gait analysis

Laboratorio di biomeccanica ed analisi del movimento

Laboratorio di biomeccanica ed analisi del movimento

Il Laboratorio di biomeccanica ed analisi del movimento si occupa di studiare il movimeno umano normale e patologico attraverso lo studio delel componenti cinematiche, cinetiche ed elettromiografiche di superficie.

I segnali derivanti dal movimento vengono catturati in maniera non invasiva e possono essere elaborati per ricavare dati sulle modalità di esecuzione del movimento, sulle caratteristiche biomeccaniche dello stesso, nonché sulle modificazioni in corso di patologia.

Neurophysiology of gait

Beyond the classic clinical description, recent studies have quantitatively evaluated gait and balance dysfunction in cerebellar ataxias by means of modern motion analysis systems. These systems have the aim of clearly and quantitatively describing the differences, with respect to healthy subjects, in kinematic, kinetic, and surface electromyography variables, establishing the basis for a rehabilitation strategy and assessing its efficacy.

Assessment of waveform similarity in electromyographical clinical gait data: the linear fit method

The assessment of waveform similarity is a crucial issue in gait analysis for the comparison of electromyography (EMG) and kinematic patterns with reference data. A typical scenario is in fact the comparison of a patient’s EMG pattern with a relevant physiological pattern. Many methods have been proposed for a quantitative comparison of the two patterns, suggesting the absence of a gold standard. A recently proposed method for comparing kinematic patterns is the linear fit method (LFM). This study aims at testing the applicability of this method on data of EMG.

A comparison of machine learning classifiers for smartphone-based gait analysis

This paper proposes a reliable monitoring scheme that can assist medical specialists in watching over the patient's condition. Although several technologies are traditionally used to acquire motion data of patients, the high costs as well as the large spaces they require make them difficult to be applied in a home context for rehabilitation. A reliable patient monitoring technique, which can automatically record and classify patient movements, is mandatory for a telemedicine protocol.

The Walking Brain: factors influencing human gait

Human walking is a standardized, repeatable and rhythmic locomotor act, with biomechanical patterns reported as roughly common to all healthy individuals. However, some gait patterns could be affected by cognitive, social and cultural factors. This mini-review aims at investigating top-down related differences in walking healthy patterns due to the above factors. The reviewed literature reported that socio-economic factors are at the basis of differences in pedestrian walking speed, related to the pace of life: faster speed was found in industrialized countries than in developing ones.

Perceiving harmony behind walking: a study on healthy subjects

This study aims to investigate how the naturalness of movement is perceived in a sample of healthy participants. Specifically, 256 people (34.2 ± 10.8 years; M = 89; F = 167) were asked by means of an online questionnaire to give an evaluation of the naturalness of a video showing a girl walking along a walkway. We presented four videos of which only one had been recorded in „normal” forward walking and at a comfortable speed and which presented a gait ratio coinciding with the golden proportion.

Gait phase proportions in different locomotion tasks: the pivot role of golden ratio

Walking is a repeatable and cyclic locomotor act, presenting standardized biomechanical patterns within the gait cycle in healthy humans. Specifically, both stance and swing durations exhibit high reliability at comfortable speed, maintaining the same proportion between the twos with respect to different contextual features in forward walking. Recently, it was found that this proportion is close to the "golden ratio" (a well-known irrational number equal to 1.618…).

Selection of clinical features for pattern recognition applied to gait analysis

This paper deals with the opportunity of extracting useful information from medical data retrieved directly from a stereophotogrammetric system applied to gait analysis. A feature selection method to exhaustively evaluate all the possible combinations of the gait parameters is presented, in order to find the best subset able to classify among diseased and healthy subjects.

L-DOPA and freezing of gait in Parkinson's disease: Objective assessment through a wearable wireless system

Freezing of gait (FOG) is a leading cause of falls and fractures in Parkinson's disease (PD). The episodic and rather unpredictable occurrence of FOG, coupled with the variable response to L-DOPA of this gait disorder, makes the objective evaluation of FOG severity a major clinical challenge in the therapeutic management of patients with PD. The aim of this study was to examine and compare gait, clinically and objectively, in patients with PD, with and without FOG, by means of a new wearable system.

Toward A Quantitative Evaluation of the Fall Risk Using the Fusion of Inertial Signals and Electromyography with Wearable Sensors

Freezing of Gait (FOG) is an unpredictable gait disorder typical of Parkinson's Disease (PD). The main goals of this work are detecting FOG episodes, classifying FOG subtypes and analyzing the leg muscles activity toward a deeper insight into the disorder pathophysiology and in the associated risk of fall. Fusion of inertial and electromyographic signals in our wearable system allows distinguishing correctly 98.4% of FOG episodes and monitoring in free-living conditions the activity type and intensity of leg antagonist muscles involved in FOG.

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