The Tass Lab has invented non-invasive, Vibrotactile Coordinated Reset (vCR) stimulation devices and methods to safely and efficiently treat brain disorders characterized by abnormal neuronal synchrony such as Parkinson's disease.
The Tass Lab has invented non-invasive, Vibrotactile Coordinated Reset (vCR) stimulation devices and methods to safely and efficiently treat brain disorders characterized by abnormal neuronal synchrony such as Parkinson's disease.
The Tass Lab has invented non-invasive, Vibrotactile Coordinated Reset (vCR) stimulation devices and methods to safely and efficiently treat brain disorders characterized by abnormal neuronal synchrony such as Parkinson's disease.
The Tass Lab has invented non-invasive, Vibrotactile Coordinated Reset (vCR) stimulation devices and methods to safely and efficiently treat brain disorders characterized by abnormal neuronal synchrony such as Parkinson's disease.
Stanford researchers have developed a method for targeted focused ultrasound application to peripheral nerves to suppress acute pain. This invention can non-invasively concentrate ultrasound waves onto peripheral nerves without impacting surrounding tissue.
Stanford researchers have designed an automated targeting software that could be incorporated into planning for Focused-Ultrasound (FUS) thalamotomy such as MRI-guided-focused-ultrasound (MRgFUS) ablation) for tremor reduction.
Stanford researchers have created a novel wearable device and system to assess fatigue on the user based on electrical activity associated with an eye blink of the subject.
Stanford researchers at the Lee Lab have developed a new system and method for measuring pathology then applying a novel algorithm to optimize neurostimulation therapy for altering pathology for treatment of neurodegenerative diseases.
Stanford researchers at the Lee Lab have developed a method to understand whole-brain circuit mechanisms underlying neurological disease and its application to predict the outcome of therapeutic interventions.
Stanford researchers have developed a patient classification method (healthy, idiopathic, diabetic, etc.) based on a quantitative assessment score derived from autonomic and gastric electrocardiogram (ECG) and electrogastrogram (EGG) data.
Researchers at Stanford University have established a deep learning segmentation algorithm for non-contrast CT images to aid clinicians in decision making and improve the speed of symptom to treatment in acute ischemic stroke
Stanford inventors have created a novel, interactive, highly scalable computational approach for representing dynamic brain activity as a network for use in clinical settings.
Stanford inventors have developed an information theoretic, seizure detection algorithm for electroencephalography (EEG) towards improving diagnosis, management, and treatment of patients with epilepsy.