July 14, 2026, 11:53 am | Read time: 4 minutes
Dopamine plays an important role in movement, motivation, and emotional processes. Changes in this neurotransmitter are linked to diseases such as Parkinson’s, Alzheimer’s, schizophrenia, and depression. Researchers from Brazil have now developed a novel sensor designed to measure dopamine easily through tear fluid.
Sensor Measures Dopamine in Tears
The central finding of the study conducted at the Federal University of Pelotas was that the newly developed sensor could reliably and very sensitively detect dopamine in synthetic tear fluid. One variant proved particularly successful. According to the researchers, the sensor provided precise measurements and detected even very low concentrations of dopamine. This technology could potentially lay the foundation for simple and noninvasive measurement methods in the future.
How the Study Was Conducted
This work is not a clinical study with patients but an experimental laboratory study. The researchers aimed to determine whether dopamine could be detected sensitively and as simply as possible using a newly developed sensor.1
For the laboratory study, the scientists developed several sensor models based on laser-induced graphene, a laser-produced, highly conductive carbon material, and compared their performance. They investigated, among other things, whether an additional coating with nickel nitrate and urea improved measurement accuracy. The sensors were tested in both a standard solution and synthetic tear fluid, which was intended to closely mimic real conditions.
Dopamine Levels in Artificial Tears Very Precisely Detected
The best results were achieved by the sensor variant with a combination of nickel nitrate and urea. It had the largest electrochemically active surface and responded particularly sensitively to dopamine. The reliability was also high: repeated measurements yielded nearly identical results, and the sensors provided ideal measurements for at least a week. In synthetic tear fluid, the recovery rates were nearly 100 percent, meaning the actual dopamine levels were very precisely detected.
According to the researchers, the technology could be of interest for so-called point-of-care applications in the future, meaning quick measurements directly in doctors’ offices or other medical facilities.
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The researchers see their sensor primarily as an important technical proof of concept. The results show that dopamine can fundamentally be measured through tear fluid. “We want to enable the ultra-early detection of neurological diseases and thus create opportunities for clinical interventions before severe symptoms occur,” says study leader Neftalí Lênin Villarreal Carreño in a press release.2 This could support the development of simple and cost-effective measurement systems in the long term. The approach is particularly interesting because no blood sample or other more burdensome procedures would be necessary for the measurement. Instead, a small tear sample could suffice in the future.
Since altered dopamine levels are associated with Parkinson’s, Alzheimer’s, schizophrenia, and depression, such measurement methods could play a role in the research or monitoring of these diseases in the future.
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Assessment of the Study and Possible Limitations
A strength of the study is that the sensor was extensively tested. The researchers compared various material combinations and examined the accuracy, reliability, and durability of the system, among other things. Important measurement values such as detection limits and error rates were also transparently provided.
However, there are also limitations. The investigation took place exclusively in the laboratory and not on patients. Most tests were conducted with artificially produced tear fluid. Therefore, it is still unclear how well the sensor works under real conditions with human tears.
Additionally, there is currently no data on whether the technology is actually suitable for medical diagnoses. Furthermore, the sensor’s performance declined over time. Therefore, further investigations are necessary for long-term use.