Sensory stimulation activates both motor and sensory components of the swallowing system.

Volitional swallowing in humans involves the coordination of both brainstem and cerebral swallowing control regions. Peripheral sensory inputs are necessary for safe and efficient swallowing, and their importance to the patterned components of swallowing has been demonstrated. However, the role of sensory inputs to the cerebral system during volitional swallowing is less clear. We used four conditions applied during functional magnetic resonance imaging to differentiate between sensory, motor planning, and motor execution components for cerebral control of swallowing. Oral air pulse stimulation was used to examine the effect of sensory input, covert swallowing was used to engage motor planning for swallowing, and overt swallowing was used to activate the volitional swallowing system. Breath-holding was also included to determine whether its effects could account for the activation seen during overt swallowing. Oral air pulse stimulation, covert swallowing and overt swallowing all produced activation in the primary motor cortex, cingulate cortex, putamen and insula. Additional regions of the swallowing cerebral system that were activated by the oral air pulse stimulation condition included the primary and secondary somatosensory cortex and thalamus. Although air pulse stimulation was on the right side only, bilateral cerebral activation occurred. On the other hand, covert swallowing minimally activated sensory regions, but did activate the supplementary motor area and other motor regions. Breath-holding did not account for the activation during overt swallowing. The effectiveness of oral-sensory stimulation for engaging both sensory and motor components of the cerebral swallowing system demonstrates the importance of sensory input in cerebral swallowing control.

Identifying airway obstructions using photoplethysmography (PPG).

OBJECTIVE: Central and obstructive apneas are sources of morbidity and mortality associated with primary patient conditions as well as secondary to medical care such as sedation/analgesia in post-operative patients. This research investigates the predictive value of the respirophasic variation in the noninvasive photoplethysmography (PPG) waveform signal in detecting airway obstruction. METHODS: PPG data from 20 consenting healthy adults (12 male, 8 female) undergoing anesthesia were collected directly after surgery and before transfer to the Post Anesthesia Care Unit (PACU). Features of the PPG waveform were calculated and used in a neural network to classify normal and obstructive events. RESULTS: During the postoperative period studied, the neural network classifier yielded an average (+/-standard deviation) 75.4 (+/-3.7)% sensitivity, 91.6 (+/-2.3)% specificity, 84.7 (+/-3.5)% positive predictive value, 85.9 (+/-1.8)% negative predictive value, and an overall accuracy of 85.4 (+/-2.0)%. CONCLUSIONS: The accuracy of this method shows promise for use in real-time monitoring situations.