Cardiac autonomic activity during sleep in high-altitude resident children compared with lowland residents

Study Objectives We aimed to characterize heart-rate variability (HRV) during sleep in Andean children native to high altitude (HA) compared with age, gender, and genetic ancestry-similar low-altitude (LA) children. We hypothesized that the hypoxic burden of sleep at HA could induce variation in HRV. As children have otherwise healthy cardiovascular systems, such alterations could provide early markers of later cardiovascular disease. Methods Twenty-six LA (14F) and 18 HA (8F) children underwent a single night of attended polysomnography. Sleep parameters and HRV indices were measured. Linear mixed models were used to assess HRV differences across sleep stage and altitude group. Results All children showed marked fluctuations in HRV parameters across sleep stages, with higher vagal activity during nonrapid eye movement sleep and greater variability of the heart rate during rapid eye movement (REM). Moreover, HA children showed higher very low-frequency HRV in REM sleep and, after adjusting for heart rate, higher low-to-high frequency ratio in REM sleep compared with children living at lower altitude. Conclusions We confirmed previous findings of a stage-dependent modulation of HRV in Andean children living at both HA and LA. Moreover, we showed subtle alteration of HRV in sleep in HA children, with intriguing differences in the very low-frequency domain during REM sleep. Whether these differences are the results of an adaptation to high-altitude living, or an indirect effect of differences in oxyhemoglobin saturation remains unclear, and further research is required to address these questions

Tidal breathing parameters measured by structured light plethysmography in children aged 2-12 years recovering from acute asthma/wheeze compared with healthy children

© 2018 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.Peer reviewedPublisher PD

Application of signal processing to respiratory cycle related EEG change (RCREC) in children

Sleep is an important part of everyday life. It directly affects daytime cognition and general performance. In children, sleep is a crucial requirement for growth and learning and lack of sleep may manifest itself as a long lasting developmental deficit. Sleep disorders which disrupt the normal continuity of sleep therefore benefit from early identification and treatment. A common cause of sleep disruption is sleep disordered breathing which can be associated with frequent arousals from sleep. Many relevant areas of sleep research continue to generate new and interesting findings utilising biosignals such as EEGs. Respiratory cycle related EEG change (RCREC) is a good example of this. The method for quantification of RCREC relies on the appropriate application of signal processing and the signals involved in the procedure are polysomnographic. Furthermore, RCREC is thought to reflect morbid micro-arousals in sleep and is hence also of clinical importance. Given that the field of RCREC research is a recently established one, there is much room for constructive investigation. The current state of RCREC research is therefore expanded in this thesis. The method for calculation of respiratory cycle related EEG change (RCREC) is replicated and expanded in this project. Shortcomings of the method have been identified and accounted for where appropriate. In particular, the sensitivity of RCREC to airflow signal segmentation is addressed and alternative segmentation approaches are suggested. The general influence of airflow segmentation on RCREC is investigated and a mathematical explanation for RCREC sensitivity is given. Additionally, the ability of RCREC related parameters to predict daytime cognitive functions is assessed. Results suggest that RCREC parameters are capable of predicting quality of episodic memory, power (speed) of attention and internal processing speed

Measuring changes in chest wall motion after lung resection using structured light plethysmography: a feasibility study.

OBJECTIVES We describe the use of structured light plethysmography (SLP)-a novel, non-contact, light-based technique for measuring tidal breathing-among a cohort of patients undergoing lung resection. In this feasibility study, we examined whether changes in chest wall motion or in asynchrony between regions of the thoraco-abdominal wall could be identified after surgery. METHODS Fifteen patients underwent wedge resection (n = 8) or lobectomy (n = 7). All patients underwent two SLP assessments (before surgery and on Day 1 post-surgery). Each assessment captured data during 5 min of quiet (tidal) breathing. RESULTS When data were averaged across all patients, motion on the operated side of the thorax was significantly reduced after surgery (mean change from presurgery ± standard deviation: -14.7 ± 16.5%, P = 0.01), while motion on the non-operated side increased (15.9 ± 18.5%, P = 0.01). Thoraco-abdominal asynchrony also increased (mean change ± standard deviation: 43.4 ± 55.1%, P = 0.01), but no significant difference was observed in right-left hemi-thoracic asynchrony (163.7 ± 230.3%, P = 0.08). When analysed by resection type, lobectomy was associated with reduced and increased motion on the operated and non-operated side, respectively, and with an increase in both right-left hemi-thoracic and thoraco-abdominal asynchrony. No significant changes in motion or asynchrony were identified in patients who underwent wedge resection. CONCLUSIONS SLP was able to detect changes in chest wall motion and asynchrony after thoracic surgery. Changes in this small group of patients were consistent with the side of the incision and were most apparent in patients undergoing lobectomy

Evaluation of the agreement of tidal breathing parameters measured simultaneously using pneumotachography and structured light plethysmography

Structured light plethysmography (SLP) is a noncontact, noninvasive, respiratory measurement technique, which uses a structured pattern of light and two cameras to track displacement of the thoraco–abdominal wall during tidal breathing. The primary objective of this study was to examine agreement between tidal breathing parameters measured simultaneously for 45 sec using pneumotachography and SLP in a group of 20 participants with a range of respiratory patterns (“primary cohort”). To examine repeatability of the agreement, an additional 21 healthy subjects (“repeatability cohort”) were measured twice during resting breathing and once during increased respiratory rate (RR). Breath‐by‐breath and averaged RR, inspiratory time (tI), expiratory time (tE), total breath time (tTot), tI/tE, tI/tTot, and IE50 (inspiratory to expiratory flow measured at 50% of tidal volume) were calculated. Bland–Altman plots were used to assess the agreement. In the primary cohort, breath‐by‐breath agreement for RR was ±1.44 breaths per minute (brpm). tI, tE, and tTot agreed to ±0.22, ±0.29, and ±0.32 sec, respectively, and tI/tE, tI/tTot, and IE50/IE50SLP to ±0.16, ±0.05, and ±0.55, respectively. When averaged, agreement for RR was ±0.19 brpm. tI, tE, and tTot were within ±0.16, ±0.16, and ±0.07 sec, respectively, and tI/tE, tI/tTot, and IE50 were within ±0.09, ±0.03, and ±0.25, respectively. A comparison of resting breathing demonstrated that breath‐by‐breath and averaged agreements for all seven parameters were repeatable (P > 0.05). With increased RR, agreement improved for tI, tE, and tTot (P ≤ 0.01), did not differ for tI/tE, tI/tTot, and IE50 (P > 0.05) and reduced for breath‐by‐breath (P < 0.05) but not averaged RR (P > 0.05)

Respiratory cycle related EEG changes: modified respiratory cycle segmentation

Respiratory cycle related EEG change (RCREC) is characterized by significant relative EEG power changes within different stages of respiration during sleep. RCREC has been demonstrated to predict sleepiness in patients with obstructive sleep apnoea and is hypothesized to represent microarousals. As such RCREC may provide a sensitive marker of respiratory arousals. A key step in quantification of RCREC is respiratory signal segmentation which is conventionally based on local maxima and minima of the nasal flow signal. We have investigated an alternative respiratory cycle segmentation method based on inspiratory/expiratory transitions. Sixty two healthy paediatric participants aged 7-17 (11.6±3) years (35M:27F) were recruited through staff of local universities in Bolivia. Subjects underwent attended polysomnography on a single night (Compumedics PS2 system). Studies were sleep staged according to standard criteria. C3/A2 EEG channel and timelocked nasal flow (thermistor) were used in RCREC quantification. Respiratory cycles were segmented using both the conventional and novel (transition) methods and differences in RCREC derived from the two methods were compared in each frequency band. Significance of transition RCREC as measured by Fisher's F value through Analysis of Variance (ANOVA) was found to be significantly higher than the conventional RCREC in all frequency bands (P<0.05) but beta. This increase in statistical significance of RCREC as demonstrated with the novel transition segmentation approach suggests better alignment of the respiratory cycle segments with the underlying physiology driving RCREC