AIMC Topic: Walking

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Comparison of feed-forward control strategies for simplified vertical hopping model with intrinsic muscle properties.

Bioinspiration & biomimetics
To analyse walking, running or hopping motions, models with high degrees of freedom are usually used. However simple reductionist models are advantageous within certain limits. In a simple manner, the hopping motion is generally modelled by a spring-...

Prediction of poststroke independent walking using machine learning: a retrospective study.

BMC neurology
BACKGROUND: Accurately predicting the walking independence of stroke patients is important. Our objective was to determine and compare the performance of logistic regression (LR) and three machine learning models (eXtreme Gradient Boosting (XGBoost),...

Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.

Sensors (Basel, Switzerland)
Gait analysis systems are critical for assessing motor function in rehabilitation and elderly care. This study aimed to develop and optimize an abnormal gait classification algorithm considering joint impairments using inertial measurement units (IMU...

Sensorimotor control of robots mediated by electrophysiological measurements of fungal mycelia.

Science robotics
Living tissues are still far from being used as practical components in biohybrid robots because of limitations in life span, sensitivity to environmental factors, and stringent culture procedures. Here, we introduce fungal mycelia as an easy-to-use ...

Robot-assisted gait training in patients with various neurological diseases: A mixed methods feasibility study.

PloS one
BACKGROUND: Walking impairment represents a relevant symptom in patients with neurological diseases often compromising social participation. Currently, mixed methods studies on robot-assisted gait training (RAGT) in patients with rare neurological di...

Gait pattern modification based on ground contact adaptation using the robot-assisted training platform (RATP).

Medical & biological engineering & computing
Robot-assisted rehabilitation and training systems are utilized to improve the functional recovery of individuals with mobility limitations. These systems offer structured rehabilitation through precise human-robot interaction, outperforming traditio...

Comparing the effectiveness of robotic plantarflexion resistance and biofeedback between overground and treadmill walking.

Journal of biomechanics
Individuals with diminished walking performance caused by neuromuscular impairments often lack plantar flexion muscle activity. Robotic devices have been developed to address these issues and increase walking performance. While these devices have sho...

Comparison of the Accuracy of Ground Reaction Force Component Estimation between Supervised Machine Learning and Deep Learning Methods Using Pressure Insoles.

Sensors (Basel, Switzerland)
The three Ground Reaction Force (GRF) components can be estimated using pressure insole sensors. In this paper, we compare the accuracy of estimating GRF components for both feet using six methods: three Deep Learning (DL) methods (Artificial Neural ...

Estimating highest capacity propulsion performance using backward-directed force during walking evaluation for individuals with acquired brain injury.

Journal of neuroengineering and rehabilitation
There are over 5.3 million Americans who face acquired brain injury (ABI)-related disability as well as almost 800,000 who suffer from stroke each year. To improve mobility and quality of life, rehabilitation professionals often focus on walking reco...

Synthetic 3D full-body skeletal motion from 2D paths using RNN with LSTM cells and linear networks.

Computers in biology and medicine
Gait analysis has proven to be a key process in the functional assessment of people involving many fields, such as diagnosis of diseases or rehabilitation, and has increased in relevance lately. Gait analysis often requires gathering data, although t...