Summary:
UCLA researchers in the Department of Electrical and Computer Engineering have developed an instrument that detects and encrypts a user’s biochemical and biometric data with only a touch of the finger.
Background:
Human machine interfaces (HMI), such as touchscreens and keyboards, are able to connect users to machines, systems, and devices. However, HMI has not been widely used in the medical field for diagnostics due to the lack of bio-perception and interpretation capabilities as well the difficulty in easily encrypting and decrypting biometric data. Therefore, there is a need for a cryptographic bio-human machine interface (CB-HMI) capable of translating the user’s touch-based entries into encrypted biochemical and biophysical indices.
Innovation:
UCLA researchers in the Department of Electrical and Computer Engineering have developed a cryptographic bio-human machine interface (CB-HMI) that is capable of sensing biochemical and biophysical indices via touch. The device uses chemical sensors and inference algorithms to non-invasively acquire and encrypt biochemical indices such as circulating molecules that partition onto the skin. Furthermore, the CB-HMI hosted physical sensors and associated algorithms to simultaneously acquire the user’s heart rate, blood oxygen level, and fingerprint minutiae pattern. The bio-perception achieved by the CB-HMI can aid on comprehensive and deep awareness of the individuals’ psychophysiological state and needs. Additionally, the acquired data can be encrypted and decrypted in-situ so that the user’s biometric data is protected while still being easily accessible to the user.
Potential Applications:
- Biomarker detection
- Diagnostic tool
- Biophysical sensor
- Medication indicator
- Biometric reader
Advantages:
- Bio-perception
- External biosensor
- Fast access to data
- Access via touch
Development to Date:
First demonstration of CB-HMI for chemo/biosensing in user’s perspiration samples.
Related Papers:
Lin, S.; Wang, B.; Zhao, Y.; Shih, X.; Cheng, X.; Yu, W.; Hojaiji, H.; Lin, H.; Hoffman, C.; Ly, D.; Tan, J.; Chen, Y.; Di Carlo, D.; Milla, C.; Emaminejad, S. “Natural Perspiration Sampling and In-Situ Electrochemical Analysis with Hydrogel Micropatches for User-Identifiable and Wireless Chemo/Bio-Sensing” ACS Sensors, 5(1), 93-102, 2019.