A method to quantify autonomic nervous system function in healthy, able-bodied individuals

Abstract

Background: The autonomic nervous system (ANS) maintains physiological homeostasis in various organ systems via parasympathetic and sympathetic branches. ANS function is altered in common diffuse and focal conditions and heralds the beginning of environmental and disease stresses. Reliable, sensitive, and quantitative biomarkers, first defined in healthy participants, could discriminate among clinically useful changes in ANS function. This framework combines controlled autonomic testing with feature extraction during physiological responses.

Methods: Twenty-one individuals were assessed in two morning and two afternoon sessions over two weeks. Each session included five standard clinical tests probing autonomic function: squat test, cold pressor test, diving reflex test, deep breathing, and Valsalva maneuver. Noninvasive sensors captured continuous electrocardiography, blood pressure, breathing, electrodermal activity, and pupil diameter. Heart rate, heart rate variability, mean arterial pressure, electrodermal activity, and pupil diameter responses to the perturbations were extracted, and averages across participants were computed. A template matching algorithm calculated scaling and stretching features that optimally fit the average to an individual response. These features were grouped based on test and modality to derive sympathetic and parasympathetic indices for this healthy population.

Results: A significant positive correlation (p = 0.000377) was found between sympathetic amplitude response and body mass index. Additionally, longer duration and larger amplitude sympathetic and longer duration parasympathetic responses occurred in afternoon testing sessions; larger amplitude parasympathetic responses occurred in morning sessions.

Conclusions: These results demonstrate the robustness and sensitivity of an algorithmic approach to extract multimodal responses from standard tests. This novel method of quantifying ANS function can be used for early diagnosis, measurement of disease progression, or treatment evaluation.

Trial registration: This study registered with Clinicaltrials.gov , identifier NCT04100486 . Registered September 24, 2019, https://www.clinicaltrials.gov/ct2/show/NCT04100486 .

Conflict of interest statement

The authors declare no competing interests.

© 2021. The Author(s).

Figures

Fig. 1

Autonomic testing and monitoring physiological signals. (a) Shown is a sample timeline of autonomic tests performed in each session. The tests include a set of sympathetic tests (standing-squatting-standing [one minute of each, in succession] and cold pressor test [immersion of hand in ice water for up to three minutes]), a set of parasympathetic tests (deep breathing [respiratory rate of six breaths per minute for seven minutes] and diving reflex test [refrigerated gel-filled compresses on the face for one minute with one minute of recovery]), and Valsalva maneuver (restricted and forced exhalation for 15 s with one minute of recovery). (b) Physiological signals for each participant were recorded by a six lead electrocardiogram (in red, wires attached to four foam adhesive electrodes placed at each shoulder and each ankle) and a respiratory belt (in green, around the torso). Recorded from the left hand were noninvasive blood pressure (in blue, small inflatable cuff on middle phalanx of middle finger) and electrodermal activity (in gold, dry, metal electrodes on distal phalanx of index and ring finger). Eye tracking glasses (in purple) were placed to record pupil diameter and gaze location

Fig. 2

Schematic of template matching method. Shown is a schematic of the template matching method to quantify autonomic responses. The average response within an epoch (a) is the template to fit the individual response (b). Once the individual response is trimmed and extrapolated for the same epoch (c), four parameters are estimated to best fit the template to the response (d). Parameters are estimated by minimizing the normalized sum of the squared error (Equation (Akselrod et al., 1981)). The parameters quantify how the individual response compares to the average template in duration scale and amplitude scale, as well as delay and vertical offset. The duration scale is reported as variable H and the amplitude scale and vertical offset are reported as variable V

Fig. 3

Monitoring and calculating physiological signals. 15 s of raw signals from these sensors are shown in the upper panel, with six channels of the electrocardiogram, one channel of respiration, one channel of finger pressure, one channel of electrodermal activity, and two channels corresponding to the left and right pupil diameter. Calculated signals in the lower panel include heart rate from the electrocardiogram, heart rate variability (RMSSD) from interbeat intervals, and the mean arterial pressure

Fig. 4

Average heart rate, mean arterial pressure, and RMSSD during autonomic testing (76 sessions). The individual calculated responses (gray lines) were accumulated and averaged (black line) to extract an average response for each modality during each test. Each column represents a different calculated signal (heart rate, mean arterial pressure, and RMSSD). The dotted black traces correspond to a 95% confidence interval. RMSSD was not calculated for the cold pressor test and Valsalva maneuver due to time constraints necessary to accurately convey heart rate variability. Squat Test: vertical lines reflect changes in posture from standing to squatting and then squatting to standing. Cold Pressor Test: the first vertical line reflects when the participant immersed their hand into the ice water. The second vertical line represents the maximum of three minutes. The average trace only represents the individual traces available at that time point, as participants removed their hand at their own discretion. All participants kept their hand in the ice water for at least 30 s. Deep Breathing: vertical lines reflect when the deep breathing rate (6 breaths/minute) began and ended. In the third column for the RMSSD, only the first two minutes were analyzed. Diving Reflex: vertical lines reflect when the refrigerated gel-mask was placed on and removed from the participant’s face. A five second removal period is designated before the one minute of recovery. Valsalva Maneuver: vertical lines reflect the phases of the effort, from baseline, five seconds designated for inhalation and preparation, 15 s of the Valsalva maneuver, 10 s at the end of maneuver, and a final minute of recovery

Fig. 5

Example of individual responses and corresponding calculated features. Here are examples of individual phasic responses to autonomic testing (blue trace) and the transformed template (red trace) resulting from stretching and scaling the average template (black trace) to best match the individual response. The calculated features (in title of each panel) represent scaling amplitude (V) and duration (H). (a) Heart rate change in the transition from squatting to standing. Participant stood at t = 0 (black vertical line). (b) Mean arterial pressure changes in the transition from squatting to standing. Participant stood at t = 0 (black vertical line). (c) Heart rate change when putting on the refrigerated mask to initiate the diving reflex. The mask is placed at t = 0 (black vertical line). (d) Mean arterial pressure change when putting on the refrigerated mask to initiate the diving reflex. The mask is placed at t = 0 (black vertical line). (e) Heart rate fluctuations during first two minutes of deep breathing task. (f) Heart rate variability RMSSD calculated during the first two minutes of the deep breathing task

Fig. 6

Calculated features vs BMI. Average calculated features for each participant as a function of their BMI. For each type of features (top row is sympathetic and bottom row is parasympathetic, first column represents H [duration scale] and second column represents V ([amplitude scale and offset]), each point represents the average for a single participant, while error bars show standard deviation. Line of best fit was approximated, with p-values for each subplot

Fig. 7

Calculated features in AM and PM. The average feature for each type for each individual was calculated for two AM sessions and two PM sessions. (a) Each trace represents one individual, where blue traces represent higher values in AM sessions and orange traces represent higher values in PM sessions. (b) Summary of the number of participants with greater feature values in either AM or PM sessions