When worn on the thorax, this device allows for precise monitoring of diaphragm thickness with sub-millimeter accuracy. Diaphragm thickness is a metric used in the clinic to assess diaphragm dysfunction and predict outcome in patients on mechanical ventilation. By analyzing muscle movements, the researchers were also able to detect different breathing patterns, such as shallow and deep breathing. This feature could help diagnose conditions related to breathing abnormalities, such as asthma, pneumonia, and chronic obstructive pulmonary disease (COPD). In a small group trial, the device was successful in differentiating the breathing patterns of COPD patients from those of healthy participants.
“This shows the potential of this technology for clinical applications in respiratory care,” said study co-lead author and postdoctoral fellow in the Department of Chemical and Nanoengineering at the University of California, San Diego, Aiso Tamfeng Lee. Muyang Lin said.
When worn on the forearm, the device can accurately track muscle movements in the hand and wrist. Thanks to artificial intelligence algorithms developed by the team, the system is able to recognize various hand gestures solely from ultrasound signals. The system can recognize 13 degrees of freedom, covering 10 finger joints and 3 wrist rotation angles. This makes it possible to capture even the slightest movement of the wrist or fingers with high sensitivity.
In a proof-of-concept test, participants controlled a robotic arm using a device worn on their forearm and injected water into a beaker with a pipette. In another demonstration, the device was used to play a virtual game, using wrist movements to control the flight of a virtual bird through obstacles. “These demonstrations highlight the potential of this technology in prosthetics, gaming, and other human-machine interface applications,” said Dr. Wenton Yue, co-lead author of the study. Aiiso Yufeng Li Family candidate in the Department of Chemistry and Nanoengineering at the University of California, San Diego.
In the future, the researchers plan to improve the accuracy, portability, energy efficiency, and computational power of this technology.
Paper: “Wearable echocardiography system based on a single transducer”
This project was supported by the National Institutes of Health (NIH grants 1R21EB025521-01, 1R21EB027303-01A1, 3R21EB027303-02S1 and 1R01 EB033464-01).
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