Geração de trajetórias angulares para articulações de uma órtese ativa usando modelagem de caminhada

Abstract

In recent years, an increase has been observed in the number of researches that uses active orthosis for rehabilitation or functional compensation. However, despise the accomplished advances, the challenges related to energy consumption reduction and the ability to generate anthropomorphic movement still persist. Furthermore, recent studies point that is important to take into consideration user-related features, which turn out not to be a trivial task. A possible aproach for these issues is using gait model in order to generate references for anthropomorphic movements. In recent years, some studies have used statistical approaches to model human gait, offering another possible solution that can generate joint trajectory information. One of these approaches is the Principal Component Analysis (PCA). The main PCA characteristic is the ability to split into different components different behavior found in a dataset. When applied to gait features it is possible to organize such components into user-oriented characteristis and general gait information. Inside this context, in the presente work is presented a method able to find useroriented gait trajectories that can be used in powered lower limb orthosis applications. The proposed method uses principal component analysis to extract shared features from a gait dataset, taking into consideration gait-related variables such as joint angle information and the users anthropometric features, used directly in an orthosis application. The trajectories of joint angles used by the model are represented by a given number of harmonics according to their respective Fourier series analyses. This representation allows better performance of the model, whose capability to generate gait information is validated through experiments using a real active orthotic device, analysing both joint motor energy consumption and user metabolic effort.