Wireless, battery-free sensor could advance early disease detection

Michigan State University researcher Chunqi Qian is developing a wireless, battery-free sensor designed to detect changes in brain and heart activity and support earlier diagnosis of neurological and cardiovascular diseases.

Qian, an associate professor in the Department of Radiology in the College of Osteopathic Medicine, is studying how the device could measure abnormal electrical activity associated with Parkinson’s disease, Alzheimer’s disease and arrhythmias. The sensor also could continuously monitor patients outside clinical settings.

The technology is described in “WISDEM: A Hybrid Wireless Integrated Sensing Detector for Simultaneous EEG and MRI,” published in Nature Methods. It harvests energy from radio frequency signals in its surroundings and requires only a small amount of power to operate as an FM broadcaster. Because it does not use a battery, recordings would not be interrupted for battery replacement.

The sensor is designed to work inside or outside a magnetic resonance imaging, or MRI, scanner. Inside the machine, the scanner serves as a receiver. Outside it, the sensor’s signal can be detected with a low-cost FM receiver.

“In this scenario, the patient doesn’t need to do repetitive scanning,” Qian said. After an initial scan, the patient could return home while the sensor operates for an extended period. If it detected unusual activity, the device could alert the patient to return for more advanced imaging.

MRI shows vascular activity, while electrodes or specialized catheters measure electrical signals. Qian wants to collect both types of information simultaneously, combining MRI’s structural images with real-time data about the body’s electrical activity.

Conventional electrophysiology relies on wired electrodes, which can cause electromagnetic interference inside an MRI scanner. Existing methods for synchronizing electrophysiology recordings with MRI also can be complex and raise safety concerns, including the potential for wires to overheat.

The sensor also could have cardiology applications, including diagnosing arrhythmias. An electrocardiogram captures heart activity during a brief clinical test, but Qian wants to record patients’ heart signals as they work, sleep and go about daily activities.

“To do that, you have to have a lightweight mobile sensor to record, upload and transmit all that information in real time,” he said.

Animal testing and commercialization

Qian is collaborating with the MSU College of Veterinary Medicine to test the sensor on companion animals. Pet owners may make repeated trips to MSU’s veterinary facilities for electrocardiogram measurements, costing time and money.

Existing sensors generally store information that veterinarians retrieve after a device is returned, Qian said. His team is configuring its sensor to broadcast continuously so veterinarians can monitor an animal’s health in real time and intervene promptly when needed.

After testing in companion animals, the team hopes to pursue human applications, including wearable sensors that capture complete heart waveforms. Qian said the technology eventually could measure electrical activity from the brain, eyes and muscles. Those signals are assessed through electroencephalograms, electro-oculograms and electromyograms, respectively.

The research was partially supported by a National Institutes of Health BRAIN Initiative grant and is now supported by a National Science Foundation grant through June 30, 2027. Qian also is working with the MSU Research Foundation to explore commercialization through Michigan Translational Research and Commercialization grants or private investment. The team is interested in partnering with companies to test and validate the sensors in community settings.

Qian also is exploring agricultural and environmental uses. The sensor could track an insect’s position and physiology inside a bee colony, potentially improving honey production. It also could continuously monitor temperature, humidity or chemical concentrations by converting measurements into electrical signals and broadcasting the data wirelessly.

Read the original feature story on the MSU College of Osteopathic Medicine website.