Wyniki wyszukiwania - BazTech

1

Self-adaptive grey wolf optimization based adaptive fuzzy aided sliding mode control for robotic manipulator

Kalshetti Sunil C., Dixit S. K.

Control and Cybernetics

|

2018

|

Vol. 47, no. 4

383--409

EN

As the robotic manipulators are highly nonlinear, it is a challenging task to design, in particular, the PUMA 560 robotic arm with acceptable performance. This paper intends to show the design and development of an adaptive sliding mode controller (SMC) for a robotic manipulator. Since it is not realistic to match the SMC operations with the system model at every time instant, this paper adopts fuzzy inference to replace the system model. This approach successfully achieves the objectives of the experiment, carried out in two stages. In the first stage, it acquires the precise characteristics of the system model for the diverse samples and adequately represents the robotic manipulator. Subsequently, we derive the acquired characteristics in the form of fuzzy rules. In the second stage, we represent the derived fuzzy rules on the basis on adaptive fuzzy membership functions. Further, the approach introduces the self-adaptiveness into a recent algorithm called Grey Wolf Optimization (GWO) in order to establish the adaptive fuzzy membership functions. We then compare the effectiveness of the proposed method with the identified experimental model and the known methods, like SMC, Fuzzy SMC (FSMC), and GWO-SMC. Finally, the comparison with the known methods establishes the effectiveness of the proposed SAGWO-FSMC technique.

2

Influence of dopaminergic treatment on resting elbow joint angle control mechanisms in patients with Parkinson’s disease – a preliminary report

Marusiak J., Jaskólska A., Budrewicz S., Koszewicz M., Andrzejewska R., Kisiel-Sajewicz K., Jaskólski A.

Acta of Bioengineering and Biomechanics

|

2018

|

Vol. 20, no. 4

75--82

EN

Heightened tonic stretch reflex contributes to increased muscle tone and a more-flexed resting elbow joint angle (EJA) in patients with Parkinson’s disease (PD). Dopaminergic medication restores central nervous system (CNS) functioning and decreases resting muscle electrical and mechanical activities. This study aimed to evaluate the effects of dopaminergic medication on parkinsonian rigidity, resting EJA, resting electrical activity (electromyography, EMG) and mechanical properties (myotonometry, MYO) of elbow flexor muscles and the associations of EJA with these muscles resting electrical activity and mechanical properties in PD patients. We also evaluated a relationship between dopaminergic treatment dose and these outcome measures values. Methods: Ten PD patients (age 68 ± 10.1 years; body mass 70 ± 16.8 kg; height 162 ± 6.6 cm; illness duration 9 ± 4.5 years) were tested during medication on- and off-phases. Resting EJA, myotonometric muscle stiffness (S-MYO) and root mean square electromyogram amplitude (RMS-EMG) were recorded from relaxed biceps brachii and brachioradialis muscles. Based on the above parameters, we also calculated the EJA/S-MYO ratio and EJA/RMS-EMG ratio. Parkinsonian rigidity was assessed using the motor section of the Unified Parkinson’s Disease Rating Scale. Results: EJA, EJA/S-MYO ratio, and EJA/RMS-EMG ratio were increased and S-MYO, RMS-EMG, and parkinsonian rigidity were decreased during the medication on-phase compared with the off-phase. In addition, the dopaminergic treatment dose was negatively correlated with S-MYO and RMS-EMG, and positively correlated with EJA/SMYO and EJA/RMS-EMG ratios. Conclusions: We conclude that dopaminergic medication-induced improvements in resting elbow joint angle in tested patients with PD are related to changes in their muscle electrical and mechanical properties.

3

Artificial neural network simulation of lower limb joint angles in normal and impaired human gait

Błażkiewicz M., Wit A.

Acta of Bioengineering and Biomechanics

|

2018

|

Vol. 20, no. 3

43--49

EN

Simulating the complexities of lower limb motion can be useful for orthosis or rehabilitation planning. The aim of this study was to develop an artificial neural network (ANN) able to accurately simulate the changes in the angle of the ankle, knee and hip joints during the gait cycle, then to use it to simulate the impact of a restricted range of ankle and hip joint angle changes on the progression of the knee joint angle. Methods: Thirty four young healthy students participated in the study. Gait kinematics data were collected using the Vicon system, then analyzed with an ANN. Results: We developed an ANN able to accurately simulate the progression of joint angles of lower-limb motion; its simulation of the impact of restricted ankle and hip joint angular ranges in the on the knee joint indicate that the braking phase is critical. Conclusions: ANNs offer a useful research method in clinical biomechanics. Further research in this vein should expand our understanding of compensatory functions in the lower limbs.

4

Comparison of sensitivity coefficients for joint angle trajectory between normal and pathological gait

Błażkiewicz M., Wit A

Acta of Bioengineering and Biomechanics

|

2012

|

Vol. 14, no. 1

83-91

EN

Gait recordings exhibit intra-subject, inter-subject, within-trial and between-trial variability as well as data analysis methods. In medicine, comparison of different measuring method results or quantifying changes due to specific treatment is required. The aim of this study was to compare a group homogeneity with respect to dispersion around the reference curve and to compare waveforms of normal and pathological gait data based on joint angle curves. Data files were tracked using APAS system. Our own model of lower limb was used to calculate the trajectories of joint angles for 5 groups: healthy men, women, children, persons with drop foot and Trendelenburg's sign. Waveform parameterizations, RMS, IAE and correlation coefficients were used to compare joint angles with reference curve. The sample scores obtained in this work provide an important information about closeness in the shape of two curves. Using multiple techniques of data analysis will benefit and give more accurate information.