Autonomic Measures Research Articles

Verification of uncertainty estimates of autonomous field measurements of marine reflectance using simultaneous observations

The primary ocean color product is the spectrum of remote sensing reflectance RRS that allows the quantification of in-water optically significant constituents and all ocean color applications. The determination of its uncertainties is thus key to the creation of comprehensive uncertainty budgets for all derived ocean color products. The assessment of satellite RRS uncertainties has largely relied on corresponding field measurements but this process is solid only if these field measurements are in turn fully characterized. Uncertainty budgets have therefore been defined and reported for the radiometric measurements collected in the framework of the Ocean Color component of the Aerosol Robotic Network (AERONET-OC). The contemporaneous deployment of two autonomous systems for 5.5 years on the Acqua Alta Oceanographic Tower (AAOT) located in the northern Adriatic Sea led to the collection of 4,449 pairs of coincident observations (collected with a time difference lower than 10 min) distributed over 659 days of data acquisitions that can be used to verify reported uncertainty values. The comparison of matched pairs showed a good agreement for RRS (with differences of typically 2%–3% between 412 and 560 nm), as well as for the aerosol optical thickness τa (3%–6%). Differences between data from the two systems appear generally consistent with their stated uncertainties, indicating that they are metrologically compatible and that uncertainties reported for AERONET-OC data are usually trustworthy (with possible exceptions depending on the level of error correlation between measurements from the two systems). Using uncertainty cone diagrams, this result holds across the range of uncertainty values with few exceptions. Independent uncertainty estimates associated with non-systematic error contributions were obtained using a collocation framework allowing for error correlation between measurements from the two systems. The resulting uncertainties appeared comparable with the reported values for τa and RRS. The related mathematical development also showed that the centered root-mean-square difference between data collected by two systems is a conservative estimate of the uncertainty associated with these data (excluding systematic contributions) if these data show a good agreement (expressed by a slope of method II regression close to 1) and if their uncertainties can be assumed similar with errors moderately correlated (typically lower than 0.5).

Intraoperative Protection of Pharyngeal Autonomic Nerves: Preventing Dysphagia After Anterior Cervical Decompression and Fusion Surgery

The study aims to investigate whether intraoperative protection of the pharyngeal autonomic nerve can effectively reduce the incidence of postoperative dysphagia following anterior cervical decompression and fusion surgery (ACDF). A retrospective analysis was conducted on 130 cases that underwent ACDF from January 2018 to June 2022 at our hospital. Divided into nonautonomic neuroprotection (NANP) group and autonomic neuroprotection group based on whether receive protective measures for the pharyngeal autonomic nerve during surgery. General data were recorded and compared between the 2 groups. Postoperative outcomes were evaluated using Neck Disability Index, Japanese Orthopaedics Association (JOA) score, and JOA improvement rate. The incidence and severity of postoperative dysphagia were assessed using Bazaz dysphagia assessment criteria and swallowing-quality of life questionnaire. There were no significant differences in general data (P > 0.05). The average operation time and intraoperative blood loss also showed no significant differences (P > 0.05). Both groups showed significant improvements in Neck Disability Index and JOA scores at all follow-up time points compared to preoperative scores (P < 0.01). The incidence of postoperative dysphagia in the autonomic neuroprotection group was significantly lower than that in the NANP group at all follow-up time points (P< 0.05). Both group showed a significant reduction in scores 3 days postoperatively compared to preoperative scores (P < 0.01), and the NANP group also showed significant reductions in scores at 3 month and 1 year postoperative follow-up time points compared to preoperative scores (P < 0.01). The adoption of pharyngeal autonomic nerve protective measures during ACDF can effectively lower the probability of postoperative dysphagia.

Functional MRI signals exhibit stronger covariation with peripheral autonomic measures as vigilance decreases

Functional MRI signals exhibit stronger covariation with peripheral autonomic measures as vigilance decreases

Design and Development a Software for Wear Measurement of Control Rod Guide Card Based on Machine Vision

The control rod guide tube (CRGT) is used to protect the rod cluster control assembly (RCCA) from bending while providing guidance for the up and down movement of the RCCA. This ensures that the dropping time of the RCCA meets nuclear safety requirements and stops nuclear reactions within the specified time frame. During the up and down movement of the RCCA, the control rod guide cards (CRGC) may experience axial and vibration wear. If the wear is severe, the CRGC may lose its guiding function, resulting in serious problems such as delayed dropping time. In this paper, a machine vision method is proposed to measure the dimensions of the CRGC. Edge extraction, image rectification, and template matching are used to realize autonomous measurement of the CRGC based on its features. The developed measurement software has been used 5 times in domestic nuclear power plant overhauls and has detected 15 CRGTs that were close to the wear limit. This provided data support for the replacement of the CRGTs and effectively improved the quality of nuclear power operation.

Design, development and deployment of a novel sea spray collector for sea-spray flux measurements

The risk of sea-spray icing on vessels and marine structures in cold regions highlights the need for an accurate and robust marine-icing estimation model. To develop such a model, it is crucial to accurately determine the quantity of liquid water available for freezing on the structure, as it directly influences ice formation. As sea spray constitutes the primary source of liquid water contributing to marine icing, researchers have often focused on measuring sea-spray flux from field campaigns to establish empirical expressions for icing estimation. However, due to the lack of standardised equipment or methods for such measurements and concerns regarding the generalisability and transferability of resulting empirical expressions, researchers have resorted to employing a variety of equipment and techniques tailored to their specific research requirements. Nevertheless, these approaches have inherent limitations. This paper introduces a novel spray collector device inspired by the cyclone separator, capable of performing real-time autonomous spray flux measurements on vessels and moving platforms. The collector is constructed using carbon fibre-infused nylon material, ensuring durability in harsh cold marine climates. Computational Fluid Dynamics (CFD) simulations and laboratory tests demonstrate that the design of the new collector is more efficient than that of the previously employed devices, particularly at higher wind speeds. The device is currently deployed on a fish farm in Northern Norway in order to assess its performance in field conditions. The paper also shares preliminary findings, experiences, and limitations encountered during the deployment period.

Immersive Virtual Reality to Assess Arm Kinematics among Older Adults with and without Major Neurocognitive Disorder – An Exploratory Cross-Sectional Study

Despite the recommendation of improving assessment objectivity and frequency, the use of immersive virtual reality to measure and quantify movement quality remains underexplored. In this study, we aimed to evaluate the reliability, validity and usability of an immersive virtual reality application, KinematicsVR, to assess upper limb kinematics among older adults with and without major neurocognitive disorder. The KinematicsVR involves the drawing of three-dimensional straight lines, circles and squares using a controller in a virtual environment. Twenty-eight older adults with or without major neurocognitive disorder were recruited. Reliability was evaluated through correlations on test–retest and validity through correlations between KinematicsVR variables and other functional tests (TEMPA, BBT-VR and Finger-Nose Test). The usability of the KinematicsVR was assessed with the System Usability Scale questionnaire. Kinematic indexes were compared between eight adults with major neurocognitive disorder and eight matched controls. Results indicated that most variables provided by the KinematicsVR had excellent reliability for tasks involving the drawing of straight lines and circles, but moderate reliability for tasks involving the drawing of squares. Secondary analyses showed that the usability of the application was excellent but few significant and strong correlations were observed between variables of the KinematicsVR and the scores of the TEMPA scale, Finger-Nose Test and BBT-VR. Adults with major neurocognitive disorder, when compared to other older adults, made larger and less linear hand movements. These findings provide perspectives for the use of immersive virtual reality to improve assessment frequency and objectivity through the autonomous measure of upper limb kinematics in older adults.

Impedance cardiogram based exploration of cardiac mechanisms in post-traumatic stress disorder during trauma recall.

Post-traumatic stress disorder (PTSD) is an independent risk factor for developing heart failure; however, the underlying cardiac mechanisms are still elusive. This study aims to evaluate the real-time effects of experimentally induced PTSD symptom activation on various cardiac contractility and autonomic measures. We recorded synchronized electrocardiogram and impedance cardiogram from 137 male veterans (17 PTSD, 120 non-PTSD; 48 twin pairs, 41 unpaired singles) during a laboratory-based traumatic reminder stressor. To identify the parameters describing the cardiac mechanisms by which trauma reminders can create stress on the heart, we utilized a feature selection mechanism along with a random forest classifier distinguishing PTSD and non-PTSD. We extracted 99 parameters, including 76 biosignal-based and 23 sociodemographic, medical history, and psychiatric diagnosis features. A subject/twin-wise stratified nested cross-validation procedure was used for parameter tuning and model assessment to identify the important parameters. The identified parameters included biomarkers such as pre-ejection period, acceleration index, velocity index, Heather index, and several physiology-agnostic features. These identified parameters during trauma recall suggested a combination of increased sympathetic nervous system (SNS) activity and deteriorated cardiac contractility that may increase the heart failure risk for PTSD. This indicates that the PTSD symptom activation associates with real-time reductions in several cardiac contractility measures despite SNS activation. This finding may be useful in future cardiac prevention efforts.

Understanding the combined effects of sleep deprivation and acute social stress on cognitive performance using a comprehensive approach

BackgroundSleep deprivation (SD) and acute social stress are common, often unavoidable, and frequently co-occurring stressors in high-risk professions. Both stressors are known to acutely induce inflammatory responses and an increasing body of literature suggests this may lead to cognitive impairment. This study examined the combined effects of total SD and acute social stress on cognitive performance and took a comprehensive approach to explore their (shared) underlying mechanism leading to cognitive decline. MethodWe recorded cognitive performance on a response inhibition task and a multitask and monitored a range of inflammatory, psychophysiological and self-reported markers in 101 participants, both before and after one night of either sleep (control group: N = 48) or SD (N = 53), and both before and after a social stressor (Trier Social Stress Test). ResultsSD decreased cognitive performance. The social stress test also results in cognitive performance decline in the control group on the response inhibition task, but improved rather than decreased performance of sleep deprived participants on both tasks. The subjective ratings of mental effort also reflect this antagonistic interaction, indicating that the social stressor when sleep-deprived also reduced mental effort. In the inflammatory and physiological measures, this pattern was only reflected by IL-22 in blood. SD reduced blood IL-22 concentrations, and the social stress reduced IL-22 in the control group as well, but not in sleep-deprived participants. There were no interactive effects of SD and social stress on any other inflammatory or psychophysiological measures. The effects of the social stress test on autonomic measures and subjective results suggest that increased arousal may have benefited sleep-deprived participants’ cognitive performance. DiscussionSD generally decreased cognitive performance and increased required mental effort. By contrast, the isolated effects of a social stressor were not generic, showing a positive effect on cognitive performance when sleep deprived. Our study is the first that studied combined effects of sleep deprivation and acute social stress on cognitive performance and inflammatory markers. It provides a comprehensive overview of effects of these stressors on a range of variables. We did not show unequivocal evidence of an underlying physiological mechanism explaining changes in performance due to (the combination of) sleep deprivation and social stress, but consider IL-22 as a possible cytokine involved in this mechanism and certainly worth following up on in future research.

Abstract 12824: Quantitative Autonomic Testing ‘Early’ and ‘Late’ After Recovery From Acute COVID-19 Illness

Background: Cardiovascular (CV) autonomic dysfunction (AD) is a known potential complication following acute COVID-19 illness and may contribute to persistent symptoms, such as fatigue and postural intolerance. However, the quantitative assessment of CV AD after an acute COVID-19 infection is largely unexplored. Objective: Compare CV autonomic testing in patients presenting ‘early’ and ‘late’ after an acute COVID-19 illness. Methods: CV autonomic testing was undertaken in symptomatic patients presenting ‘early’ (0-10 months) and ‘late’ (11-20 months) after an acute COVID-19 illness. Findings were compared to autonomic testing results in healthy control subjects. Measures included i) heart rate (HR) and blood pressure (BP) responses during active standing (AS), ii) time to BP nadir and recovery during AS, iii) Valsalva ratio (VR), and iv) respiratory sinus arrhythmia (RSA). Unpaired student t-test was used to compare findings (mean ± SD) in post-COVID patients to controls. A p-value of &lt;0.05 was statistically significant. Results: Control (n=82, mean 33 years, 87% female), ‘early’ (n= 37, mean 38 years, 89% female) and ‘late’(n=18, mean 43 years, 72% female) groups were similar in age and sex. Compared to controls, VR was abnormally low in both the ‘early’ and ‘late’ groups (‘early’ 1.5 and ‘late’ 1.4 vs. controls 1.7, both p&lt;0.03) ( Table ). Other autonomic measures did not differ significantly from controls. However, compared to the ’early’ group, the ‘late’ group exhibited a trend toward more marked AD ( Figure ). Conclusion: Patients presenting ‘early’ and ‘late’ after an acute COVID-19 illness exhibit similar severity of autonomic disturbance. Potentially, the ‘late’ group experienced more severe COVID illness leading to delayed referral for troublesome AD symptoms. Nonetheless, our findings suggest that abnormal CV AD findings may persist without apparent improvement for lengthy periods (up to 20 months in this study) after acute COVID-19 infection.

Abstract 18481: Paroxysmal Atrial Fibrillation and Sleep Apnea: Diurnal Patterning of Autonomic Function and Influence of CPAP Therapy

Introduction: Autonomic nervous system (ANS) dysfunction is implicated in sleep-disordered breathing (SDB) and atrial fibrillation (AF). Hypothesis: We hypothesize that ANS measures of heart rate variability (HRV) exhibit diurnal differences in paroxysmal AF(PAF) relative to SDB severity and is impacted by continuous positive airway pressure (CPAP). Methods: Data from the Sleep Apnea and Atrial Fibrillation Biomarkers and Electrophysiologic Atrial Triggers (SAFEBEAT) study including PAF (7-24 day ECG monitoring), concomitant actigraphy and SDB from polysomnography at baseline and 3-months post-CPAP were analyzed. Linear mixed-effects models were used to assess SDB (apnea hypopnea index (AHI), hypoxia (%sleep time with SaO2&lt;90% and nadir SaO2) and diurnal average HRV (frequency domain (sympathovagal)): low-frequency range (LF), high-frequency range (HF), LF/HF; time domain: mean of normal RR interval (MNN), standard deviation of NN intervals (SDNN), SD1(Poincare plot standard deviation) and effect of 3-month CPAP. Results: In 44869 five-minute epochs from 109 participants with SDB and PAF, during wakefulness, associations of AHI and LFP, nadir SaO2 with sympathovagal measures (LFP, LHR) and time domain measures (SDNN, SD2) were observed. A sleep-wake significant interaction was observed with all HRV measures and stronger associations in wake than sleep. Baseline to follow-up CPAP time domain measures were increased during wakefulness (MNN, SDNN, RMSSD, CV, SD1, and SD2) and increased during sleep (MNN, SD2, LHR). Conclusions: Diurnal variation of autonomic measures in moderate to severe SDB was observed and association with SDB severity was more pronounced during wakefulness; CPAP influenced autonomic function. These findings in earlier onset AF may contribute to electrophysiological remodeling with implications for ANS-specific chronobiology in SDB.

Variability of total alkalinity in coastal surface waters determined using an in-situ analyzer in conjunction with the application of a neural network-based prediction model

Total alkalinity (TA) is an important variable of the ocean carbonate system. In coastal oceans, carbonate system dynamics are controlled by a range of processes including photosynthesis and respiration, calcification, mixing of water masses, continental inputs, temperature changes, and seasonal upwelling. Assessments of diel, seasonal and interannual variations in TA are required to understand the carbon cycle in coastal oceans. However, our understanding of these variations remains underdeveloped due to limitations in observational techniques. Autonomous TA measurements are therefore required. In this study, an in situ TA analyzer (ISA-TA) based on a single-point titration with spectrophotometric pH detection was deployed in Tong'an Bay, Xiamen, China, over a five-month period in 2021 to determine diel and seasonal TA variations. The TA observations were combined with an artificial neural network (ANN) model to construct TA prediction models for this area. This provided a simple method to investigate TA variations in this region and was applied to predict surface water TA between March and April 2021. The in situ TA observations showed that TA values in Tong'an Bay varied within a range from 1931 to 2294 μmol kg−1 over the study period, with low TA in late winter, early summer and late summer, and high TA in early winter. The TA variations in late summer and early winter were mainly controlled by mixing of water bodies. The diel variations of TA were greatly determined by tides, with a diel amplitude of 9 to 247 μmol kg−1. The ANN model used temperature, salinity, chlorophyll, and dissolved oxygen to estimate TA, with a root-mean-square error (RMSE) of ∼14 μmol kg−1, with salinity as the input variable with the greatest weight. The approach of combining ISA-TA observations with an ANN model can be extended to study the carbonate system in other coastal regions.

Autonomic function measurements for evaluating fatigue and quality of life in patients with breast cancer undergoing radiation therapy: a prospective longitudinal study

BackgroundFatigue during radiation therapy in women with breast cancer can decrease quality of life (QOL), yet it is often underestimated and needs to be evaluated objectively. This longitudinal study aimed to evaluate fatigue and QOL of women with breast cancer undergoing radiotherapy with a simple autonomic function measurement.MethodsWomen with breast cancer who underwent postoperative radiotherapy in eight cancer care hospitals in Chubu and Kinki regions in Japan were recruited between October 2021 and June 2022. The women underwent a self-administered questionnaire that included the Cancer Fatigue Scale (CFS) and the Short Form-8 Health Survey (SF-8) and an autonomic nervous function measurement using a simple, non-invasive device before (T0, baseline), mid (T1), and at the end (T2) of treatment.ResultsThe 57 women showed similar trends, with CFS scores and log LF/HF ratio being the highest at T0 and significantly decreasing at T1 (both p < 0.05). The log LF/HF trends differed between those with high and low baseline log LF/HF values. Women with mental component summary (MCS) score improvement (T0 to T2) had the highest log LF/HF ratio at T0 and had significantly lower log LF/HF values at T1 and T2 than at T0 (p < 0.01 and p < 0.05, respectively). The change of (⊿) MCS from T0 to T1 was negatively correlated with ⊿log LF/HF from T0 to T1 (r = − 0.36, p < 0.01).ConclusionsMeasurement of autonomic nerve function with a simple device is useful for objective fatigue assessment during radiotherapy. Psychological support is important as improvement in mental health helps improve autonomic nerve function and, in turn, fatigue.

Soundscape during summer in Kongsfjorden, Svalbard, Arctic

This paper summarises research on ambient noise data collected during the summers of 2016 and 2017 by an autonomous Ambient Noise Measurement System (ANMS) deployed in the Kongsfjorden, Arctic. The primary goals of this study are to identify the various soundscape components and the variation of the soundscape in the Arctic environment during the summers of 2016 and 2017. This work mainly quantifies the ambient noise sources during each month of the summer. After analysing the data, five distinct sources of soundscape were identified, out of which three geophysical sources, including iceberg bubbling, glacier calving, and rain noise, as well as two anthropogenic sources, such as shipping noise and ice ramming noise, were identified. No biological sources were identified either in the summer of 2016 or in 2017. A comparison of average Sound Pressure Levels (SPL) in the summers of 2016 and 2017 shows that the difference in average SPL below 8 kHz is 3 dB re 1 μPa2/Hz.

Development of an Autonomous Measurement System for Estimation of Snow Profile on Road Surfaces

This paper presents the development of a novel prototype system to measure the profile of snow and detect ice on road surfaces. While researchers have previously developed methods to estimate the tire-road friction coefficient, methods to create a high resolution map of snow cover and ice on roads have not been developed. The prototype and data processing methods presented in this study provide a potential solution that would greatly benefit winter road maintenance teams. Having a device capable of creating a detailed map of snow and ice cover on roads would allow for more efficient plowing and salt deployment, better informing of the public about current road conditions, as well as better analysis of current plowing techniques to improve winter road maintenance operations. The measurement of the snow profile is based on the use of two types of inexpensive ranging sensors mounted on a rotationally controlled stepper motor platform. The technical challenges addressed in the development include analysis of the scan path over which the system scans the road, differentiation between asphalt, concrete, and snow surfaces using reflection amplitudes, accurate transformation of raw distance measurements to inertial coordinates, and identification of the Euler angles of the sensors using parameters associated with the scanned surface profile. Extensive experimental results and test data are presented, which show that the system is capable of measuring the snow profile on a road with an accuracy of ±1 cm when a reasonable portion of bare road is visible, and ±2 cm when only small portions of bare road are visible.

Advanced IoT Pressure Monitoring System for Real-Time Landfill Gas Management.

This research presents a novel stand-alone device for the autonomous measurement of gas pressure levels on an active landfill site, which enables the real-time monitoring of gas dynamics and supports the early detection of critical events. The developed device employs advanced sensing technologies and wireless communication capabilities, enabling remote data transmission and access via the Internet. Through extensive field experiments, we demonstrate the high sampling rate of the device and its ability to detect significant events related to gas generation dynamics in landfills, such as flare shutdowns or blockages that could lead to hazardous conditions. The validation of the device's performance against a high-end analytical system provides further evidence of its reliability and accuracy. The developed technology herein offers a cost-effective and scalable solution for environmental landfill gas monitoring and management. We expect that this research will contribute to the advancement of environmental monitoring technologies and facilitate better decision-making processes for sustainable waste management.

Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures

Objective20–40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS. MethodsThe prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18–65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri‑ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS. ResultsThe study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83–0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99). SignificanceHR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.

Autonomous Ultrasonic Thickness Measurement of Steel Bridge Members Using a Climbing Bicycle Robot

This paper presents the development of a steel-climbing bicycle robot integrated with an ultrasonic sensing device towards autonomous thickness measurement of steel bridge members. The bicycle-like robot has two magnetic wheels controlled by two independent steering actuators, which navigates on various steel surfaces (flat, curved, rough, concave, and convex). The compact ultrasonic sensing device is capable of high-voltage pulse excitation, filtering/amplification of the received ultrasonic signal, and high-speed analog-to-digital conversions (up to 80 MHz). Along with the ultrasonic sensing device, the robot carries a dual element transducer, an automatic gel couplant dispenser, a position tracking sensor, and a camera. A mounting/retrieving mechanism of the transducer is designed to ensure the reliable contact of the transducer on steel surfaces. The camera view assists an operator to safely navigate the robot to measurement locations, properly dispense gel couplant, and firmly press the transducer on a measurement surface. The automated robot localization provides accurate thickness measurement locations, which are mapped real-time in three-dimensional (3D) space together with the robot’s travel path. We validate the performance of the developed system in several indoor and outdoor tests. Weblink to a supplementary video demonstrating the robot’s maneuverability and ultrasonic thickness measurements is available in the Data Availability Statement of this article.

The co-existence of peripheral and vestibular neuropathy in diabetes: a cross-sectional study

PurposeDiabetic neuropathy can lead to decreased peripheral sensation and motor neuron dysfunction associated with impaired postural control and risk of falling. However, the relationship between decreased peripheral sensation and impaired vestibular function in diabetes mellitus is poorly investigated. Therefore, the aim of this study was to investigate the relationship between peripheral and autonomic measurements of diabetic neuropathy and measurements of vestibular function.MethodsA total of 114 participants with type 1 diabetes (n = 52), type 2 diabetes (n = 51) and controls (n = 11) were included. Vestibular function was evaluated by video head impulse testing. Peripheral neuropathy was assessed by quantitative sensory testing and nerve conduction. Autonomic neuropathy using the COMPASS 31 questionnaire. Data were analyzed according to data type and distribution.ResultsMeasurements of vestibular function did not differ between participants with type 1 diabetes, type 2 diabetes or controls (all p-values above 0.05). Subgrouping of participants according to the involvement of large-, small- or autonomic nerves did not change this outcome. Correlation analyses showed a significant difference between COMPASS 31 and right lateral gain value (ρ = 0.23, p = 0.02,), while no other significant correlations were found.ConclusionDiabetic neuropathy does not appear to impair vestibular function in diabetes, by means of the VOR.Clinical trialsNCT05389566, May 25th, 2022.

Differential Associations of Childhood Abuse and Neglect With Adult Autonomic Regulation and Mood-Related Pathology.

This study assessed whether different types of childhood maltreatment (i.e., abuse versus neglect) had differential relationships with heart rate variability (HRV) and baroreflex sensitivity. In addition, this study tested the indirect effect of maltreatment subtypes on adult mood-related psychopathology via HRV, and whether these relationships differed in those with HRV above and below established clinical cutoffs. Secondary analysis was performed using the Midlife Development in the United States data set ( N = 967; Mage = 55; 58.4% female; 75.9% White). In a single study visit, autonomic measurements were captured at rest, during two cognitive stressors (Stroop and MATH tasks), and during recovery after the tasks. Structural equation modeling was used to assess the relationships between key variables during all three measurement periods. Resting pathways from abuse and neglect to baroreflex sensitivity were nonsignificant, as was the pathway from HRV to mood-related pathology. Notably, greater abuse was significantly predictive of lower HRV (standardized β = -0.42, p = .009), whereas greater neglect was significantly predictive of higher HRV (standardized β = 0.32, p = .034). In addition, higher abuse was significantly predictive of greater adult symptoms (standardized β = 0.39, p < .001), but neglect was not found to be related to adult mood-related pathology. Significant relationships between variables were only found in those with low HRV. Although cross-sectional, our findings provide further evidence that low HRV may be a transdiagnostic endophenotype for mood-related pathology and suggest that greater differentiation between abuse and neglect is appropriate when investigating the impact of childhood maltreatment on adult health outcomes.

Study on the Autonomous Non-contact Measurement of Biometric Signals.

In this study, we developed a robot that can recognize and track a person, and autonomously measure two biological signals, respiration rate and heart rate, in a non-contact manner. Through experiments, we confirmed that both signals can be measured with high accuracy and that the robot can perform the measurement under conditions similar to those in actual workplaces. We also investigated factors that can affect the accuracy of the non-contact measurement and studied a method to evaluate the reliability of the measured signals.