Parkinson's disease
PulseAugur coverage of Parkinson's disease — every cluster mentioning Parkinson's disease across labs, papers, and developer communities, ranked by signal.
8 day(s) with sentiment data
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AI model uses wrist sensors for Parkinson's screening
Researchers have developed a novel attention mechanism for more accurate and efficient Parkinson's disease screening using wearable sensors. This method, detailed in an arXiv paper, processes data from wrist-worn Inerti…
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AI model screens Parkinson's disease using face and voice without labels
Researchers have developed a novel method for screening Parkinson's disease using only facial expressions and voice analysis, eliminating the need for direct PD labels. This approach leverages frozen pretrained encoders…
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Celebrities urged to use influence for public health advocacy
Public figures, including athletes and actors, have a responsibility to use their influence for public good, particularly in health advocacy. While celebrity does not equate to expertise, their ability to connect with m…
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Deep learning estimates Parkinson's gait forces with minimal IMUs
Researchers have developed a novel deep learning framework to estimate ground reaction forces (GRFs) in individuals with Parkinson's disease (PD) using a minimal set of wearable inertial measurement units (IMUs). This a…
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Parkinson's disease impairs motor recovery after typing errors, study finds
Researchers have developed a method to distinguish between error monitoring and motor recovery in Parkinson's disease patients using keystroke dynamics. By analyzing backspace events in typing data from the neuroQWERTY …
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Agentic AI aids discovery in large-scale sleep physiology research
Researchers have developed an AI system called AI Sleep Co-Scientist to analyze large-scale sleep physiology data from over 124,000 polysomnography recordings. This expert-guided environment uses specialist agents to as…
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Fosun Pharma subsidiary gets nod for Parkinson's drug trial
Fosun Pharmaceutical has announced that its subsidiary, Fosun Wanbang, has received approval from the National Medical Products Administration to conduct clinical trials for DM1001, a treatment for idiopathic Parkinson'…
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New benchmark standardizes early Parkinson's detection from speech
Researchers have introduced a new benchmark designed to standardize and improve the evaluation of early-stage Parkinson's disease detection using speech. This benchmark addresses inconsistencies in existing studies by p…
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New Level 5 method analyzes Parkinson's gait dynamics using PCA
Researchers have developed a new method called Level 5 to analyze gait dynamics in individuals with Parkinson's disease. This approach uses principal component analysis (PCA) to approximate observed transformations in g…
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Interpretable ML predicts Parkinson's severity using MRI and fMRI
Researchers have developed an interpretable machine learning model capable of predicting Parkinson's disease motor severity using a combination of QSM MRI and multiband multiecho fMRI features. The study found that imag…
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New Spanish speech corpus targets ASR for neurological conditions
Researchers have introduced S-DiverSe, a new corpus of Spanish speech data specifically designed to improve automatic speech recognition (ASR) for individuals with neurological conditions. The dataset comprises 3.2 hour…
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Neuromorphic controller offers power-efficient adaptive DBS for Parkinson's
Researchers have developed a novel neuromorphic silicon neuron controller, named SiLIF-DBS, for adaptive deep brain stimulation (aDBS) in Parkinson's disease patients. This controller, implemented using CMOS technology,…
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New framework improves Parkinson's classification using ECoG and EEG data
Researchers have developed a new swap-adversarial framework designed to improve the accuracy of Parkinson's disease classification using electrocorticography (ECoG) and electroencephalography (EEG) data. This framework …
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AI research tackles superposition in biological data for improved interpretability
Researchers have developed a novel method using sparse autoencoders (SAEs) to address the issue of superposition in artificial intelligence, particularly within high-dimensional biological data. This technique aims to i…
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Neuromorphic learning cuts deep brain stimulation energy by 80%
Researchers have developed an energy-aware learning approach for adaptive deep brain stimulation (DBS) to treat Parkinson's disease. This method directly incorporates actuator energy into the reinforcement learning rewa…
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Video-based system counts Parkinson's steps without wearables · 2 sources tracked
Researchers have developed a novel video-based framework to passively count steps for individuals with Parkinson's disease, addressing limitations of current wearable-based methods. The system utilizes 3D human mesh rec…
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Inverse Reinforcement Learning Identifies Parkinson's Biomarkers in Keystroke Dynamics
Researchers have applied inverse reinforcement learning (IRL) to keystroke dynamics to identify biomarkers for Parkinson's disease (PD). This novel approach models typing behavior to recover an interpretable reward func…
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New DBS system improves Parkinson's gait, published in Nature Medicine
A new deep brain stimulation system developed by the University of California, San Francisco, has shown promise in improving gait for Parkinson's disease patients. This system can detect neural signals related to each s…
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Native-space AI models outperform template-based for subcortical brain segmentation
Researchers have developed two U-Net-based pipelines for segmenting subcortical brain regions, specifically the Subthalamic Nucleus (STN), Red Nucleus (RN), and Substantia Nigra (SN), which are critical for neurosurgica…
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New ML pipeline ActiTect screens for REM sleep disorder
Researchers have developed ActiTect, an open-source machine learning pipeline designed to screen for REM sleep behavior disorder (RBD) using actigraphy data. This tool aims to standardize and automate the analysis of ab…