Fabiola Spolaor

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The next generation of tools for rehabilitation robotics requires advanced human-robot interfaces able to activate the device as soon as patient’s motion intention is raised. This paper investigated the suitability of Support Vector Machine (SVM) classifiers for identification of locomotion intentions from surface electromyography (sEMG) data. A(More)
The World Health Organization warns that, in 2000, as many as 33 million Europeans suffered from diabetes, approximately 15% will likely develop foot ulcers, and approximately 15-20% of these patients will face lower-extremity amputation. Changes in some gait parameters that appear to be specific in diabetes have been identified in the literature: shorter(More)
Diabetic peripheral neuropathy (DPN) causes motor control alterations during daily life activities. Tripping during walking or stair climbing is the predominant cause of falls in the elderly subjects with DPN and without (NoDPN). Surface Electromyography (sEMG) has been shown to be a valid tool for detecting alterations of motor functions in subjects with(More)
This paper evaluates the use of Gaussian Mixture Model (GMM) trained through Electromyography (EMG) signals to online estimate the bending angle of a single human joint. The parameters involved in the evaluation are the number of Gaussian components, the channel used for model, the feature extraction method, and the size of the training set. The feature(More)
Gait analysis is recognized as a useful assessment tool in the field of human movement research. However, doubts remain on its real effectiveness as a clinical tool, i.e. on its capability to change the diagnostic-therapeutic practice. In particular, the conditions in which evidence of a favorable cost-benefit ratio is found and the methodology for properly(More)
Introduction Type 2 diabetes is predicted to become the 7 leading cause of death in the world by the year 2030 [1]. Diabetic foot is the most common long-term diabetic complication, and it is a major risk factor for plantar ulceration (PU), it is determined by peripheral neuropathy (PN), vascular disease, increased foot pressures, foot trauma, deformity and(More)
Diabetes neuropathy and vasculopathy are the two major complications of diabetes mellitus, leading to diabetic foot disease, of which the worst consequences are plantar ulcers and amputations. Motor impairments like joint stiffness and loss of balance are distinctive effects of diabetes and they have been extensively explored. However, while altered muscle(More)
Diabetic foot is one of the most debilitating complications of diabetes and may lead to plantar ulcers. In the last decade, gait analysis, musculoskeletal modelling (MSM) and finite element modelling (FEM) have shown their ability to contribute to diabetic foot prevention and suggested that the origin of the plantar ulcers is in deeper tissue layers rather(More)
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