Hemospec uses near-infrared spectroscopy (NIR) to analyse whole blood through its optical signature. The system measures how the sample absorbs light across the near-infrared region. That spectral signal carries information related to the molecular composition of the sample and can be used to estimate clinically relevant parameters.
In practice, the sensor captures the optical reading, and the analytical layer processes that signal using cloud-based
models. The aim is to extract useful information from the spectral pattern of the sample and translate it into a
structured result set. This is why the system combines photonics, software and analytical modelling in a single
architecture.
This approach makes it possible to work with a small blood sample, avoid reagent-heavy handling and bring a
broader panel of biomarkers closer to the point of care. In the current product framing, that includes
hematological parameters together with C-reactive protein, expanding the system beyond single-analyte
testing.
The current validation work shows stronger consistency in the
hematological panel, supported by larger sample sets and more
stable distributions, while some biochemical parameters still show
greater variability and require more cautious interpretation. That
distinction is important and should be explicit on the page.
MARD around 9%, with
accuracy ranging from 84% to
87%
MARD around 8–10%, with
accuracy ranging from 82% to
94%
MARD around 10–11%, with
accuracy ranging from 76%
to 80%
Classification accuracy around
73% to 80% in validated units
MARD around 10–13%, with
accuracy ranging from 61% to
63%
Texto sobre os papers e estudos no Hospital de Braga (Study 01 –
MyHEALTH Do IT e Study 02 – Internal Medicine Department of
Hospital de Braga)
Hemospec continues to evolve as an analytical platform. Current work
includes the expansion of the biomarker panel through targeted VIS/
NIR development in creatinine, total proteins, albumin, and additional
work around glucose and lactate.
Labinlight is advancing non-invasive glucose measurement
through transdermal optical analysis, combining dedicated
optical configurations with analytical models developed for
this new mode of sensing.
A second research direction is non-targeted analysis, where the full
spectral signature is used to identify clinically meaningful patterns
rather than focusing on a single biomarker alone. This approach opens
the platform to broader analytical models associated with complex
conditions, including sepsis, chronic kidney disease, iron-deficiency
anaemia and prognostic stratification. Internal research materials
already describe encouraging model performance across several of
these exploratory paths.
