Fully Wearable Armband for Long-Term Peripheral Ultrasound Neuromodulation in Pain Management
Moscoso-Barrera, W. D.; Han, Y.; Jeong, J.; Chen, Q.; Wynn, T.; Yu, M.; Tang, K. W. K.; Yao, M.; Hsieh, J.-C.; Wu, D.; Gauthreaux, L.; Qian, X.; Jia, Y.; Wang, H.
Show abstract
Chronic pain is a leading cause of medical consultations, often managed with opioids despite their high risk of addiction. Low-Intensity Focused Ultrasound (LIFU) neuromodulation has emerged as a promising non- invasive alternative for pain management. However, effective pain modulation often requires prolonged or continuous stimulation, and current LIFU devices are typically bulky and tethered to external power sources, limiting their applicability as wearable technologies for long-term use. This study introduces a fully wearable LIFU-based armband designed for peripheral nerve stimulation in pain management. It integrates a concave piezoelectric transducer, an acoustic hydrogel sheet for strong adhesion and extended use, as well as a miniaturized electronic circuit with a lithium-ion battery in a fabric armband for comfortable placement. LIFU was applied to the median nerve, and its effects on pain thresholds were evaluated in healthy volunteers using pressure algometry and cold pressor tasks. Results showed a significant increase in pain thresholds, with an average rise of 15%. These findings support the potential of wearable LIFU neuromodulation as a noninvasive and portable therapy for chronic pain management.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Biohybrid tendons enhance the power-to-weight ratio and modularity of muscle-powered robots 94%
- Multimodal layer-crossing interrogation of brain circuits enabled by microfluidic axialtrodes 94%
- Stiffness-tunable neurotentacles for minimally invasive implantation and long-term neural activity recordings 94%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.