AIMC Topic: Humans

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A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and Imagined Speech.

IEEE transactions on bio-medical engineering
OBJECTIVE: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols combining the temporal resolution of electroencephalography (EEG) wit...

A Human-Centered Machine-Learning Approach for Muscle-Tendon Junction Tracking in Ultrasound Images.

IEEE transactions on bio-medical engineering
Biomechanical and clinical gait research observes muscles and tendons in limbs to study their functions and behaviour. Therefore, movements of distinct anatomical landmarks, such as muscle-tendon junctions, are frequently measured. We propose a relia...

A Neuromorphic Model With Delay-Based Reservoir for Continuous Ventricular Heartbeat Detection.

IEEE transactions on bio-medical engineering
There is a growing interest in neuromorphic hardware since it offers a more intuitive way to achieve bio-inspired algorithms. This paper presents a neuromorphic model for intelligently processing continuous electrocardiogram (ECG) signal. This model ...

T cell immune responses deciphered.

Science (New York, N.Y.)
A machine-learning approach reveals antigen encoding that predicts T cell responses.

Retzius-Sparing Robot-Assisted Radical Prostatectomy.

Journal of visualized experiments : JoVE
The technique of Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) and initial experience with it at a single center are provided. The technique is described step-by-step and further illustrated by a video to enhance reproducibility. Ear...

Feasibility of Overground Gait Training Using a Joint-Torque-Assisting Wearable Exoskeletal Robot in Children with Static Brain Injury.

Sensors (Basel, Switzerland)
Pediatric gait disorders are often chronic and accompanied by various complications, which challenge rehabilitation efforts. Here, we retrospectively analyzed the feasibility of overground robot-assisted gait training (RAGT) using a joint-torque-assi...

Deep Learning Methods for Speed Estimation of Bipedal Motion from Wearable IMU Sensors.

Sensors (Basel, Switzerland)
The estimation of the speed of human motion from wearable IMU sensors is required in applications such as pedestrian dead reckoning. In this paper, we test deep learning methods for the prediction of the motion speed from raw readings of a low-cost I...

Real-Time Abnormal Object Detection for Video Surveillance in Smart Cities.

Sensors (Basel, Switzerland)
With the adaptation of video surveillance in many areas for object detection, monitoring abnormal behavior in several cameras requires constant human tracking for a single camera operative, which is a tedious task. In multiview cameras, accurately de...

A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts.

Sensors (Basel, Switzerland)
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...

RL-DOVS: Reinforcement Learning for Autonomous Robot Navigation in Dynamic Environments.

Sensors (Basel, Switzerland)
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t...