A portable, smart ultrasound monitor for the muscles has been developed by researchers. Attachable to the body with an epoxy and powered by a little power, the system remotely captures high-resolution images of body movements, enabling steady, long-term monitoring. It essentially monitored the diaphragm work for breathing health analyses when worn on the breast box. It effectively recorded hand gestures when worn on the shoulder, enabling people to use robotic arms and play online games. This novel technologies has possible applications in both human-machine interfaces and care for more normal mechanical control of conditions affecting muscles function.
A smart sonar machine with potential programs in medical and human-machine interfaces has been created by engineers at the University of California San Diego. The system allows ultra-high-resolution tracking of body work without the need for invasive procedures because it is able to adhere to body with a layer of epoxy and work with a battery.
A team of researchers at UC San Diego’s Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, led by Sheng Xu, a doctor and Jacobs Faculty Scholar, published their work on October 31 in Nature Electronics. The task involved Jinghong Li, a professor of medicine at UC San Diego Health, a cardiologist, expert in intensive care, and author of the book.
To track membrane movement and texture, which are important for determining breathing health, the system was worn over the rib cage in testing. According to Joseph Wang, a distinguished teacher in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering who is a co-author of the review,” the systems could possibly help patients with respiratory problems and those depend on mechanical ventilation.”
Additionally, the device’s ability to record hand and wrist muscle activity allowed it to function as a human-machine interface for controlling a robotic arm and playing a virtual game.
This wearable ultrasound technology may provide a promising alternative to the conventional electromyography ( EMG) technique, which involves applying metal electrodes to the skin to measure electrical muscle activity. Despite EMG’s longstanding use, it suffers from low resolution and weak signals. For instance, it’s challenging to separate the contributions of a particular muscle fiber because signals from several different muscle fibers frequently blend together.
Ultrasound, however, provides high-resolution imaging by penetrating deep tissues, offering detailed insights into muscle function. The ultrasound technology that Xu’s team and their collaborators developed has the additional advantages of being compact, wireless, and low-power. ” This technology could potentially be worn by individuals during their daily routines for continuous, long-term monitoring”, said study co-first author Xiangjun Chen, a Ph. PhD candidate at UC San Diego’s program in materials science and engineering.
A single transducer for sending and receiving ultrasound waves, a custom-designed wireless circuit that controls the transducer, records data, and wirelessly transmits the data to a computer, and a lithium-polymer battery that can last at least three hours make up the system’s main components.
The effective use of a single ultrasound transducer is a key innovation in this study. The transducer generates radiofrequency signals with intensity-controlled ultrasound waves, which provide valuable information for use in clinical applications like measuring the thickness of the diaphragm. Using these signals, the device can achieve high spatial resolution, which is key for isolating specific muscle movements. The researchers created an artificial intelligence algorithm that can identify precise hand gestures from the collected signals with high accuracy and reliability in order to extract new insights from these signals.
The device can accurately measure the thickness of the diaphragm with submillimeter accuracy when worn on the rib cage. In the clinic, diaphragm thickness is used to assess diaphragm dysfunction and forecast patient outcomes in ventilated conditions. By analyzing muscle motion, the researchers could also detect different breathing patterns, such as shallow and deep breaths. This capability could aid in the diagnosis of breathing problems like asthma, pneumonia, and chronic obstructive pulmonary disease ( COPD). The device was successful in a small-group trial in separating COPD sufferers ‘ breathing patterns from healthy participants’.
Muyang Lin, a postdoctoral researcher in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering at UC San Diego, said,” This demonstrates the technology’s potential for clinical applications in respiratory care.”
The wrist and hand movements are precisely tracked when the device is worn on the forearm. The team’s developed artificial intelligence algorithm allows the system to only recognize various hand gestures from ultrasound signals. The wrist’s 13 different degrees of freedom are covered by 10 finger joints and three rotational rotations. As a result, it can capture even slight wrist and finger movements with high sensitivity.
Participants tapped the robotic arm on their forearms to pipe water into beakers in proof-of-concept tests. In another demonstration, they used the device to play a virtual game, using wrist movements to control a virtual bird’s flight through obstacles. ” These demonstrations underscore the technology’s potential for prosthetics, gaming and other human-machine interface applications”, said study co-first author Wentong Yue, a Ph. Candidate for the D.C. at UC San Diego’s Aiiso Yufeng Li Family Department of Chemical and Nano Engineering.
Moving forward, the researchers plan to improve the technology’s accuracy, portability, energy efficiency and computational capabilities.
