantitative motion analysis to this date. The aim of this article is to determine Kinect's ability and accuracy in calculating higher-order kinematic parameters, such as velocity and acceleration, in hand movements. Four methods, i.e. moving average, Butterworth lter, B-spline, and Kalman lter, were proposed to calculate velocity and acceleration from Kinect's raw position data. The results were experimentally compared with two established motion capture systems, i.e. Vicon and Xsens, to analyze the strengths and weaknesses of each method. The results show that B-spline is the best method for calculating velocity and acceleration from Kinect's position data. Using this method, these parameters can be measured with an acceptable accuracy.

Determining accurate hand positions in three-dimensional space using twin-axis electrogoniometer sensors

“…There is a diversity of measurement systems for determining the position which vary substantially according to their cost, accuracy, working space and lifetime, such as bodyposition sensors such as inertial measurement units (IMU) and optical tracking systems [5]. Microsoft Kinect, which was developed for video gaming can also be used for position sensing [6], but the accuracy of its sensor is low compared to clinical sensors [7]. However, each of these sensors suffers from specific disadvantages.…”

Knee Joint Angle Measuring Portable Embedded System based on Inertial Measurement Units for Gait Analysis

“…This can generate inaccuracies when estimating parameters such as speed and acceleration. Therefore, it is necessary to develop methods to reduce noise, among them, Butterworth low pass filter [24], [25] and Kalman filter [7], [26]- [31] are the most used. Tannous et al [32] incorporate IMU sensors in joint rotation axes to measure ankle and knee accelerations.…”