ABSTRACT
BACKGROUND: An early diagnosis of peripheral neuropathy in diabetic patients is useful in order to slow down the progress of this complication. Nerve conduction tests are the gold standard for this diagnosis but they are challenging for the patients. This study examines whether it is possible to assess the presence of diabetic neuropathy at an early stage by static posturography tests. METHODS: Static posturography tests were performed on 37 type-2 diabetic subjects (25 neuropathic patients and 12 non-neuropathic control subjects). Each subject was tested twice under two visual conditions: open and closed eyes. Both "global" (classic) and "structural" (model-based) posturographic parameters (PP) were derived from centre-of-pressure trajectories. A total of 65 PP were computed but only five were selected, normalized and fed to a linear classifier based on linear discriminant analysis. RESULTS: This method correctly classified 86.5% of the patients. Five subjects were misclassified and only 2 false negatives out of 25 neuropathic subjects were erroneously diagnosed as control subjects. CONCLUSIONS: This paper shows that "global" and "structural" parameters derived by static posturography tests, and classic linear statistical approaches, can be used for the diagnosis of neuropathy provided PP are properly chosen and normalized.
Subject(s)
Diabetes Mellitus, Type 2/physiopathology , Diabetic Neuropathies/diagnosis , Neural Conduction/physiology , Peripheral Nervous System Diseases/diagnosis , Posture/physiology , Aged , Anthropometry , Body Mass Index , Case-Control Studies , Diabetic Neuropathies/physiopathology , Discriminant Analysis , Early Diagnosis , Female , Humans , Linear Models , Male , Middle Aged , Multivariate Analysis , Neurologic Examination/methods , Peripheral Nervous System Diseases/physiopathology , Peroneal Nerve/physiopathology , Postural Balance/physiology , Reference Values , Severity of Illness IndexABSTRACT
The objective of this work was to derive a procedure able to estimate joint kinematics, relative to a simple, yet functionally relevant, motor task, starting from ground reaction data. The minimum number of input data has been used: force platform data, few and simple measurements relative to the subject, and protocol-specific parameters. Standing reach (SR) is the motor task analysed. The biomechanical model is a two degrees-of-freedom inverted pendulum moving on the vertical sagittal plane. Joint kinematics has been estimated solving the related direct dynamic problem stated in function of ground reaction data. The original nonlinear differential equation system of the model showed a high sensitivity to errors affecting initial conditions and experimental input data. Consequently, an approximate solution has been looked for in order to reduce the coupling between the model differential equations. This was possible taking into account the peculiar characteristics of the motor task. An optimization procedure has been deemed necessary in order to minimize the effects of the assumed approximation. The method has been tested both with simulated and with experimental data. In this latter case the validation of the angular kinematics estimated by the proposed method has been performed by means of data obtained by a stereophotogrammetric system. Results show a satisfactory behaviour of the whole optimization procedure. Very good results have been obtained in the case of slow reaching tasks.
