Nenad S. Jovicic

Kinematics of Gait: New Method for Angle Estimation Based on Accelerometers

A new method for estimation of angles of leg segments and joints, which uses accelerometer arrays attached to body segments, is described. An array consists of two accelerometers mounted on a rigid rod. The absolute angle of each body segment was determined by band pass filtering of the differences between signals from parallel axes from two accelerometers mounted on the same rod. Joint angles were evaluated by subtracting absolute angles of the neighboring segments. This method eliminates the need for double integration as well as the drift typical for double integration. The efficiency of the algorithm is illustrated by experimental results involving healthy subjects who walked on a treadmill at various speeds, ranging between 0.15 m/s and 2.0 m/s. The validation was performed by comparing the estimated joint angles with the joint angles measured with flexible goniometers. The discrepancies were assessed by the differences between the two sets of data (obtained to be below 6 degrees) and by the Pearson correlation coefficient (greater than 0.97 for the knee angle and greater than 0.85 for the ankle angle).

Automatic Identification and Classification of Freezing of Gait Episodes in Parkinson's Disease Patients

Alternation of walking pattern decreases quality of life and may result in falls and injuries. Freezing of gait (FOG) in Parkinsons disease (PD) patients occurs occasionally and intermittently, appearing in a random, inexplicable manner. In order to detect typical disturbances during walking, we designed an expert system for automatic classification of various gait patterns. The proposed method is based on processing of data obtained from an inertial sensor mounted on shank. The algorithm separates normal from abnormal gait using Pearsons correlation and describes each stride by duration, shank displacement, and spectral components. A rule-based data processing classifies strides as normal, short (short+) or very short (short-) strides, FOG with tremor (FOG+) or FOG with complete motor block (FOG-). The algorithm also distinguishes between straight and turning strides. In 12 PD patients, FOG+ and FOG- were identified correctly in 100% of strides, while normal strides were recognized in 95% of cases. Short+ and short- strides were identified in about 84% and 78%. Turning strides were correctly identified in 88% of cases. The proposed method may be used as an expert system for detailed stride classification, providing warning for severe FOG episodes and near-fall situations.

Wireless distributed functional electrical stimulation system

BackgroundThe control of movement in humans is hierarchical and distributed and uses feedback. An assistive system could be best integrated into the therapy of a human with a central nervous system lesion if the system is controlled in a similar manner. Here, we present a novel wireless architecture and routing protocol for a distributed functional electrical stimulation system that enables control of movement.MethodsThe new system comprises a set of miniature battery-powered devices with stimulating and sensing functionality mounted on the body of the subject. The devices communicate wirelessly with one coordinator device, which is connected to a host computer. The control algorithm runs on the computer in open- or closed-loop form. A prototype of the system was designed using commercial, off-the-shelf components. The propagation characteristics of electromagnetic waves and the distributed nature of the system were considered during the development of a two-hop routing protocol, which was implemented in the prototype’s software.ResultsThe outcomes of this research include a novel system architecture and routing protocol and a functional prototype based on commercial, off-the-shelf components. A proof-of-concept study was performed on a hemiplegic subject with paresis of the right arm. The subject was tasked with generating a fully functional palmar grasp (closing of the fingers). One node was used to provide this movement, while a second node controlled the activation of extensor muscles to eliminate undesired wrist flexion. The system was tested with the open- and closed-loop control algorithms.ConclusionsThe system fulfilled technical and application requirements. The novel communication protocol enabled reliable real-time use of the system in both closed- and open-loop forms. The testing on a patient showed that the multi-node system could operate effectively to generate functional movement.

Classification of walking patterns in Parkinson's disease patients based on inertial sensor data

The gait disturbances in Parkinsons disease (PD) patients occur occasionally and intermittently, appearing in a random, inexplicable manner. These disturbances include festinations, shuffling, and complete freezing of gait (FOG). Alternation of walking pattern decreases the quality of life and may result in falls. In order to recognize disturbances during walking in PD patients, we recorded gait kinematics with wireless inertial measurement system and designed an algorithm for automatic recognition and classification of walking patterns. The algorithm combines a perceptron neural network with simple signal processing and rule-based classification. In parallel, gait was recorded with video camera. Medical experts identified FOG episodes from videos and their results were used for comparison and validation of this method. The summary result shows that the error in recognition and classification of walking patterns is up to 16%.

Nonlinear optimization for drift removal in estimation of gait kinematics based on accelerometers

A new data processing method is described for estimation of angles of leg segments, joint angles, and trajectories in the sagittal plane from data recorded by sensors units mounted at the lateral side of leg segments. Each sensor unit comprises a pair of three-dimensional accelerometers which send data wirelessly to a PC. The accelerometer signals comprise time-varying and temperature-dependent offset, which leads to drift and diverged signals after integration. The key features of the proposed method are to model the offset by a slowly varying function of time (a cubic spline polynomial) and evaluate the polynomial coefficients by nonlinear numerical simplex optimization with the goal to reduce the drift in processed signals (angles and movement displacements). The angles and trajectories estimated by our method were compared with angles measured by an optical motion capture system. The comparison shows that the errors for angles (rms) were below 4° and the errors in stride length were below 2%. The algorithm developed is applicable for real-time and off-line analysis of gait. The method does not need any adaptation with respect to gait velocity or individuality of gait.

Signal acquisition and processing in the magnetic defectoscopy of steel wire ropes

The system that resolves the problem of wire rope defects using magnetic method of inspection is presented. Implementation of the system should provide for full monitoring of wire rope condition, according to the prescribed international standards. The purpose of this system, except to identify defects in the rope, is to determine to what extent the damage has been done. The measurement procedure provides for a better understanding of the defects that occur, as well as the rejection criteria of used ropes, that way increasing their security. Hardware and software design of appliance for recording defects and test results are presented in this paper.

Reproducibility of “BUDA” multisensor system for gait analysis

Gait analysis is important element in therapy and rehabilitation of hemiplegic individuals. We developed a simple, portable sensor system, which can be used for recording of gait signals, as well as for estimation of important gait parameters like joint angles, ground reaction forces, and various temporal parameters. In order to assess robustness of the system in everyday use in different environmental conditions and to see how it reacts to atypical gait patterns, we recorded signals from five healthy and five hemiplegic subjects, repeating the experiment on several consecutive days. We compared angles between adjacent leg segments and used Pearsons correlation coefficient as a measure of similarity. We obtained a high correlation for healthy persons, and a notably smaller correlation for hemiplegics.

Quantification of Finger-Tapping Angle Based on Wearable Sensors

We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns. The obtained tapping angles were compared with results of a motion capture camera system, demonstrating excellent accuracy. The root-mean-square (RMS) error between the two sets of data is, on average, below 4°, and the intraclass correlation coefficient is, on average, greater than 0.972. Data obtained by the proposed method may be used together with scores from clinical tests to enable a better diagnostic. Along with hardware simplicity, this makes the proposed method a promising candidate for use in clinical practice. Furthermore, our definition of the tapping angle can be applied to all tapping assessment systems.

The capacitive divider power supply and its design problem

Capacitive divider power supply is a well-known circuit. Still, it has not been paid attention to among researchers and is still lacking a thorough analysis and referred optimal design guidelines. We give the formal time-domain equations describing the behavior of the supply, as well as the estimation for the circuits dissipation, that will be used as a foundation for a further research.

New generation of assistive systems for humans with disability: New tool for neurorehabilitation

In this paper we are discussing the “pacemakers” for cyclic and goal directed movements in humans with central nervous systems injury/disease that are based on electrical stimulation. The system that restores or augments movement is termed Motor Neural Prosthesis (MNP). The novelties needed to make MNP compatible with the richness of living systems must be based on better understanding of the effects of electrical stimulation to the complete neural network (peripheral and central nervous system) and the design that can mimic the operation of the natural system. The novelties that we are discussing are related to the following facts: 1) electrical stimulation activates both afferent and efferent pathways, 2) external (artificial) control should match the natural (biological) control, 3) sensors system needs to ensure the application of predictive automatic adaptation to perturbations from the target trajectories, and 4) systems should minimize nonphysiological effects of application of electrical stimulation leading to tissue changes and fatigue. Other issues that hinder the current applicability of MNP relate to the technical aspects (e.g., power source, connectors, miniaturization, biocompatibility), but they are more likely to be resolved in the nearest future due to fast development of micro and nano technologies.