AIMC Topic: Foot
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A Novel Gait Phase Recognition Method Based on DPF-LSTM-CNN Using Wearable Inertial Sensors.
Sensors (Basel, Switzerland)
Jun 26, 2023
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)
May 30, 2023
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)
Jan 2, 2023
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)
Oct 27, 2022
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
Oct 11, 2022
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)
Sep 14, 2022
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 ...
Effect of button layout on the exploration and learning of robot operation using an unfamiliar controller.
PloS one
Sep 2, 2022
Robots are becoming increasingly accessible to both experts and non-experts. Therefore, establishing a method for learning robot operations that can be easily mastered by non-experts is important. With this in mind, we aimed to develop a method that ...
A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts.
Sensors (Basel, Switzerland)
May 19, 2022
Many algorithms use 3D accelerometer and/or gyroscope data from inertial measurement unit (IMU) sensors to detect gait events (i.e., initial and final foot contact). However, these algorithms often require knowledge about sensor orientation and use e...
Strategies for Generating Footsteps of Biped Robots in Narrow Sight.
Sensors (Basel, Switzerland)
May 18, 2022
In this paper, we present a strategy for a legged robot to stably cross cinder blocks with a limited area acquired from a camera. First, we used the point cloud acquired from the camera to detect the planes and calculate their centroids and direction...
Performance of Deep Learning Models in Forecasting Gait Trajectories of Children with Neurological Disorders.
Sensors (Basel, Switzerland)
Apr 13, 2022
Forecasted gait trajectories of children could be used as feedforward input to control lower limb robotic devices, such as exoskeletons and actuated orthotic devices (e.g., Powered Ankle Foot Orthosis-PAFO). Several studies have forecasted healthy ga...
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