2 citations · 3 across the 10 of their papers we have counts for
6 papers · 1 filter
Reciprocal Learning of Intent Inferral with Augmented Visual Feedback for Stroke
Jingxi Xu, Ava Chen, Lauren Winterbottom +5
Intent inferral, the process by which a robotic device predicts a user's intent from biosignals, offers an effective and intuitive way to control wearable robots. Classical intent…
Fabric Sensing of Intrinsic Hand Muscle Activity
Katelyn Lee, Runsheng Wang, Ava Chen +9
Wearable robotics have the capacity to assist stroke survivors in assisting and rehabilitating hand function. Many devices that use surface electromyographic (sEMG) for control rel…
ChatEMG: Synthetic Data Generation to Control a Robotic Hand Orthosis for Stroke
Jingxi Xu, Runsheng Wang, Siqi Shang +10
Intent inferral on a hand orthosis for stroke patients is challenging due to the difficulty of data collection. Additionally, EMG signals exhibit significant variations across diff…
Meta-Learning for Fast Adaptation in Intent Inferral on a Robotic Hand Orthosis for Stroke
Pedro Leandro La Rotta, Jingxi Xu, Ava Chen +5
We propose MetaEMG, a meta-learning approach for fast adaptation in intent inferral on a robotic hand orthosis for stroke. One key challenge in machine learning for assistive and r…
Grasp Force Assistance via Throttle-based Wrist Angle Control on a Robotic Hand Orthosis for C6-C7 Spinal Cord Injury
Joaquin Palacios, Alexandra Deli-Ivanov, Ava Chen +4
Individuals with hand paralysis resulting from C6-C7 spinal cord injuries frequently rely on tenodesis for grasping. However, tenodesis generates limited grasping force and demands…
Volitional Control of the Paretic Hand Post-Stroke Increases Finger Stiffness and Resistance to Robot-Assisted Movement
Ava Chen, Katelyn Lee, Lauren Winterbottom +7
Increased effort during use of the paretic arm and hand can provoke involuntary abnormal synergy patterns and amplify stiffness effects of muscle tone for individuals after stroke,…