AIMC Topic: Foot

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The generalized spring-loaded inverted pendulum model for analysis of various planar reduced-order models and for optimal robot leg design.

Bioinspiration & biomimetics
This paper proposes a generalized spring-loaded inverted pendulum (G-SLIP) model to explore various popular reduced-order dynamic models' characteristics and suggest a better robot leg design under specified performance indices. The G-SLIP model's co...

From jargon to clarity: Improving the readability of foot and ankle radiology reports with an artificial intelligence large language model.

Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
BACKGROUND: The purpose of this study was to evaluate the efficacy of an Artificial Intelligence Large Language Model (AI-LLM) at improving the readability foot and ankle orthopedic radiology reports.

Accurate COP Trajectory Estimation in Healthy and Pathological Gait Using Multimodal Instrumented Insoles and Deep Learning Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Measuring center-of-pressure (COP) trajectories in out-of-the-lab environments may provide valuable information about changes in gait and balance function related to natural disease progression or treatment in neurological disorders. Traditional equi...

A Novel Gait Phase Recognition Method Based on DPF-LSTM-CNN Using Wearable Inertial Sensors.

Sensors (Basel, Switzerland)
Gait phase recognition is of great importance in the development of rehabilitation devices. The advantages of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) are combined (LSTM-CNN) in this paper, then a gait phase recognition me...

Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning.

Sensors (Basel, Switzerland)
Legged robots can travel through complex scenes via dynamic foothold adaptation. However, it remains a challenging task to efficiently utilize the dynamics of robots in cluttered environments and to achieve efficient navigation. We present a novel hi...

Deep Neural Network for the Detections of Fall and Physical Activities Using Foot Pressures and Inertial Sensing.

Sensors (Basel, Switzerland)
Fall detection and physical activity (PA) classification are important health maintenance issues for the elderly and people with mobility dysfunctions. The literature review showed that most studies concerning fall detection and PA classification add...

Gait Events Prediction Using Hybrid CNN-RNN-Based Deep Learning Models through a Single Waist-Worn Wearable Sensor.

Sensors (Basel, Switzerland)
Elderly gait is a source of rich information about their physical and mental health condition. As an alternative to the multiple sensors on the lower body parts, a single sensor on the pelvis has a positional advantage and an abundance of information...

Optimal planar leg geometry in robots and crabs for idealized rocky terrain.

Bioinspiration & biomimetics
Natural terrain is uneven so it may be beneficial to grasp onto the depressions or 'valleys' between obstacles when walking over such a surface. To examine how leg geometry influences walking across obstacles with valleys, we (1) modeled the performa...

Using Deep Learning to Predict Minimum Foot-Ground Clearance Event from Toe-Off Kinematics.

Sensors (Basel, Switzerland)
Efficient, adaptive, locomotor function is critically important for maintaining our health and independence, but falls-related injuries when walking are a significant risk factor, particularly for more vulnerable populations such as older people and ...