Purpose: The biomechanics of the musculoskeletal system in patients after tibial nonunion treatment using the Ilizarov method have not yet been fully explored. From the orthopaedic and patient point of view, after the treatment, an assessment should be carried out of the biomechanics of the musculoskeletal system. The aim of this study was to assess the body balance of patients treated with the Ilizarov method for tibial nonunion. Methods: The research group included 24 individuals with a mean age of 55 years, who were treated for aseptic tibial nonunion with the Ilizarov method. The control group was matched to the study group in terms of gender and age, and consisted of 32 subjects with a mean age of 50.5 years and no significant medical history. This study evaluated the balance of patients with the use of pedobarography. Results: In the control group, a statistically significantly shorter path of centre of gravity was observed. There were no statistical differences between the study and control groups for the field area of the centre of gravity. There were no statistical differences between the study and control groups for the minor axis length or major axis length of the centre of gravity. There was a relationship between the centre of pressure path length and the age of the participants in both the control group and the study group. Conclusions: Treatment of patients with tibial nonunion with the Ilizarov fixator achieves similar balance to healthy volunteers. In the pedobarographic evaluation, patients treated for tibial nonunion using the Ilizarov method had similar statics of the musculoskeletal system to healthy volunteers.
The aim of this study was to establish the reference values of spatiotemporal parameters, joint angles, ground reaction forces and plantar pressure distribution collected simultaneously on the same measurement path during normal gait in a homogenous group of young, healthy women. Methods: The studied group consisted of 28 healthy women aged 21 years on average. The motion capture system BTS Smart-D, 2 AMTI force platforms and Footscan pedobarographic platform were used in this research. The 14-metre measurement path and the 6-metre distance that examined women had to walk through before entering the measurement area ensured that a natural gait pattern was recorded. Statistical analysis was performed to evaluate differences between right and left lower extremities. Results: The applied method enabled collecting several parameters regarding normal female gait biomechanics such as: spatiotemporal parameters, angle-time characteristics as well as range of motion of pelvis, hip, knee and ankle joints in gait cycle, force-time characteristics and peaks of ground reaction force components in stance phase, peak pressure and time of loading of defined foot regions in stance phase. Conclusions: The results may be used by clinicians, physiotherapists or researchers as a reference in diagnosing gait disorders or evaluating patient’s walking pattern. In recent literature there are some disparities in gait parameters reference values even regarding similar research groups. These differences may arise from distinct method, slower or faster gait, other laboratory environment etc. This should be considered and more than one source of normative values should be checked when searching for reference data.
Purpose : Exerting axial pressure on the affected lower limb remains one of the most crucial elements of Ilizarov method . Objective was to determine the effects of an early intrahospital rehabilitation on weight bearing during lower extremity lengthening with Ilizarov`s Method. Methods: Study included 15 patients who underwent lower limb lengthening. The patients were tested on the third day after surgery using the pedobarographic platform. The tests were performed four times in the standing position:twice with the support of forearm crutches and twice without crutches. Patients were asked to either remain in the relaxed standing position(two tests) or use the lower limb equipped with Ilizarov apparatus to support the body weight(two tests). Results: In relaxed stance average pressure with forearm crutches was 24.1% for affected limb, as compared to 75.9% for the healthy limb. In test without forearm crutches average pressure for affected limb was 26.1%, as compared to 73.9% for the healthy limb. Patients shifted body weight to the affected limb with forearm crutches on average, at the rate of 53.6% . In test without forearm crutches the affected limb was supporting the body weight at the rate of 48.26%. None of the patients was able to fully support the body weight on the affected leg. Conclusions: In spite of strict physiotherapy regimen,patients are, neither able to equally distribute their body weight between the two lower limbs ,nor to shift their body weight to the limb equipped with Ilizarov apparatus.
Distortion of the axis and shortening of the limbs result in multiple musculoskeletal pathologies. Rotation disorders should also be included among the disorders of the axis of the lower limb. In the case of rotational distortion, only derotation osteotomy can effectively correct torsion-associated deformations. Rotational distortion correction is accompanied by translational displacement and torsion, which results in more complex biomechanics. Using the pedobarographic platform, it is possible to evaluate static and dynamic posture and gait, percentage of body weight distribution on the lower limbs, and balance. Physiological gait and distribution of weight on the lower extremities are symmetrical. Balance is one of the determinants of proper biomechanics of the musculoskeletal system. An important aspect of treatment evaluation is pedobarographic assessment of balance and body weight distribution on the lower extremities ratio. The aim of this work was to evaluate the pedobarographic assessment of body weight distribution on the lower limbs and balance in patients with derotation corticotomies using the Ilizarov method. The study examined a group of 56 patients, who underwent derotation corticotomy using the Illizarov method between 1996 and 2012 at the Clinic of Orthopaedics and Traumatology of the Musculoskeletal System in Wrocław. The control group consisted of 54 patients, who were treated with correctional derotation-free corticotomy using the Ilizarov. Distribution of body weight on the lower limbs and balance were assessed with the pedobarographic platform. Following derotation corticotomy, the amount of body weight placed on the operated limb by subjects from the study group averaged 47.81%, 52.19% in the case of the healthy limb. These differences were not statistically significant. The difference between the average percentage of body weight placed on the diseased and healthy limb in the study group and the controls were not found to be statistically significant. There were no statistical differences in the average length of the gravity line or in the average surface area of the center of gravity position between the study and control groups. Balanced distribution of body weight on the lower limbs was achieved following derotation corticotomies using the Ilizarov method. Derotation corticotomies performed with the Ilizarov method allow for achieving normalization of body weight distribution on the lower limbs and balance, with values similar to those resulting from Ilizarov method derotation-free osteotomy.
This study was based on observations of 117 patients suffering from motor disturbances. Among them 42 cases with hemiparetic syndrome, majority of them after cerebral stroke, 52 cases affected by acute sciatic neuralgia and 23 patients with recognition of Parkinson - disease symptoms. To the control group 16 healthy adults were selected, from medical staff of clinics. All subjects were examined using pedobarographic equipment - Parotec System for Windows (PSW) [1]. Based on these observations several pattern solutions have been introduced. They concern gait disturbances descriptions in three distinguished neurological diseases. These findings extracted a new data from the PSW records and options with new diagnostic techniques, based on the gait characteristics observation.
The paper concerns the implementation of some diagnostic measures describing gait disturbances produced by neurological diseases. The discussed contribution explains various experiments provided by the authors' works on Parotec System for Windows development [1]. The subject of the investigations was defined by many experiments carried-out at clinics, with gait's characteristic features analysis, involving the fuzzy logic paradigms. The linguistic notations of diagnostic classes are computed dynamically in accordance with disease statistics, provided by the characteristics of the patient under investigation. The comprehensive system was recognised as a friendly user package, which insulates the user from the complex analysis of measures describing the physiological gait characteristic features. What is more, the application has the ability to be tuned more precisely after the data record size has grown. The software-units implementation provided the user with a selftuned system that enriches the application knowledge, during the data acquisition, while the set of the data records is still growing.
The paper concerns the use of diagnostic measures for detection of gait disturbances for neurological pathologies identification. Project of using the PSW (Parotec System for Windows) system for detection of gait's characteristics described by the expert doctor and collected in knowledge base stored using modified Horn's rules with fuzzy linguistic notions was based on several years of experience in implementation and use of the PSW system. Linguistic notions are computed dynamically with use of diagnostic measure distribution of examined population. It makes system more friendly (isolates expert from questions which values of measures describe physiological gait), on the other hand it provides self-tuning of system during acquisition of still growing amount of measurements collected. Condition of correct pathology classification is to obtain proper description of disturbance from an expert and collection of explorations among pathological and physiological population. The best way of tuning the system is to use it for sift research. An implementation of system is currently at the final stage.
The paper describes an analysis of measuring errors that are responsible for not satisfactory conclusion quality. The analysis concerns the PSW (Parotec System for Windows) [1] equipment developed for walking abnormality diagnosis. The paper shows the analysis principles that indicate what kind of faults are acceptable, for an adequate disease classification.
The paper presents main features of computer unit that supports the conclusion making system. The system helps the medical staff in putting diagnosis concerning a foot abnormality recognition and classification. For the data record registration the PSW (Parotec System of Windows) has been used [1]. The described unit allows collecting medical experts' knowledge given in fuzzy measures. The classified mechanisms of the patient's walk features have been implemented in diagnostics tool of orthopaedic and neurological diseases. Finally the rehabilitation processes can be organised under control of the expert unit.
The paper describes various neural network models designed for automatic conclusion making software in the PSW [8], [4] system. It presents abilities of neural network configuration for choosing the optimal parameters to process the PSW-registered data. The paper also contains the description of artificial data making algorithms, that allow to overcome the problem of insufficient data records describing particular pathologies.
PL
Praca zawiera opis modeli sieci neuronowych wykonanych dla modułu automatycznego wspomagania diagnozy w systemie PSW (Parotec System for Windows). Przedstawione zostały możliwości konfiguracji i doboru parametrów poszczególnych sieci dla określenia wartości optymalnych dla przetwarzania danych generowanych przez system pomiarowy PSW. Przedstawiona została również metoda sztucznej generacji nowych danych pozwalająca na eksperymentalne dobieranie parametrów sieci w warunkach niedoboru ilości danych pomiarowych.
The paper presents the data base structure where fuzzy logic defines the threshold of the foot abnormality. The conclusion making unit supports Parotec System for Windows (PSW) [1], the diagnostic equipment that allows to discus the diseases factors observed on a patient’s static and dynamic footprint. The fuzzy logic roles are used for pathological features selection. They classify the data records putting them into the most relevant pathology. The presented system allows to enter roles describing the disease instead of giving a strict definition. When number of roles grows the fuzzy threshold is getting the strict value. The early results of the system development are described in the paper. The conclusion making unit has been evaluated by several records. For full evaluation of the system more experiments are planed to be done in clinics.
PL
Praca prezentuje system wspomagania diagnozy wykorzystujący regułową bazę wiedzy z pojęciami rozmytymi. System nie rozpoznaje schorzeń, lecz podpowiada patologie związane z nieprawidłowym (nie fizjologicznym) obciążeniem wybranych stref stopy w statyce i dynamice. Informacją potrzebną do prawidłowego funkcjonowania systemu jest zbiór pomiarów pozyskanych przy użyciu narzędzia Parotec System for Windows (PSW). Drugim elementem wykorzystywanym w procesie wnioskowania jest baza wiedzy z regułami rozmytymi ekstrahowana od lekarza – eksperta. Wiedza zapisywana jest w formie koniunkcji warunków pierwotnych opartych na relacji wartości funkcji filtracji do lingwistycznego pojęcia względnego – oddającego wartość wybranego czynnika do odpowiedniej wartości dla całej populacji zebranej w bazie pomiarów. W dynamicznym procesie wnioskowania udostępniono trzy metody wyznaczania term (trójkąty o równych i nierównych podstawach) obejmujących całą dziedzinę pomiarów, oraz odrzucenie pomiarów obarczonych błędem przypadkowym wykraczających poza odchylenie standardowe wyznaczone funkcją Gaussa. Prezentowany system udostępnia możliwość wprowadzania reguł w sposób opisowy bez konieczności dokładnej analizy wartości wielkości mierzonych przez PSW. W procesie defuzyfikacji wyznaczona jest ostra wartość wynikła z superpozycji wartości warunków pierwotnych składających się na regułę wnioskowania lecz końcowym rezultatem diagnozy jest pojęcie rozmyte opisujące „natężenie” występującej patologii.
The paper describes experiments done with the automatic diagnosis module for the PSW System. The experiments have been done in spite of insufficient data records used for learning the neural network. Taking advantage of the artificial data making data making system there was possible to examine some neural network models: Back-Propagation, ART and Counter-Propagation. The paper presents analysis of obtained results and compares efficiency of the neural network algorithms.
PL
Praca prezentuje opis eksperymentów wykonanych przy wykorzystaniu modułu automatycznego wspomagania diagnozy dla systemu PSW (Parotec System for Windows). Eksperymenty zostały wykonane w warunkach niedoboru ilości danych uczących sieć neuronową, stanowiącą trzon całości systemu wnioskowania. Korzystając z metody sztucznej generacji nowych danych pomiarowych na bazie danych rzeczywistych zakłócanych zbiorem wybranych funkcji przetestowano użyteczność dla systemu PSW trzech różnych konfiguracji sieci neuronowej: Back-Propagation, Counter-Propagation oraz ART. Przedstawiona została analiza uzyskanych wyników obejmująca m.in. porównanie efektywności badanych algorytmów oraz zaproponowany został kierunek dalszych badań.
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