<p>The early-stage of knee osteoarthritis (OA) is usually asymptomatic. However, timely detection of osteoarthritis can prevent further cartilage degeneration <i>via</i> appropriate exercise prescription and behavioral change. In this article, a noninvasive method to diagnose the OA of a knee recording the knee vibroarthrographic (VAG) signals over the mid-patella during the standing movement is proposed. A method that combines empirical mode decomposition (EMD) and wavelet transform is developed to analyze the nonstationary VAG signals. The least squares support vector machine algorithm (LSSVM) that is a type of support vector machine is used to classify the knee joint VAG signals (26 normal and 25 abnormal) collected from healthy subjects and patients suffering from the knee OA using the Kellgren and Lawrence grading system III and IV (KLGS III and IV). The LSSVM classifier achieves an accuracy of 86.67% in differentiating the normal and abnormal subjects that proves the effectiveness of the autocorrelation function features and continuous wavelet transform (CWT) features. Therefore, the VAG signals can be clinically significant for the classification of healthy and OA subjects.</p> <div style="text-align:center;"> </div>

Keywords

Osteoarthritis (OA), Vibroarthrographic (VAG), Empirical Mode Decomposition (EMD), Wavelet transform, Least Squares Support Vector Machine Algorithm (LSSVM)

Paper information

Rui GONG, Kazunori HASE, Hiroaki GOTO, Keisuke YOSHIOKA, Susumu OTA, “Knee osteoarthritis detection based on the combination of empirical mode decomposition and wavelet analysis”, Journal of Biomechanical Science and Engineering, Vol.15, No.3 (2020), p.20-00017. doi:10.1299/jbse.20-00017. Final Version Released on July 24, 2020, Advance Publication Released on April 09, 2020.

Sports prosthesis for lower-extremity amputees has a mechanical structure similar to flat springs, and its elastic energy is expected to improve sports performance. However, it is quite challenging to represent the mechanical phenomena during the takeoff action with sports prosthesis because the contact point to the ground moves based on the direction and deformation of the prosthesis. The purpose of this study is to propose a parametric model of sports prosthesis based on the flat spring design formulas to represent the deformation and rolling contact with the ground with a reasonable computational cost. The shape of the prosthesis is modeled as serial elements, and it can easily be changed by using design parameters, such as the curvature and length of each element. The curvature of each element of the prosthesis is modified by the deflection angle of the flat spring model, and the contact point to the ground is calculated by considering the deformation and rolling contact. The spring properties obtained from the proposed model well agreed with the result of a finite element analysis. Moreover, simulation results revealed that the deformed shape of the prosthesis and the takeoff action in the long jump qualitatively agreed with the actual phenomena. As future research, the proposed model, coupled with the human body model, will be applied to a computer simulation system to optimize the shape of the prosthesis in order to improve sports performance.

Keywords

Human dynamics, Simulation, Rolling contact, Ground reaction force, Long jump

Paper information

Kazunori HASE, Hiroto TOGAWA, Satoshi KOBAYASHI, Goro OBINATA, “Parametric modeling of sports prostheses based on the flat spring design formulas”, Journal of Biomechanical Science and Engineering, Vol.15, No.1 (2020), p.19-00446. doi:10.1299/jbse.19-00446. Final Version Released on March 27, 2020, Advance Publication Released on December 19, 2019.

In this paper, we analyze the influence of dynamical characteristics of man-machine interfaces on both impedance perception levels and motor control characteristics of humans. In order to estimate dynamical characteristics of man-machine interfaces, humans make use of the coupling characteristics between sensory systems and motor systems in their bodies. In this study, we propose a new model-based estimation method of impedance perception level of related with motor control characteristics of the body. For the experiment, we used a 6 degree-of-freedom manipulator to simulate different impedances. A dual task was imposed on the subjects along with measuring dynamic characteristics of human who are operating the manipulator, where subjects were asked to perform simultaneously an upper limb tracking task and an impedance perception task. Based on the experimental results that show proportional relation between the differences of impedance perception levels and changes of the gain characteristics of the motor control transfer function model, the power spectrum density of the developed human model can be applied for on-line estimation of the impedance perception level of human in man-machine interface. The effectiveness of the proposed method is verified through comparison with subjective evaluation results.

Keywords

Human Motor Control System, Closed Loop Identification, Man-Machine Interface, Impedance Perception Characteristics

Paper information

Youngwoo KIM, Keiichi ONISH, Goro OBINATA and Kazunori HASE, “Model-based Analysis of Impedance Perception Related with Motor Control System”, Journal of Biomechanical Science and Engineering, Vol. 7, No. 2 (2012), pp.259-274 . doi:10.1299/jbse.7.259

We propose a method for the comprehensive identification of spastic and intrinsic properties of spastic knee joints using multiple pendulum tests. The stretch reflex system was modeled as a velocity feedback loop where the key component was the muscle spindle model generating the afferent signals with a constant threshold and gain of the lengthening velocity. For the comprehensive identification, multiple trajectories from one session of pendulum trials with different release angles were used as the reference trajectories that the model must reproduce. The identification was successful based on the results that the identified model represented the various features of pendulum trajectories and the simulated spastic torque closely matched the experimental EMG. The identified velocity threshold showed a remarkable correlation with the EMG duration and peak. The session-based method was effective in the identification of the spastic musculoskeletal system and the velocity threshold of the stretch reflex was suggested as a reliable and intuitive indicator of spastic severity.

Keywords

Spasticity, Pendulum Test, Identification, Stretch Reflex, Mechanical Properties

Paper information

Chul-Seung KIM, Gwang-Moon EOM and Kazunori HASE, “Modeling and Identification of Mechanical and Reflex Properties related to Spasticity in Stroke Patients using Multiple Pendulum Tests”, Journal of Biomechanical Science and Engineering, Vol. 6, No. 3 (2011), pp.135-147 . doi:10.1299/jbse.6.135