One of the devices’ limitations is that in order to gather enough lactate to meaningfully analyze data, subjects need to perform exercise or other physical activity that get people to sweat. In future work, researchers will aim to do away with this requirement.
“The next step is also to integrate electronics into the sensor,” Yuchen Xu said.
The team is also working on processing the data on the device itself. Ultimately, the goal is to transmit the processed data wirelessly to a computer or a smartphone. In-ear sensors could also gather additional data, such as oxygen saturation levels and glucose levels.
The researchers envision this work to lead to new therapies.
“Auditory neurofeedback coupling the measured brain signals with sound played by the device in the ear may enable potentially far-reaching new therapeutic advances for active remediation of debilitating neurological disorders, such as tinnitus for which currently no effective treatment is available,” Cauwenberghs said.
Characterizing the sensors
Throughout the study, researchers conducted extensive experiments to validate the efficacy of the sensors.
They characterized the electrode performance as well as several prominent brain signal patterns, including alpha modulation and auditory steady-state responses, in addition to electrooculography (EOG) for the electrophysiological sensors.
They characterized the sensitivity, selectivity, and long-term stability of lactate sensors.
They also characterized crosstalk between sensors, mechanical stability, and environmental stability for the integrated sensors.
“The ear canal has been relatively underexplored within the wearable technology community,” said Sheng Xu, a faculty member in the Jacobs School Department of NanoEngineering. “This work demonstrates the potential of continuous sensing to capture valuable physical and chemical signals from the ear canal thereby paving the way for numerous exciting opportunities in the field of wearables.”
Unobtrusive in-ear integrated physiological and metabolic sensors for continuous brain-body activity monitoring
UC San Diego Shu Chien-Gene Lay Department of Bioengineering: Yuchen Xu, Akshay Paul, Min Lee, Abhinav Uppal, William Chen, Stephen Deiss, Gert Cauwenberghs
UC San Diego Department of NanoEngineering and Chemical Engineering: Ernesto De la Paz, Kuldeep Mahato, Juliane R. Sempionatto, Nicholas Tostado, Muyang Lin, Srishty Dua, Lu Yin, Sheng Xu, Joseph Wang
UC San Diego Department of Electrical and Computer Engineering: Gopabandhu Hota, Brian L. Wuerstle, Patrick Mercier
This research was performed at, and supported by, the Center for Wearable Sensors at the UC San Diego Jacobs School of Engineering.