Changes in Heart Rate in Response to Heat Pressure and Neural Stimulation

Pain, a subjective sensation, has been increasingly studied, as it has been recognized as an important factor in patients' recovery and quality of life. Pain is charted today as one of the vital signs. For standardization, pain is charted by a number from 0 to 10 indicating its level. The most common practiced pain assessment tool today is the VAS- Visual Analog Score (facial or numerical), by which the patient himself indicates the level of the pain he or she endures. It has been found that the correlation between the reported pain by the patient and the assessed pain by the caregivers or the medical personnel becomes poor as pain intensifies.

Objective assessment of anesthesia using the heart rate and its spectral analyses was done in the past. By using this modality, works on neonatal pain were conducted. In adults, works have shown that there is possibility to assess pain using this modality, though no repeated proof for its ability to detect pain was published.

We know that physiological signals such as ECG consist of mixtures of variety of patterns and phenomena accruing at different patterns and time points. Traditional analysis methods are designed and optimized to handle signals that include a single class of patterns such as pure harmonics or piece-wise constant functions. However, such basic operations that use a single representation method usually yield mediocre results when applied to real complex biological signals as ECG and EEG especially in the case where the Signal to Noise Ratio (SNR) is very low. Recent trends in digital signal processing (DSP) use the novel idea of merging several different representation methods to create a so called over-complete dictionary, examples of this approach include the Matching Pursuit algorithm and the Basis Pursuit algorithm. We intend to develop and apply the novel signal processing tools to the ECG signals for the first time. We believe that such tools have the potential to provide much better insight of the signal basic components and their relation to pain.