Identification of Respiratory Pauses during Swallowing by Unconstrained Measuring Using Millimeter Wave Radar.

Breathing temporarily pauses during swallowing, and the occurrence of inspiration before and after these pauses may increase the likelihood of aspiration, a serious health problem in older adults. Therefore, the automatic detection of these pauses without constraints is important. We propose methods for measuring respiratory movements during swallowing using millimeter wave radar to detect these pauses. The experiment involved 20 healthy adult participants. The results showed a correlation of 0.71 with the measurement data obtained from a band-type sensor used as a reference, demonstrating the potential to measure chest movements associated with respiration using a non-contact method. Additionally, temporary respiratory pauses caused by swallowing were confirmed by the measured data. Furthermore, using machine learning, the presence of respiring alone was detected with an accuracy of 88.5%, which is higher than that reported in previous studies. Respiring and temporary respiratory pauses caused by swallowing were also detected, with a macro-averaged F1 score of 66.4%. Although there is room for improvement in temporary pause detection, this study demonstrates the potential for measuring respiratory movements during swallowing using millimeter wave radar and a machine learning method.

Novel Outcome Analysis Tool for Hypoglossal Nerve Stimulator Sensor Lead Function and Comparison by Incision Type (2 Versus 3).

OBJECTIVE: No reported outcome measures have been established to evaluate sensor lead function in the hypoglossal nerve stimulator (HNS). This study describes the development of novel functional outcome measures for intraoperative sensor electrode function and compares 2-incision and 3-incision outcomes for HNS. METHODS: A retrospective cohort study of 100 consecutive patients who underwent HNS between June 2019 and September 2021. Demographic information, intraoperative findings, and immediate postoperative outcomes were recorded. Structured parameters were developed to compare intraoperative waveforms with six outcome measures utilized: waveform syncing, waveform amplitude, sensory current leakage, shark-fin morphology, cardiac artifact, and overall impression. Two sleep surgeons and two sleep medicine specialists compared all waveforms in a blinded fashion and assigned scores on the Likert Scale. RESULTS: The cohort included 50 three-incision and 50 two-incision patients. Age, gender, average body mass index, comorbidity profiles, and sleep endoscopy findings did not significantly differ between the two groups. No major complications occurred. The interclass-correlation-coefficient was greater than 0.7 for all comparisons (good to very good interrater reliability). There was no difference in waveform amplitude, cardiac artifact, sensory current leakage, or shark-fin morphology between the two groups. Waveform syncing and overall impression were statistically better in the 2-incision cohort. CONCLUSIONS: This study is the first to define a structured method of HNS sensor electrode outcome measurement and showed consistent measures by surgeons and sleep medicine specialists. This article supports the transition to the 2-incision technique among surgeons for placement of the sensor lead. Consideration should be given to utilizing this novel tool in the clinical/research setting and validating these measures moving forward. LEVEL OF EVIDENCE: 3 Laryngoscope, 133:423-430, 2023.

Use of carbon nanotube sensor for detecting postoperative abnormal respiratory waveforms.

BACKGROUND: This feasibility study aimed to detect respiratory waveforms from thoracic movements and evaluate if postoperative complications could be predicted using a carbon nanotube sensor. METHODS: Fifty patients who underwent lung resection for lung tumors were enrolled. The lung monitoring system of the carbon nanotube sensor was placed on bilateral chest walls across the 6th-9th ribs to measure chest wall motion. We examined the respiratory waveform in relation to surgical findings, postoperative course, and complications using Hilbert transform and Fast Fourier Transform (FFT). RESULTS: Of 50 patients (37 males, 13 females), 22 were included in the normal lung function group and 28 were included in the low lung function group. The respiratory rate and waveform indicated a regular pattern in the normal lung function group and the respiratory rate could be detected. Conversely, irregular respiratory pattern was detected in 70% of patients in the low lung function group. There was no significant different overall envelope peak value between operated side and non-operated side (0.195±0.05 and 0.18±0.06). In contrast, there was significantly high peak value in the presence of postoperative complications (P<0.05). And there was a significantly higher peak value in air leakage presence than air leakage absence in operated side (P=0.045). CONCLUSIONS: The present study confirmed the feasibility of the sensor. It is promising in visualizing the respiratory state and detecting respiratory changes postoperatively.

The predictive value of Holter monitoring in the risk of obstructive sleep apnea.

BACKGROUND: Patients with obstructive sleep apnea (OSA) often present with cardiovascular symptoms. Holter monitors were reported to predict sleep apnea, though were rarely used in everyday clinical practice. In this study, by comparing Holter monitoring to polysomnography (PSG), we try to find out an operable way for clinicians to use Holter to predict OSA risk. METHODS: Patients (n=63) suspected of OSA underwent Holter monitoring with concurrent PSG at a sleep center. Respiration and heart rate variability (HRV) indices were calculated from the Holter and compared with PSG indices. RESULTS: The sensitivity of the Holter-derived respiratory waveform for OSA was 90.0%, and the specificity was 82.6%. The time domain indices including standard deviation of all NN intervals during 24 hours, mean of standard deviation of the averages of NN intervals in all 5-minute segments, square root of the mean squared differences of successive NN intervals, percentage of beat-to-beat NN interval differences that were more than 50 milliseconds, and the frequency domain index of high frequency decreased in participants with OSA and correlated with the PSG derived indices including apnea-hypopnea index (AHI), oxygen reduction index (ODI) and nadir SaO2. Logistic regression showed that standard deviation of all NN intervals during 24 hours and gender could predict the risk of OSA (P<0.001), with a sensitivity for diagnosing moderate to severe OSA of 87.5% and could accurately distinguish the risk of OSA in 77.8% of patients. Males with standard deviation of all NN intervals during 24 hours ≤177 ms or females with standard deviation of all NN intervals during 24 hours ≤80.9 ms were considered to be at high risk for OSA. CONCLUSIONS: Commercial and common parameters from Holter monitoring could predict the risk of OSA with high sensitivity. Therefore, the risk of OSA may be assessed using the Holter examination to improve the diagnosis and treatment rate of OSA.

[Impact of Respiratory Waveform on Gate Signal Generation on Respiratory Gated Irradiation and Evaluation Method of Respiratory Waveform to Be Used].

PURPOSE: The respiratory gated irradiation using the real-time position management system (RPM) was used to clarify the generation of the gated signal when the respiration waveform changed, and also the evaluation method of the respiration waveform was also examined. METHODS: The respiratory waveform was changed using a moving phantom. Respiratory waveform was analyzed from the data recorded in RPM, and the out-of-phase gated rate was examined. Analysis was made by focusing on the coefficient of variation of the respiratory wavelength in the evaluation of respiratory waveform. RESULTS: Immediately after the change of respiratory wavelength from the short cycle to the long cycle, a gated signal was generated at a phase before the set gated phase, and a maximum advance of 1.259 ± 0.212 s occurred. Immediately after the change of respiratory wavelength from the long cycle to the short cycle, the gated signal was generated at the phase exceeding the set gated phase, and a delay of 0.997 ± 0.180 s occurred at the maximum. As the value of the coefficient of variation increased, the gated rate which was out of setting also increased. CONCLUSION: In respiratory gated irradiation using RPM, it became clear that the gated signal is generated out of the phase set by the respiratory waveform change. Coefficient of variation of the respiratory wavelength is considered to be an indicator for evaluating the respiratory waveform to be used in the respiratory gated irradiation.