相关论文: A Metric for Evaluating and Comparing Closed-Loop …
Foot drop is commonly managed using Functional Electrical Stimulation (FES), typically delivered via open-loop controllers with fixed stimulation intensities. While users may manually adjust the intensity through external controls, this…
Closed-loop sleep modulation is an emerging research paradigm to treat sleep disorders and enhance sleep benefits. However, two major barriers hinder the widespread application of this research paradigm. First, subjects often need to be…
The evaluation of machine learning algorithms in biomedical fields for applications involving sequential data lacks standardization. Common quantitative scalar evaluation metrics such as sensitivity and specificity can often be misleading…
Functional Electrical Stimulation (FES) systems are successful in restoring motor function and supporting paralyzed users. Commercially available FES products are open loop, meaning that the system is unable to adapt to changing conditions…
This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of Rapid Human Movement. We have validated our research in a…
Compressed sensing typically deals with the estimation of a system input from its noise-corrupted linear measurements, where the number of measurements is smaller than the number of input components. The performance of the estimation…
Inspired by spiking neural feedback, we propose a spiking controller for efficient locomotion in a soft robotic crawler. Its bistability, akin to neural fast positive feedback, combined with a sensorimotor slow negative feedback loop,…
We study the statistical physics of a surprising phenomenon arising in large networks of excitable elements in response to noise: while at low noise, solutions remain in the vicinity of the resting state and large-noise solutions show…
A deep neural network (DNN) that can reliably model muscle responses from corresponding brain stimulation has the potential to increase knowledge of coordinated motor control for numerous basic science and applied use cases. Such cases…
Neurostimulation is a promising therapy for abating epileptic seizures. However, it is extremely difficult to identify optimal stimulation patterns experimentally. In this study human recordings are used to develop a functional 24 neuron…
Activity and motion analysis has the potential to be used as a diagnostic tool for mental disorders. However, to-date, little work has been performed in turning stratification measures of activity into useful symptom markers. The research…
The assessment of Parkinson's disease (PD) poses a significant challenge as it is influenced by various factors which lead to a complex and fluctuating symptom manifestation. Thus, a frequent and objective PD assessment is highly valuable…
The objective of this paper is to present a Mixed Reality System (MRS) for rehabilitation of the upper limb after stroke. The system answers the following challenges: (i) increase motivation of patients by making the training a personalized…
Recent global estimates suggest that as many as 2.41 billion individuals have health conditions that would benefit from rehabilitation services. Home-based Physical Therapy (PT) faces significant challenges in providing interactive feedback…
Peripheral Nerve Stimulation (PNS) constrains the clinical performance of Magnetic Resonance and Particle Imaging (MRI and MPI) systems. Extensive magneto-stimulation studies have been carried out recently in the field of MPI, where typical…
Parkinson's disease (PD) is a chronic, degenerative neurological disorder. PD cannot be prevented, slowed or cured as of today but highly effective symptomatic treatments are available. We consider relevant estimands and treatment effect…
In this paper, we analyze 48 signals of rest tremor velocity related to 12 distinct subjects affected by Parkinson's disease. The subjects belong to two different groups, formed by four and eight subjects with, respectively, high- and…
Common measures of neural representational (dis)similarity are designed to be insensitive to rotations and reflections of the neural activation space. Motivated by the premise that the tuning of individual units may be important, there has…
Much of the focus in the design of deep neural networks has been on improving accuracy, leading to more powerful yet highly complex network architectures that are difficult to deploy in practical scenarios, particularly on edge devices such…
Objective: The aim of this study is to propose an adaptive scheme embedded into an open-source environment for the estimation of the neural activation extent during deep brain stimulation and to investigate the feasibility of approximating…