Erkan Kaplanoglu

Design of Shape Memory Alloy-Based and Tendon-Driven Actuated Fingers towards a Hybrid Anthropomorphic Prosthetic Hand

This paper presents the design of tendon-driven actuated fingers using a shape memory alloy for a hybrid anthropomorphic prosthetic hand. The ring and little (pinky) fingers are selected for shape ...

24 DOF EMG controlled hybrid actuated prosthetic hand

A complete mechanical design concept of an electromyogram (EMG) controlled hybrid prosthetic hand, with 24 degree of freedom (DOF) anthropomorphic structure is presented. Brushless DC motors along with Shape Memory Alloy (SMA) actuators are used to achieve dexterous functionality. An 8 channel EMG is used for detecting 7 basic hand gestures for control purposes. The prosthetic hand will be integrated with the Neural Network (NNE) based controller in the next phase of the study.

Characterization of a bend sensor for neuroprosthetic applications

In this study, the static characterization of a bend sensor which is commonly used for various applications was performed. Electrical properties of the sensor was measured and analyzed on a robotic hand. Thus, the feasibility of the sensor for neuroprosthetic applications was discussed. The mean coefficient of determination (R2) is 0.98 and the mean hysteresis value is 9.1 %. The joint angles on a robotic hand were estimated, but the results were different from the actual values because of the sensor placement method.

SMA actuated prosthetic finger design

The proposed work will cover a mechanical design that imitates natural shape and posture of anatomic finger and design of Shape Memory Alloy (SMA) actuators that mimics natural functions of a finger. The best mechanical finger design lies in imitating the complex structure (anatomy) of the human finger with all its bones, joints, muscles, tendons and their connections as close as possible. At this point shape memory alloys are good potential with its muscle like working principles, SMA actuators are placed on phalanges to provide finger movements.

Real‐Time Parameter Estimation Method Applied to a MIMO Process and its Comparison with an Offline Identification Method

An experiment based method is proposed for parameter estimation of a class of linear multivariable systems. The method was applied to a pressure‐level control process. Experimental time domain input/output data was utilized in a gray‐box modeling approach. Prior knowledge of the form of the system transfer function matrix elements is assumed to be known. Continuous‐time system transfer function matrix parameters were estimated in real‐time by the least‐squares method. Simulation results of experimentally determined system transfer function matrix compare very well with the experimental results. For comparison and as an alternative to the proposed real‐time estimation method, we also implemented an offline identification method using artificial neural networks and obtained fairly good results. The proposed methods can be implemented conveniently on a desktop PC equipped with a data acquisition board for parameter estimation of moderately complex linear multivariable systems.

Evaluation of Sensory Feedback from a Robotic Hand: A Preliminary Study

In this study, a robotic hand was equipped with force and bend sensors. Sensors were modified to fit the robotic hand and for more efficient utilization. A cylindrical grasping task was performed for three conditions, namely no object, soft object and hard object. Features were formed using the outputs of the sensors and their first and second derivatives. A multinomial logistic regression model was fitted to the data. Classification was done according to both object type (no object, soft object and hard object classes) and movement type (no movement, flexion, contact/release and extension classes). Results have shown that the information from the force sensors do not adequately contribute to the feature space because of poor coupling and this affects discrimination of soft object and contact/release classes. More sensors and a better actuation protocol need to be used in future work.

Comparative EMG classification of index finger

In this study electromyography (EMG) signals obtained from index finger movements are analysed and classified in two separated methods and results are compared as a pre-study of dexterous anthropomorphic prosthesis hand project. The index finger differs from other hand digits for its tendon structure and higher mobility capabilities. The relation between the EMG signal and movement of the index finger is a key to understanding how the finger performs the tasks such as grasping and postures. Signals are measured from two different muscle groups and classified by grasping and positions. Finite State Machine (FSM) and Artificial Neural Network (ANN) are used for classification. Also the study indicates the effects of signals from index finger motions on a myoelectric controlled prosthetic hand.

Design and Implementation of Web Based Mobile Robot Control Platform for Robotics Education

In this paper, we present a particular case of a dynamic, real-time and efficient web-based mobile robot experiment platform (WEB.MREP) design for mobile robotic applications. The design and construction of a multipurpose and WEB.MREP for the application of different path planning and tracking, simultaneous localization and mapping (SLAM) and robot vision techniques for mobile robotic system is the main purpose of this study. The designed and constructed experiment platform consists of five main components: Festo Robotino mobile robot sets, a designed experimental area, a server software, web interfaces (user interfaces) and security measures. The designed platform provides monitoring, real-time controlling and programming of mobile robots for experimental studies and, it helps the users to achieve these studies through a standard web browser without any additional supportive software.