Body-conforming Multi-modal Sensing with Ultrasound-compatible Surface Electromyography Sensors and a Wearable Ultrasound Array

Surface electromyography (sEMG) is a widely used non-invasive diagnostic modality in rehabilitation, designed to detect muscle activation in response to neural signals at the skin’s surface. However, sEMG has limitations, including its inability to accurately measure deeper muscle activation, low spatial resolution, susceptibility to noise interference, and crosstalk from neighboring muscles. In contrast, ultrasound (US) imaging provides valuable insights into muscle thickness, stiffness, force, and fatigue with high spatial resolution and detection accuracy. Furthermore, the US can assess both superficial and deep muscle layers, addressing the shortcomings of sEMG. The integration of sEMG with US can provide comprehensive insights into both electrophysiological and morphological activities of muscle simultaneously. To facilitate this, we developed ultrasoundcompatible EMG (US-EMG) sensors and a 64-element wearable ultrasound (WUS) array. The US-EMG sensor was fabricated using silver-nanowires and polydimethylsiloxane (AgNWs/PDMS) composite. The fabricated US-EMG sensor performed comparably to the commercial EMG electrodes. Next, The WUS was electrically and acoustically characterized, demonstrating uniformity across the array. Successful acquisition of EMG signals and B-mode US imaging without significant signal loss was achieved during the vertical integration of the WUS array with the US-EMG sensors. On the contrary, the commercial EMG sensors did not allow for clear US imaging. This multi-modal sensing device shows great potential for enhancing motion prediction and muscle fatigue detection.

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Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793647
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
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article
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Body-conforming Multi-modal Sensing with Ultrasound-compatible Surface Electromyography Sensors and a Wearable Ultrasound Array

Yong Zhu, Sunho Moon, Xiaoning Jiang, Xiangming Xue et al.
1 citations
Advanced Sensor and Energy Harvesting Materials
0.18
article

Body-conforming Multi-modal Sensing with Ultrasound-compatible Surface Electromyography Sensors and a Wearable Ultrasound Array

Yong Zhu, Sunho Moon, Xiaoning Jiang, Xiangming Xue, Nitin Sharma, Darpan Shukla, Vidisha Ganesh
article en
1 citations

Abstract

Surface electromyography (sEMG) is a widely used non-invasive diagnostic modality in rehabilitation, designed to detect muscle activation in response to neural signals at the skin’s surface. However, sEMG has limitations, including its inability to accurately measure deeper muscle activation, low spatial resolution, susceptibility to noise interference, and crosstalk from neighboring muscles. In contrast, ultrasound (US) imaging provides valuable insights into muscle thickness, stiffness, force, and fatigue with high spatial resolution and detection accuracy. Furthermore, the US can assess both superficial and deep muscle layers, addressing the shortcomings of sEMG. The integration of sEMG with US can provide comprehensive insights into both electrophysiological and morphological activities of muscle simultaneously. To facilitate this, we developed ultrasoundcompatible EMG (US-EMG) sensors and a 64-element wearable ultrasound (WUS) array. The US-EMG sensor was fabricated using silver-nanowires and polydimethylsiloxane (AgNWs/PDMS) composite. The fabricated US-EMG sensor performed comparably to the commercial EMG electrodes. Next, The WUS was electrically and acoustically characterized, demonstrating uniformity across the array. Successful acquisition of EMG signals and B-mode US imaging without significant signal loss was achieved during the vertical integration of the WUS array with the US-EMG sensors. On the contrary, the commercial EMG sensors did not allow for clear US imaging. This multi-modal sensing device shows great potential for enhancing motion prediction and muscle fatigue detection.

North Carolina State University (US)
Affordable and clean energy
Openalex Percentile: Top 49%
Advanced Sensor and Energy Harvesting Materials
0.18
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