Incommunicado and in pain: IR to the rescue

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  • Published: Nov 1, 2017
  • Author: David Bradley
  • Channels: Infrared Spectroscopy
thumbnail image: Incommunicado and in pain: IR to the rescue

Functional pain assessment

Toward a functional near-infrared spectroscopy-based monitoring of pain assessment for nonverbal patients.

Functional near-infrared spectroscopy (fNIRS) could offer hope to non-verbal patients who are suffering from pain allowing their carers and clinicians to observe episodes of pain even when the patient cannot communicate the problem.

R Fernandez Rojas and X Huang of the University of Canberra, Human-Centred Technology Research Centre, ESTEM Faculty, in Canberra, Australia, and KL Ou of the Taipei Medical University Hospital, Taiwan and also the Taipei Medical University-Shuang Ho Hospital and 3D Global Biotech Inc explain how sophisticated neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have already been used to assess neuronal function in response to nociception and pain. They further explain that machine learning approaches have even been used in other research to predict different cognitive tasks. The team is now working towards using those machine learning models with fNIRS measurements of signals due to oxyhaemoglobin and how they correlate with temperature level (cold or hot) and the corresponding pain intensity (low or high).

Modelling the pain response

In order to build a model of fNIRS response to hot and cold pain, the team recruited 18 healthy subjects (15 men and 3 women) of mean age approximately 32 years. "The classification model is based on the bag-of-words approach," the team explains. This is a histogram representation used in document classification based on the frequencies of extracted words and adapted for time series. They then used the fNIRS to carry out classification of responses in the somatosensory region defined as the region of interest in the study. They were able to obtain accuracy of over 90% predicting whether or not a volunteer was experiencing temperature pain, hot or cold based on the fNIRS data.

"These results indicate potential applications of fNIRS in the development of a physiologically based diagnosis of human pain that would benefit vulnerable patients who cannot self-report pain," the team explains. Obviously, the ability to self-report one's pain is the definitive method of communicating pain to clinicians and healthcare workers. The individual patient is truly the only person who knows exactly how much one is suffering. However, non-verbal patients often cannot self report. Such patients might include those with motor neuron disease, cerebral palsy, paralysis, dementia, those with special educational needs, post-operative patients having undergone head, neck or throat surgery, and many others.


"Pain assessment is not a trivial task and some factors should be taken into consideration to achieve a reliable estimate of it," the team explains. "For instance, pain perception can be affected by age, sex, weight, psychological state, or cultural background." For non-verbal patients where there is no possibility of self-reporting, an analytical approach is likely to be the best alternative. "fNIRS is a technique capable of identifying cortical hemodynamic changes in response to chemical, temperature, and pressure noxious stimuli," the team reports. It has the additional benefit of being far more convenient and less costly than an fMRI or positron emission tomography (PET) as well as not using putatively harmful ionizing radiation.

Related Links

J Biomed Opt 2017, 22, 1-12: "Toward a functional near-infrared spectroscopy-based monitoring of pain assessment for nonverbal patients."

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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