Kvantitativna i kvalitativna procena obrasca hoda kod bolesnika sa Parkinsonovom bolešću

Background/Aim. Postural impairments and gait disorders in Parkinson's disease (PD) affect limits of stability, impaire postural adjustment, and evoke poor responses to perturbation. In the later stage of the disease, some patients can suffer from episodic features such as freezing of gait (FOG). Objective gait assessment and monitoring progress of the disease can give clinicians and therapist important information about changes in gait pattern and potential gait deviations, in order to prevent concomitant falls. The aim of this study was to propose a method for identification of freezing episodes and gait disturbances in patients with PD. A wireless inertial sensor system can be used to provide follow-up of the treatment effects or progress of the disease. Methods. The system is simple for mounting a subject, comfortable, simple for installing and recording, reliable and provides high-quality sensor data. A total of 12 patients were recorded and tested. Software calculates various gait parameters that could be estimated. User friendly visual tool provides information about changes in gait characteristics, either in a form of spectrogram or by observing spatiotemporal parameters. Based on these parameters, the algorithm performs classification of strides and identification of FOG types. Results. The described stride classification was merged with an algorithm for stride reconstruction resulting in a useful graphical tool that allows clinicians to inspect and analyze subject's movements. Conclusion. The described gait assessment system can be used for detection and categorization of gait disturbances by applying rule-based classification based on stride length, stride time, and frequency of the shank segment movements. The method provides an valuable graphical interface which is easy to interpret and provides clinicians and therapists with valuable information regarding the temporal changes in gait.Uvod/Cilj. Poremećaji hoda i ravnoteže kod bolesnika sa Parkinsonovom bolešću (PD) uključuju i poremećaje stabilnosti, održavanja ravnoteže prilikom hoda i nemogućnost adekvatne reakcije na iznenadne perturbacije. U kasnijim fazama bolesti neki bolesnici razvijaju i epizode motornog bloka, odnosno 'frizing' tokom hoda. Objektivno praćenje i merenje karakteristika hoda i promena obrasca hoda tokom progresije bolesti mogu pomoći kliničarima jer ukazuju na promene koje bi dovele do padova i ugrozile bolesnika. Cilj rada bio je razvoj metode koja bi identifikovala ovakve epizode kod bolesnika sa Parkinsonovom bolesti. Razvijeni bežični sistem sa senzorima mogao bi se koristiti za posmatranje efekata terapije ili progresije bolesti. Metode. U radu je prikazan sistem za objektivnu procenu obrasca hoda. Korišćenjem bežičnog senzorskog sistema koji koristi akcelerometre, žiroskope i senzore sile, moguće je dobiti procenu parametara hoda, ali i identifikovati 'frizing' epizode karakteristične za PD. Uz pomoć ovog sistema snimljeno je 12 bolesnika, te je na osnovu snimljenih signala razvijen novi softverski alat koji omogućava praćenje parametara hoda. Rezultati. Na osnovu dužine koraka, trajanja koraka i frekvencije pokreta, razvijen je algoritam za klasifikaciju tipova koraka i uočavanje promena frekvencija pokreta tokom hoda. Prikaz rezultata ovog sistema je dat kroz primer jednog bolesnika. Zaključak. Opisani sistem za procenu hoda može biti korišćen za kategorizaciju poremećaja hoda kroz posmatranje promena u dužini i trajanju koraka, kao i frekvencija segmenata noge. Razvijeni metod omogućava iliustrativni prikaz i grafički interfejs koji je jednostavan za interpretaciju i omogućava dobijanje informacija koje kliničarima mogu ukazati na trenutne promene u obrascu hoda

Wireless distributed functional electrical stimulation system

<p>Abstract</p> <p>Background</p> <p>The 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>The 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.</p> <p>Conclusions</p> <p>The 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.</p

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 Parkinson's 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 proposedmethod is based on processing of data obtained from an inertial sensor mounted on shank. The algorithm separates normal from abnormal gait using Pearson's 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

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

The gait disturbances in Parkinson's 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%

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

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

Implementation of continuous wavelet transformation in repetitive finger tapping analysis for patients with PD

In this paper we propose a methodology for objective evaluation and classification of repetitive finger tapping performance based solely on its spectral behavior. We used miniature sensor system with gyroscope placed over fingertip of index finger for finger tapping recording. The study included 20 subjects 10 patients with Parkinson's disease (PD) and 10 age and gender matched healthy controls. Acquired data were preprocessed using continuous wavelet transformation (CWT), and their coefficients were used in further analysis. Based on cross-sections of CWT in time and frequency, we introduced parameters describing characteristic tapping frequencies and vigor of the performed movements, its decrement and isolated characteristic frequency areas. These parameters were further used in classification for distinction between PD patients and controls, achieving 95% classification accuracy

A Demonstration Project for the Utility of Kinect-Based Educational Games to Benefit Motor Skills of Children with ASD

Motor disorders often accompany autism spectrum disorder (ASD), although they are not included in its diagnostic criteria. Slower motor development is evident in early childhood in this population, making early motor skills intervention advisable. As educational games and modern technology can represent new forms of treatment, this study evaluated four Kinect-based visuo-motor games called Fruits that were specially designed for this research. We sought to test whether children with ASD would show behavior changes during their game play and whether any effects would generalize to another game called Rackets. The study included 10 elementary school children with ASD, aged 9-13 years, who were divided into (a) an experimental group (n = 5) who, in addition to standard treatment, played Fruits once a week for a 5-week period and Rackets both before and after the 5-week period and (b) a control group (n = 5) who received only standard treatment during this period and also played Rackets before and after it. We found significant improvements in gross motor skills and successful generalization of acquired skills among children in the experimental group relative to the control group. The experimental group also showed an increase in positive emotions and a decrease in loss of attention while playing the games. These preliminary findings indicate a motor skill benefit for children with ASD who play Kinect-based educational games, but further research is needed to replicate and expand these findings with larger participant samples