Fibromyalgia syndrome (FMS) is characterized by longstanding multifocal pain with generalized allodynia/hyperalgesia. There are several treatment methods but none has been specifically approved for this application. We conducted a randomized controlled study to evaluate the effect of hyperbaric oxygen (HBO) therapy in FMS (HBO group: n = 26; control group: n = 24). Tender points and pain threshold were assessed before, and after the first and fifteenth sessions of therapy. Pain was also scored on a visual analogue scale (VAS). There was a significant reduction in tender points and VAS scores and a significant increase in pain threshold of the HBO group after the first and fifteenth therapy sessions. There was also a significant difference between the HBO and control groups for all parameters except the VAS scores after the first session. We conclude that HBO therapy has an important role in managing FMS.

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We address the problem of prototypical waveform extraction in cognitive experiments using functional near-infrared spectroscopy (fNIRS) signals. These waveform responses are evoked with visual stimuli provided in an oddball type experimental protocol. As the statistical signal-processing tool, we consider the linear signal space representation paradigm and use independent component analysis (ICA). The assumptions underlying ICA is discussed in the light of the signal measurement and generation mechanisms in the brain. The ICA-based waveform extraction is validated based both on its conformance to the parametric brain hemodynamic response (BHR) model and to the coherent averaging technique. We assess the intra-subject and inter-subject waveform and parameter variability.

Abstract-Functional near-infrared spectroscopy (fNIRS) is an emerging technique for monitoring the concentration changes of oxy-and deoxy-hemoglobin (oxy-Hb and deoxy-Hb) in the brain. An important consideration in fNIRS-based neuroimaging modality is to conduct group-level analysis from a set of time series measured from a group of subjects. We investigate the feasibility of multilevel statistical inference for fNIRS. As a case study, we search for hemodynamic activations in the prefrontal cortex during Stroop interference. Hierarchical general linear model (GLM) is used for making this multilevel analysis. Activation patterns both at the subject and group level are investigated on a comparative basis using various classical and Bayesian inference methods. All methods showed consistent left lateral prefrontal cortex activation for oxy-Hb during interference condition, while the effects were much less pronounced for deoxy-Hb. Our analysis showed that mixed effects or Bayesian models are more convenient for faithful analysis of fNIRS data. We arrived at two important conclusions. First, fNIRS has the capability to identify activations at the group level, and second, the mixed effects or Bayesian model is the appropriate mechanism to pass from subject to group-level inference.Index Terms-General linear model (GLM), near-infrared spectroscopy, statistical inference, Stroop task.

It has been hypothesised by many researchers that the spike activity signals of the stomach are responsible for triggering peristaltic contractions. Since most gastric motility disorders include an abnormality in the contraction pattern, it is very important to access this information non-invasively. The aim in this study is to use abdominal electrogastrogram (EGG) signals to detect the spike activity signals generated by the serosa of the stomach, and hence provide clinicians with a better method to monitor the motility state of the stomach. Through second and third-order spectral estimations performed on the serosal data obtained from canine experiments, it was concluded that the spike activity in serosal signals occupies a frequency range of 50-80 cycles per minute. An increase in this frequency range during strong antral contractions was observed both in the serosal and cutaneous power spectra. By using the 'continuous wavelet transform' with respect to a modified Morlet wavelet, the spike activity signals generated from the serosa of the stomach can be detected and quantified in time from the cutaneous EGG records. During phase III contraction episodes, a detection accuracy of up to 96% from the cutaneous EGG recordings was calculated based on the scored serosal spike activities simultaneously recorded.