Back

Circuit-free, optoelectronic sensing of electrodermal activities based on photon recycling of a micro-LED

Sheng, X.

2020-07-06 bioengineering
10.1101/2020.07.05.188391 bioRxiv
Show abstract

Conventional epidermal electronics integrate multiple power harvesting, signal amplification and data transmission components for wireless biophysical and biochemical signal detection. This paper reports the real-time electrodermal activities can be optically captured using a microscale light-emitting diode (micro-LED), eliminating the need for complicated sensing circuit. Owing to its strong photon-recycling effects, the micro-LEDs photoluminescence (PL) emission exhibits a superlinear dependence on the external resistance. Taking advantage of this unique mechanism, the galvanic skin response (GSR) of a human subject is optically monitored, and it demonstrates that such an optoelectronic sensing technique outperforms a traditional tethered, electrically based GSR sensing circuit, in terms of its footprint, accuracy and sensitivity. This presented optoelectronic sensing approach could establish promising routes to advanced biological sensors.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Advanced Functional Materials
○ 46 papers in training set
Top 0.1%
12.8%
Similar papers in this journal
2
Advanced Science
○ 286 papers in training set
Top 0.2%
11.8%
Similar papers in this journal
3
ACS Sensors
● 49 papers in training set
Top 0.1%
10.9%
Similar papers in this journal
4
Advanced Materials
○ 56 papers in training set
Top 0.1%
7.8%
Similar papers in this journal
5
Biosensors and Bioelectronics
○ 57 papers in training set
Top 0.2%
5.4%
Similar papers in this journal
6
Science Advances
● 1243 papers in training set
Top 5%
5.1%
50% of probability mass above
7
Nature Communications
○ 5641 papers in training set
Top 32%
4.0%
8
Small
○ 78 papers in training set
Top 0.4%
3.2%
9
Nano Letters
● 71 papers in training set
Top 0.4%
3.2%
10
ACS Nano
● 113 papers in training set
Top 0.9%
2.4%
11
Advanced Materials Technologies
○ 29 papers in training set
Top 0.2%
2.4%
12
Angewandte Chemie International Edition
○ 93 papers in training set
Top 0.7%
2.1%
13
ACS Applied Bio Materials
● 24 papers in training set
Top 0.3%
2.1%
14
Analytical Chemistry
● 218 papers in training set
Top 1%
2.1%
15
ACS Applied Materials & Interfaces
● 39 papers in training set
Top 0.6%
1.7%
16
Light: Science & Applications
○ 16 papers in training set
Top 0.2%
1.7%
17
Nature Photonics
○ 10 papers in training set
Top 0.1%
1.5%
18
Communications Biology
○ 993 papers in training set
Top 22%
1.1%
19
Scientific Reports
○ 3612 papers in training set
Top 64%
1.1%
20
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 37%
1.1%
21
Optica
● 27 papers in training set
Top 0.2%
1.0%
22
ACS Photonics
● 13 papers in training set
Top 0.2%
1.0%
23
Optics Express
● 26 papers in training set
Top 0.3%
1.0%
24
Advanced Healthcare Materials
○ 85 papers in training set
Top 1%
1.0%
25
Advanced Biology
○ 29 papers in training set
Top 0.8%
0.8%
26
Photoacoustics
○ 12 papers in training set
Top 0.3%
0.8%
27
Lab on a Chip
● 96 papers in training set
Top 1%
0.6%
28
Journal of Neural Engineering
○ 221 papers in training set
Top 2%
0.6%
29
Nature Nanotechnology
○ 32 papers in training set
Top 0.7%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.