Wearable barometric pressure sensor to improve postural transition recognition of mobility-impaired stroke patients

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Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpa ...

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the ...

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decod ...

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body’s kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to livin ...

Smartphones enable understanding human behavior with activity recognition to support peoples daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly conducted in homogeneous ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and m ...

The success of drone missions is incumbent on an accurate determination of the drone pose and velocity, which are collectively estimated by fusing iner- tial measurement unit and global navigation satellite system (GNSS) mea- surements. However, during a G ...

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

In this thesis, the aerodynamic challenges in flapping wing flight are addressed. In particular, the effects of different wing kinematics, flexibilities, and planforms on the the leading edge vortex development and aerodynamic performance are investigated. ...

The sense of touch can provide a robot with a wealth of information about the contact region when interacting with an unknown environment. Nevertheless, utilizing touch information to plan exploration paths and adjust robot posture to improve task efficien ...

Wearable barometric pressure sensor to improve postural transition recognition of mobility-impaired stroke patients

Chattez avec Graph Search

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Early decoding of walking tasks with minimal set of EMG channels

Exploration-based model learning with self-attention for risk-sensitive robot control

Identification of the trade-off between speed and efficiency in undulatory swimming using a bio-inspired robot

Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Piecewise Affine Curvature model: a reduced-order model for soft robot-environment interaction beyond PCC

Identifying aerodynamics of small fixed-wing drones using inertial measurements for model-based navigation

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Implicit Distance Functions: Learning and Applications in Robotics

The effects of kinematics, flexibility, and planform on the vortex formation and aerodynamic performance of flapping wing flight

Online active and dynamic object shape exploration with a multi-fingered robotic hand