Vol.10 (2020) No. 2 ISSN: 2088-5334 Knee Joint Angle Measuring Portable Embedded System based on Inertial Measurement Units for Gait Analysis Dagoberto Mayorca-Torres a,b , Julio C. Caicedo-Eraso b , Diego H. Peluffo-Ordóñez c,d a Facultad de Ingeniería, Universidad Mariana, Pasto (Nariño), 520001, Colombia E-mail: gomay1069@gmail.com b Facultad de Ingeniería, Universidad de Caldas, Manizales (Caldas), 170001, Colombia E-mail: julioc.caicedo@ucaldas.edu.co c Escuela de Ciencias Matemáticas y Computacionales , Yachay Tech, San Miguel (Urcuquí), 100650, Ecuador E-mail: dpeluffo@yachaytech.edu.ec d Ingeniería Informática , Corporación Universitaria Autónoma de Nariño (Pasto), 520001, Colombia E-mail: diegohpo@gmail.com Abstract— Inside clinical research, gait analysis is a fundamental part of the functional evaluation of the human body's movement. Its evaluation has been carried out through different methods and tools, which allow early diagnosis of diseases, and monitoring and assessing the effectiveness of therapeutic plans applied to patients for rehabilitation. The observational method is one of the most used in specialized centers in Colombia; however, to avoid any possible errors associated with the subjectivity observation, technological tools that provide quantitative data can support this method. This paper deals with the methodological process for developing a computational tool and hardware device for the analysis of gait, specifically on articular kinematics of the knee. This work develops a prototype based on the fusion of inertial measurement units (IMU) data as an alternative for the attenuation of errors associated with each of these technologies. A videogrammetry technique measured the same human gait patterns to validate the proposed system, in terms of accuracy and repeatability of the recorded data. Results showed that the developed prototype successfully captured the knee- joint angles of the flexion-extension motions with high consistency and accuracy in with the measurements obtained from the videogrammetry technique. Statistical analysis (ICC and RMSE) exhibited a high correlation between the two systems for the measures of the joint angles. These results suggest the possibility of using an IMU-based prototype in realistic scenarios for accurately tracking a patient’s knee-joint kinematics during a human gait. Keywords— IMU; gait analysis; motion analysis; knee-joint angle; kalman filter. I. INTRODUCTION Human gait can be described as a sequence of events that occur rhythmically, that is, a repetitive pattern that allows the locomotion by combining several activities from the brain, nerves, and muscles. Gait analysis offers an opportunity for clinical evaluation of the act of walking and may reveal physical and psychological characteristics [1]– [4]. Observational gait analysis is an acquired skill that requires much practice and repetition. The process is complex and difficult because the physical therapist must learn how to look at the different body's joints while simultaneously compares the observed gait with normal gait features in three body planes (sagittal, frontal, and transversal) [5]. In effect, biomechanics gait data from knee joints are collected by laboratories using different technologies and instrumentation, such as [6], [7]. Moreover, it is possible to employ kinematics of rigid bodies for calculating the knee joint angle coming from the relative movement between the knee segments of the tibia and the femur [8], [9]. The data are reported in two-dimensional charts, where the abscissa defines the percentage of the gait cycle (GC), i.e., the time interval from heel contact of one foot to the next heel contact of the same foot, meanwhile the ordinate corresponds to the biomechanical measure of interest, that is, the knee-joint angle [10]. Gait analysis is commonly used to describe and identify normal gait but also to discover abnormal gait patterns [11], [12].The motion capture (MOCAP) system is one of the most used methods for gait analysis. It digitally records the 430