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The intermittent hypoxia (IH) phenomenon is a subject of intensive examinations. In this study we examined whether it could be possible to distinguish the strength of the hypoxic stimulus given in IH cycles on the basis of observed changes in the breathing pattern. We investigated the ventilatory responses to five hypoxic-normoxic cycles (1 min hypoxia/3 min normoxia) in rabbits. Two different hypoxic stimuli were given: gas mixtures of 14% and 11% O2 in N2, each one in a separate run of IH. Ventilatory features: frequency (f), tidal volume (VT) and minute ventilation (VE) were analyzed using the algorithms of the pattern recognition theory. The probability of wrong classification was used as a criterion for the recognition quality evaluation. This probability can be estimated experimentally by calculating the percentage of misclassifications, i.e., an error rate (Er). When the features were analyzed alone, the VT offered the lowest misclassification rate of 19.3% and 10.3% in the stimulus and normoxic periods, respectively. However, using the single features measured during the stimulus and recovery phases allowed to decrease the error rate more than 2-fold, achieving 4.3% for VT. The best results were obtained for both phases associated with single cycles of IH. Suitable feature selection procedures enabled reducing the global misclassification rate to 0.7%. In conclusion, the pattern recognition approach may potentially be useful for controlling the stimulus strength in intermittent hypoxic training.

This study seeks to determine the effects on respiratory function of acute intermittent hypoxia. The experiments were performed on anesthetized, spontaneously breathing rabbits. The experimental protocol consisted of 5 one-minute episodes of hypoxia (14% O(2) in N(2)) interspersed with three-minute normoxic recovery periods. Ventilatory variables, minute ventilation (MV) and its tidal and frequency components, were derived from the continuously recorded airflow signal. We found that MV progressively increased with each next hypoxic-normoxic cycle; the increases were driven by both ventilatory components. Ventilatory augmentation concerned both the stimulus (hypoxic) and recovery (normoxic) periods, but it was significantly greater in the former. The augmented ventilation was sustained for up to 30 min after the last hypoxic run, which suggests the appearance of ventilatory long-term facilitation. The results demonstrate that acute intermittent hypoxia consisting of a few hypoxic-normoxic cycles is capable of inducing appreciable ventilatory changes. Such changes reflect plasticity of the respiratory motor output developing on a short-term basis during ongoing cycles of hypoxia, which, in the present study, correlated with the number of hypoxic cycle. Ventilatory augmentation in response to acute cyclic hypoxic episodes may give insights into the mechanisms of respiratory improvement by intermittent hypoxic training, increasingly used in both sports physiology and medicinal approaches.

In the present study we investigated whether classical or non-classical statistical methods might be useful in the diagnosis of early changes evoked by intermittent hypoxia (IH) in an experimental model. The experiments were carried out in anesthetized, spontaneously breathing rabbits. IH consisted of 5 cycles of breathing 14% O(2) in N(2) for 1 min interspersed with 3 min normoxic intervals. The following ventilatory variables were evaluated: frequency breathing, tidal volume, and minute ventilation. The results indicate that IH had a progressively stimulatory effect on the baseline ventilation and on the hypoxic ventilatory responses. Further, the algorithms of the pattern recognition theory might be a suitable tool for the recognition of early ventilatory effects of recurrent hypoxic events in the IH model. The recognition of IH states may be useful in clinical and sports medicine.

In this study, we examined the usefulness of arterial blood gas variables, as changed by the hypoxic stimulus, in discerning various experimentally-induced conditions of diaphragm weakness in anesthetized cats. We defined three experimental situations (models): (i) intact muscle, statistical Class I, (ii) four degrees of muscle dysfunction (after sequential diaphragm denervation), Classes II-V, and (iii) entirely paralyzed muscle, Class VI. Responses to a hypoxic stimulus in the above-mentioned conditions were evaluated by using the methods of the pattern recognition theory. We found that before the hypoxic stimulus, with partial but of different severity denervation of the diaphragm, the k-nearest neighbor classifier (k-NN) assigned 100% of the classified cases to Class II (one phrenic nerve rootlet cut). In contrast, during hypoxia only 67% of cases were assigned to Class II, the remaining being spread throughout other classes of muscle weakness. When one limits the procedure to the extreme classes: Class I (intact diaphragm) and Class VI (totally denervated diaphragm), the k-NN picks out 33% and 50% cases of bilateral diaphragm paralysis before and during hypoxia, respectively. We conclude that any remaining innervations of the diaphragm ensure the functionally optimal level of lung ventilation that may waver when hypoxia develops.

This work deals with the application of a pattern recognition method to distinguish the degree of diaphragm paralysis after gradual unilateral sections of phrenic nerve rootlets in anesthetized, spontaneously breathing cats. The data set consisted of the features that characterize breathing pattern and of phrenic nerve amplitude. The method called for stratification of 6-dimensional vectors into three classes: intact, partial, and complete unilateral phrenicotomy, which offers the possibility to construe the classification rule on the basis of the information contained in a set of feature vectors with the known class-membership. This method deals with the use of a distance function as a measure of similarity between two feature points. The results show that the degree of diaphragm paralysis could be recognized with the probability higher than 90%. Distinguishing the severity of diaphragmatic dysfunction and the compensatory strategies of the respiratory system, knowing only a handful of basic values describing breathing pattern, might have a practical meaning in respiratory emergencies.