Nikola Jorgovanovic

A multi-pad electrode based functional electrical stimulation system for restoration of grasp

BackgroundFunctional electrical stimulation (FES) applied via transcutaneous electrodes is a common rehabilitation technique for assisting grasp in patients with central nervous system lesions. To improve the stimulation effectiveness of conventional FES, we introduce multi-pad electrodes and a new stimulation paradigm.MethodsThe new FES system comprises an electrode composed of small pads that can be activated individually. This electrode allows the targeting of motoneurons that activate synergistic muscles and produce a functional movement. The new stimulation paradigm allows asynchronous activation of motoneurons and provides controlled spatial distribution of the electrical charge that is delivered to the motoneurons. We developed an automated technique for the determination of the preferred electrode based on a cost function that considers the required movement of the fingers and the stabilization of the wrist joint. The data used within the cost function come from a sensorized garment that is easy to implement and does not require calibration. The design of the system also includes the possibility for fine-tuning and adaptation with a manually controllable interface.ResultsThe device was tested on three stroke patients. The results show that the multi-pad electrodes provide the desired level of selectivity and can be used for generating a functional grasp. The results also show that the procedure, when performed on a specific user, results in the preferred electrode configuration characteristics for that patient. The findings from this study are of importance for the application of transcutaneous stimulation in the clinical and home environments.

Virtual Grasping: Closed-Loop Force Control Using Electrotactile Feedback

Closing the control loop by providing somatosensory feedback to the user of a prosthesis is a well-known, long standing challenge in the field of prosthetics. Various approaches have been investigated for feedback restoration, ranging from direct neural stimulation to noninvasive sensory substitution methods. Although there are many studies presenting closed-loop systems, only a few of them objectively evaluated the closed-loop performance, mostly using vibrotactile stimulation. Importantly, the conclusions about the utility of the feedback were partly contradictory. The goal of the current study was to systematically investigate the capability of human subjects to control grasping force in closed loop using electrotactile feedback. We have developed a realistic experimental setup for virtual grasping, which operated in real time, included a set of real life objects, as well as a graphical and dynamical model of the prosthesis. We have used the setup to test 10 healthy, able bodied subjects to investigate the role of training, feedback and feedforward control, robustness of the closed loop, and the ability of the human subjects to generalize the control to previously “unseen” objects. Overall, the outcomes of this study are very optimistic with regard to the benefits of feedback and reveal various, practically relevant, aspects of closed-loop control.

Quantification of dynamic EMG patterns during gait in children with cerebral palsy.

Our goal was to simplify the representation and interpretation of surface electromyographic (EMG) activity during gait to develop a clinical method for evaluating gait disabilities in children with cerebral palsy (CP). EMG was recorded from four muscles of a lower extremity. Gait cycles were tracked from one force-sensing resistor signal that was recorded synchronously with EMG. The method is based on the comparison of a patients dynamic EMG envelope shapes and the normative gait-related patterns (norms). Developed norms were based on EMG data obtained in 10 healthy children. Due to newly introduced techniques for time and amplitude normalization, norms were developed regardless of differences in subject age, gender, basic gait parameters and the EMG measurement process. The proposed gait metric quantifies the similarity between a patients gait-related patterns and norms by a single global value suitable for gait analysis in general, including a detailed analysis using the 10 partial values. The gait metric was experimentally validated with a control group of healthy children and a group of children with CP with different degrees of motor deficits. Gait metric values obtained in children from the control group are high for all muscles, which means that gait-related patterns are close to norms, whereas in children with CP the higher the degree of motor deficit, the lower the gait metric values. The method could be a very useful clinical tool for the recognition and tracking of motor disorders of the lower extremities in children with CP as well as many other neuromotor pathologies.

Application of Neural Network for Automatic Classification of Leukocytes

Differential blood count is one of the most frequently used diagnostic methods in medicine. An algorithm for leukocytes classification represents the crucial part of any device for the automatic compilation of a differential blood count. This paper demonstrates a new algorithm for the automatic classification of leukocytes based on neural networks and digital image processing. The results of the algorithm testing show a high sensitivity of the algorithm in leukocyte detection, as well as classification accuracy of 86%

Soft sensor for real-time cement fineness estimation.

This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development.

Dyadic Wavelets for Real-time Heart Rate Monitoring

We developed the new intelligent virtual ECG device by integrating the dyadic wavelet (DyWT) based algorithm for QRS complex detection into the virtual teleECG. The new virtual instrument (VI) was realized by using LabVIEW software. The system allows real-time detection of the heart rhythm, offline analysis of the previously recorded signals or offline analysis when using the system via Internet. The new system allows the physician to locate and recognize life threatening events in ECG recordings and provides the patient with an ECG alarm system. The tests on data from a MIT-BIH database show that the DyWT based detector detects accurately 99.53% of QRS complexes, and similarly better than 99% for the clinical recordings. The analysis in clinical environment showed that in ECG signals comprising a sharp and large T wave the algorithm must be fine tuned, otherwise it could result with classifying the T wave as the R peak

Assisting Humans with Special Needs: Curriculum for HUman-TOol Interaction Network - HUTON

The arising field of biomedical engineering is becoming more popular worldwide. TEMPUS project ”Assisting humans with special needs: Curriculum for HUman-TOol interaction Network - HUTON” has a goal to provide new curriculum and necessary equipment for three universities in Serbia, as well as to establish a collaboration between nine partners involved in project from four countries (Serbia, Slovenia, Greece and Italy) for future research in the field of mechatronic in medical rehabilitation. This is of great importance for institutions in Serbia to be recognized and introduced to EU scientific community.