A model-based strategy for quadruped running with differentiated fore- and hind leg morphologies

This article introduces a model-based strategy for a quadruped robot with differentiated fore- and hind-leg ground reaction-force patterns to generate animal-like running behavior. The proposed model comprises a rigid body and two eSLIP legs with dampers. The eccentric-SLIP (eSLIP) model extends the traditional spring-loaded inverted pendulum (SLIP) model by adding a bar to offset the spring direction. The proposed two-leg eSLIP (TL-eSLIP) model’s fore- and hind legs were designed to have the same offset magnitude but in opposite offset directions, producing different braking and thrusting force patterns. The TL-eSLIP model’s reference leg trajectories were designed based on the fixed-point motion of the eSLIP model. Additionally, the legs were clock torque-controlled to modulate leg motion and stabilize the model to follow its natural dynamics. The model’s equations for motion were derived, and the model’s dynamic behavior was simulated and analyzed. The simulation results indicate that the model with leg offsets and in either trotting or pronking has differentiated leg force patterns, and it is more stable and has larger basins of attraction than the model without leg offsets. A quadruped robot was built for experimental validation. The experimental results demonstrate that the robot with differentiated legs ran with differentiated ground reaction force patterns and ran more stably than another robot with the same leg morphology.

Using motion capture analysis for assessing locomotion after arthroscopic anterior cruciate ligament reconstruction

An anterior cruciate ligament tear is one of the most common injuries to the capsular ligament apparatus of the knee necessitating operative treatment. Postoperatively, patients with anterior cruciate ligament injuries develop a pathologic gait pattern. Today, innovative diagnostic and rehabilitation methods for patients with gait disturbances associated with such injuries are in high demand. Below, we present a case of using 3D motion capture analysis for the personalized assessment of gait function in a patient with the reconstructed anterior cruciate ligament two months after surgery. The analysis revealed that the patient had a slower, shorter, wider step with longer step intervals than the healthy subject; the flexion and extension amplitude in the large joints of the operated leg was smaller than in the healthy contralateral leg. Motion capture analysis can be used to assess the postoperative dynamics in patients with anterior cruciate ligament tears.

Proposta de novos índices de simetria e assimetria para amplitude de movimento em idosas

Objetivo: Propor uma nova equação para o cálculo do índice de simetria e assimetria de amplitude de movimento entre membros. Métodos: Foram propostas duas equações distintas para avaliação de simetria e assimetria entre membros, denominadas como Índice de Simetria entre Membros e Índice de Assimetria entre Membros. Sendo assim, foi realizada a avaliação de 48 idosas com idade entre 60 e 79 anos, mediante bateria de testes para amplitude de movimento. Foram utilizados testes funcionais para avaliação em membros superiores, membros inferiores, e o Ankle Test na plataforma Leg Motion para a dorsiflexão de tornozelo. Os dados foram analisados através das equações propostas pelos autores do presente estudo. Resultados: As equações utilizadas se apresentaram aplicáveis e eficientes para análise da simetria e assimetria da amplitude de movimento entre membros em idosas. Conclusão: As equações propostas são aplicáveis para determinação de valores de simetria e assimetria de amplitude de movimento entre membros em mulheres idosas utilizando diferentes testes funcionais. Além disso, tais equações proporcionam subsídios aos profissionais da saúde para este tipo de avaliação.

Utilization of Micro-Doppler Radar to Classify Gait Patterns of Young and Elderly Adults: An Approach Using a Long Short-Term Memory Network

To develop a daily monitoring system for early detection of fall risk of elderly people during walking, this study presents a highly accurate micro-Doppler radar (MDR)-based gait classification method for the young and elderly adults. Our method utilizes a time-series of velocity corresponding to leg motion during walking extracted from the MDR spectrogram (time-velocity distribution) in an experimental study involving 300 participants. The extracted time-series was inputted to a long short-term memory recurrent neural network to classify the gaits of young and elderly participant groups. We achieved a classification accuracy of 94.9%, which is significantly higher than that of a previously presented velocity-parameter-based classification method.