2 citations · 2 across the 6 of their papers we have counts for
6 papers
ME-Dex 1.0: Bringing Heterogeneous Tactile Sensing into World Action Modeling
Xuancheng Zhang, Xuetao Liu, Qianying Tang +8
World Action Models bring the predictive capabilities of video models into robot action generation, providing a rich foundation for modeling future visual states. Tactile sensing c…
ReactEMG Stroke: Healthy-to-Stroke Few-shot Adaptation for sEMG-Based Intent Detection
Runsheng Wang, Katelyn Lee, Xinyue Zhu +4
Surface electromyography (sEMG) is a promising control signal for assist-as-needed hand rehabilitation after stroke, but detecting intent from paretic muscles often requires length…
ReactEMG: Stable, Low-Latency Intent Detection from sEMG via Masked Modeling
Runsheng Wang, Xinyue Zhu, Ava Chen +5
Surface electromyography (sEMG) signals show promise for effective human-machine interfaces, particularly in rehabilitation and prosthetics. However, challenges remain in developin…
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…
An Investigation of Multi-feature Extraction and Super-resolution with Fast Microphone Arrays
Eric T. Chang, Runsheng Wang, Peter Ballentine +5
In this work, we use MEMS microphones as vibration sensors to simultaneously classify texture and estimate contact position and velocity. Vibration sensors are an important facet o…