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Human gait pattern changes detection system: A multimodal vision-based and novelty detection learning approach

Paulo J., Asvadi A., Peixoto P., Amorim P.

Biocybernetics and Biomedical Engineering

2017

Vol. 37, no. 4

701--717

This paper proposes a novel gait rehabilitation analysis system, based on an innovative multimodal vision-based sensor setup, focused on detecting gait pattern changes over time. The proposed setup is based on inexpensive technologies, without compromising performance, and was designed to be deployed on walkers, which are a typical assistive aid used in gait rehabilitation. In the medical field the evaluation of a patient's rehabilitation progress is typically performed by a medical professional through subjective techniques based on the professional's visual perception and experience. In this context, we are proposing an automatic system to detect the progress of patients undergoing rehabilitation therapy. Our approach is able to perform novelty detection for gait pattern classification based on One- Class Support Vector Machines (OC-SVM). Using point-cloud and RGB-D data, we detect the lower limbs (waist, legs and feet) by using Weighted Kernel-Density Estimation and Weighted Least-Squares to segment the legs into several parts (thighs and shins), and by fitting 3D ellipsoids to model them. Feet are detected using k-means clustering and a Circular Hough Transform. A temporal analysis of the feet's depth is also performed to detect heel strike events. Spatiotemporal and kinematic features are extracted from the lower limbs' model and fed to a classifier based on the fusion of several OC-SVMs. Experiments with volunteers using the robotic walker platform ISR-AIWALKER, where the proposed system was deployed, revealed a lower limbs tracking accuracy of 38 and that our novelty detection approach successfully identified novel gait patterns, evidencing an overall 97.89% sensitivity.

Rehabilitation robot RRH1

Kaczmarski M., Granosik G.

Archive of Mechanical Engineering

2011

Vol. LVIII, nr 1

103-113

The paper presents a prototype of a rehabilitation robot for lower extremities. It is created on the basis of cylindrical kinematic model, equipped with two rigid arms, special handles and fixtures. It has five active degrees of freedom and is designed to repeat the trajectories generated by physiotherapist during the learning phase. Presented prototype of rehabilitation robot has the ability to replay different types of trained exercises such as: hip and knee flexion/extension, leg abduction/adduction. The protection system (including overload detection) implemented in the robot ensures safe working with patients.

Artykuł prezentuje prototyp robota do rehabilitacji kończyn dolnych. Robot zbudowany jest w oparciu o cylindryczny układ kinematyczny o dwóch sztywnych ramionach. Posiada 5 aktywnych stopni swobody i przeznaczony jest do odtwarzania zadanej przez fizykoterapeutę trajektorii ruchu. Robot posiada możliwość odtwarzania ćwiczeń zgięcia, wyprostu w stawie kolanowym i biodrowym oraz przywodzenia i odwodzenia nogi. Zastosowany w robocie system zabezpieczeń, zawierający detekcję nadmiernego oddziaływania kończyny dolnej na ramiona robota, pozwala na bezpieczną pracę z pacjentami.