Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients

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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 ...

The hands, our silent performers in daily life, face overwhelming challenges when neurological impairments disrupt the simple tasks that compose our daily symphony. This thesis unveils a comprehensive framework for the objective monitoring of upper-limb re ...

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IntroductionThe current assessment and standardization of microsurgical skills are subjective, posing challenges in reliable skill evaluation. We aim to address these limitations by developing a quantitative and objective framework for accurately assessing ...

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 ...

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 ...

"Ensure healthy lives and promote well-being for all at all ages" is the third sustainable development goal for the United Nations Agenda of 2030. This doctoral thesis fully embodied this objective by targeting stroke, a leading cause of death and disabili ...

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 ...

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

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 motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and ...

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Motor skill learning is a crucial process at all ages. However, healthy aging is often accompanied by a reduction in motor learning capabilities. This study characterized the brain dynamics of healthy older adults during motor skill acquisition and identif ...

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

Hand motor impairments are one of the main causes of disabilities worldwide. Rehabilitation procedures like mirror therapy are given crucial importance. In the traditional setup, the patient moves the healthy hand in front of a mirror; the view of the mirr ...

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients

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Context-Aware Monitoring of Hand Motor Primitives in Daily Life Activities: A Pathway to Objectively Assess Rehabilitation of Patients with Upper-Limb Neurological Impairment

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Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

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

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A mirror therapy system using virtual reality and an actuated exoskeleton for the recovery of hand motor impairments: a study of acceptability, usability, and embodiment

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Contrasting action and posture coding with hierarchical deep neural network models of proprioception