The Quest for Ecological Validity in Hearing Science: What It Is, Why It Matters, and How to Advance It.

Ecological validity is a relatively new concept in hearing science. It has been cited as relevant with increasing frequency in publications over the past 20 years, but without any formal conceptual basis or clear motive. The sixth Eriksholm Workshop was convened to develop a deeper understanding of the concept for the purpose of applying it in hearing research in a consistent and productive manner. Inspired by relevant debate within the field of psychology, and taking into account the World Health Organization's International Classification of Functioning, Disability, and Health framework, the attendees at the workshop reached a consensus on the following definition: "In hearing science, ecological validity refers to the degree to which research findings reflect real-life hearing-related function, activity, or participation." Four broad purposes for striving for greater ecological validity in hearing research were determined: A (Understanding) better understanding the role of hearing in everyday life; B (Development) supporting the development of improved procedures and interventions; C (Assessment) facilitating improved methods for assessing and predicting ability to accomplish real-world tasks; and D (Integration and Individualization) enabling more integrated and individualized care. Discussions considered the effects of variables and phenomena commonly present in hearing-related research on the level of ecological validity of outcomes, supported by examples from a few selected outcome domains and for different types of studies. Illustrated with examples, potential strategies were offered for promoting a high level of ecological validity in a study and for how to evaluate the level of ecological validity of a study. Areas in particular that could benefit from more research to advance ecological validity in hearing science include: (1) understanding the processes of hearing and communication in everyday listening situations, and specifically the factors that make listening difficult in everyday situations; (2) developing new test paradigms that include more than one person (e.g., to encompass the interactive nature of everyday communication) and that are integrative of other factors that interact with hearing in real-life function; (3) integrating new and emerging technologies (e.g., virtual reality) with established test methods; and (4) identifying the key variables and phenomena affecting the level of ecological validity to develop verifiable ways to increase ecological validity and derive a set of benchmarks to strive for.

Physiological Monitoring and Hearing Loss: Toward a More Integrated and Ecologically Validated Health Mapping.

With an ongoing shift from managing disease toward the inclusion of maintaining health and preventing disease, the world has seen the rise of increasingly sophisticated physiological monitoring and analytics. Innovations range from wearables, smartphone-based spot monitoring to highly complex noncontact, remote monitoring, utilizing different mechanisms. These tools empower the individual to better navigate their own health. They also generate powerful insights towards the detection of subclinical symptoms or processes via existing and novel digital biomarkers. In that context, a topic that is receiving increasing interest is the modulation of human physiology around an individual "baseline" in everyday life and the impact thereof on other sensorineural body functions such as hearing. More and more fully contextualized and truly long-term physiological data are becoming available that allows deeper insights into the response of the human body to our behavior, immediate environment and the understanding of how chronic conditions are evolving. Hearing loss often goes hand in hand with chronic conditions, such as diabetes, cognitive impairment, increased risk of fall, mental health, or cardiovascular risk factors. This inspires an interest to not only look at hearing impairment itself but to take a broader view, for example, to include contextualized vital signs. Interestingly, stress and its physiological implications have also been shown to be a relevant precursor to hearing loss and other chronic conditions. This article deduces the requirements for wearables and their ecosystems to detect relevant dynamics and connects that to the need for more ecologically valid data towards an integrated and more holistic mapping of hearing characteristics.

Continuous noninvasive glucose monitoring; water as a relevant marker of glucose uptake in vivo.

With diabetes set to become the number 3 killer in the Western hemisphere and proportionally growing in other parts of the world, the subject of noninvasive monitoring of glucose dynamics in blood remains a "hot" topic, with the involvement of many groups worldwide. There is a plethora of techniques involved in this academic push, but the so-called multisensor system with an impedance-based core seems to feature increasingly strongly. However, the symmetrical structure of the glucose molecule and its shielding by the smaller dipoles of water would suggest that this option should be less enticing. Yet there is enough phenomenological evidence to suggest that impedance-based methods are truly sensitive to the biophysical effects of glucose variations in the blood. We have been trying to answer this very fundamental conundrum: "Why is impedance or dielectric spectroscopy sensitive to glucose concentration changes in the blood and why can this be done over a very broad frequency band, including microwaves?" The vistas for medical diagnostics are very enticing. There have been a significant number of papers published that look seriously at this problem. In this review, we want to summarize this body of research and the underlying mechanisms and propose a perspective toward utilizing the phenomena. It is our impression that the current world view on the dielectric response of glucose in solution, as outlined below, will support the further evolution and implementation toward practical noninvasive glucose monitoring solutions.

Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device.

Even if still at an early stage of development, non-invasive continuous glucose monitoring (NI-CGM) sensors represent a promising technology for optimizing diabetes therapy. Recent studies showed that the Multisensor provides useful information about glucose dynamics with a mean absolute relative difference (MARD) of 35.4% in a fully prospective setting. Here we propose a method that, exploiting the same Multisensor measurements, but in a retrospective setting, achieves a much better accuracy. Data acquired by the Multisensor during a long-term study are retrospectively processed following a two-step procedure. First, the raw data are transformed to a blood glucose (BG) estimate by a multiple linear regression model. Then, an enhancing module is applied in cascade to the regression model to improve the accuracy of the glucose estimation by retrofitting available BG references through a time-varying linear model. MARD between the retrospectively reconstructed BG time-series and reference values is 20%. Here, 94% of values fall in zone A or B of the Clarke Error Grid. The proposed algorithm achieved a level of accuracy that could make this device a potential complementary tool for diabetes management and also for guiding prediabetic or nondiabetic users through life-style changes.

First Experiences With a Wearable Multisensor in an Outpatient Glucose Monitoring Study, Part I: The Users' View.

BACKGROUND: Extensive past work showed that noninvasive continuous glucose monitoring with a wearable Multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions. METHODS: To test previous findings also in uncontrolled in-clinic and outpatient conditions, a long-term study has been conducted to collect Multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking Multisensor data to glucose applied to estimate glucose trends noninvasively. The operation of a digital log book, daily semiautomated data transfer and at least 10 daily SMBG values were requested from the patient. RESULTS: Results showed that the Multisensor is capable of indicating glucose trends. It can do so in 9 out of 10 cases either correctly or with one level of discrepancy. This means that in 90% of all cases the Multisensor shows the glucose dynamic to rapidly increase or at least increase. CONCLUSIONS: The Multisensor and the algorithmic routine used in controlled conditions can track glucose trends in all patients, also in uncontrolled conditions. Training of the patient proved to be essential. The workload imposed on patients was significant and should be reduced in the next step with further automation. The feature of glucose trend indication was welcomed and very much appreciated by patients; this value creation makes a strong case for the justification of wearing a wearable.

First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View.

BACKGROUND: Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions. METHOD: To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively. RESULTS: The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR. CONCLUSIONS: The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better.

The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.

BACKGROUND: We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate. METHOD: Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived. RESULTS: We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals. CONCLUSIONS: We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches.

Non-invasive continuous glucose monitoring with multi-sensor systems: a Monte Carlo-based methodology for assessing calibration robustness.

In diabetes research, non-invasive continuous glucose monitoring (NI-CGM) devices represent a new and appealing frontier. In the last years, some multi-sensor devices for NI-CGM have been proposed, which exploit several sensors measuring phenomena of different nature, not only for measuring glucose related signals, but also signals reflecting some possible perturbing processes (temperature, blood perfusion). Estimation of glucose levels is then obtained combining these signals through a mathematical model which requires an initial calibration step exploiting one reference blood glucose (RBG) sample. Even if promising results have been obtained, especially in hospitalized volunteers, at present the temporal accuracy of NI-CGM sensors may suffer because of environmental and physiological interferences. The aim of this work is to develop a general methodology, based on Monte Carlo (MC) simulation, to assess the robustness of the calibration step used by NI-CGM devices against these disturbances. The proposed methodology is illustrated considering two examples: the first concerns the possible detrimental influence of sweat events, while the second deals with calibration scheduling. For implementing both examples, 45 datasets collected by the Solianis Multisensor system are considered. In the first example, the MC methodology suggests that no further calibration adjustments are needed after the occurrence of sweat events, because the "Multisensor+model" system is able to deal with the disturbance. The second case study shows how to identify the best time interval to update the model's calibration for improving the accuracy of the estimated glucose. The methodology proposed in this work is of general applicability and can be helpful in making those incremental steps in NI-CGM devices development needed to further improve their performance.

Dielectric spectra broadening as a signature for dipole-matrix interaction. III. Water in adenosine monophosphate/adenosine-5'-triphosphate solutions.

In this, the third part of our series on the dielectric spectrum symmetrical broadening of water, we consider the nucleotide aqueous solutions. Where in Parts I [E. Levy et al., J. Chem. Phys. 136, 114502 (2012)] and II [E. Levy et al., J. Chem. Phys. 136, 114503 (2012)], the dipole-dipole or ion-dipole interaction had a dominant feature, now the interplay between these two types of dipole-matrix interactions will be considered. We present the results of high frequency dielectric measurements of different concentrations of adenosine monophosphate/adenosine-5'-triphosphate aqueous solutions. We observed the Cole-Cole broadening of the main relaxation peak of the solvent in the solutions. Moreover, depending on the nucleotide concentration, we observed both types of dipole-matrix interaction. The 3D trajectory approach (described in detail in Part I) is applied in order to highlight the differences between the two types of interaction.

Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system.

Non-invasive continuous glucose monitoring (NI-CGM) sensors are still at an early stage of development, but, in the near future, they could become particularly appealing in diabetes management. Solianis Monitoring AG (Zurich, Switzerland) has proposed an approach for NI-CGM based on a multi-sensor concept, embedding primarily dielectric spectroscopy and optical sensors. This concept requires a mathematical model able to estimate glucose levels from the 150 channels directly measured through the Multisensor. A static multivariate linear regression model (with order and parameters common to the entire population of subjects) was proposed for such a scope (Caduff et al., Biosens Bioelectron 26:3794-3800, 2011). The aim of this work is to evaluate the accuracy in the estimation of glucose levels and trends that the NI-CGM Multisensor platform can achieve by exploiting different techniques for model identification, namely, ordinary least squares, subset variable selection, partial least squares and least absolute shrinkage and selection operator (LASSO). Data collected in human beings monitored for a total of 45 study days were used for model identification and model test. Several metrics of standard use in the diabetes scientific community to measure point and clinical accuracy of glucose sensors were used to assess the models. Results indicate that the LASSO technique is superior to the others shrinking many channel weights to zero thus leading to smoother glucose profiles and resulting in a more robust model to possible artifacts in the Multisensor data. Although, as expected, the performance of the NI-CGM system with the LASSO model is not yet comparable with that of enzyme-based needle glucose sensors, glucose trends are satisfactorily estimated. Considering the non-invasive nature of the multi-sensor platform, this result can have an immediate impact in the current clinical practice, e.g., to integrate sparse self-monitoring of blood glucose data with an indication of the glucose trend to aid the diabetic patient in dealing with, or even preventing in the short time scale, the threats of critical events such as hypoglycaemia.

A 4-h hyperglycaemic excursion induces rapid and slow changes in major electrolytes in blood in healthy human subjects.

Hyperglycaemia is well known to cause reductions in plasma Na(+) levels or even hyponatraemia due to an osmotically induced dilution of the interstitium and blood. It is, however, unclear whether this dilution is significantly counteracted by ion regulatory homeostatic mechanism(s) or not. Furthermore, the effects of moderate hyperglycaemia on other major ions are less well known. To further clarify these questions, we measured the changes in blood osmolarity and concentrations of Na(+), K(+), Cl(-), Mg(2+) and Ca(2+) during a 4-h-long experimental hyperglycaemia in healthy subjects rendered temporarily insulin deficient using the hyperglycaemic clamp. Hyperglycaemia, 16.8 mM, was rapidly imposed from a baseline of 4.4 mM by intravenous somatostatin and glucose infusions in 19 healthy subjects (10 m, 9 f; age 36 ± 5 years (mean ± SD); BMI 22.7 ± 2.9 kg/m(2)). Subsequently, glycaemia was returned to basal and measurements continued until all dynamic changes had stopped (at ~8 h). Osmolarity increased from 281.8 ± 0.7 to 287.9 ± 0.7, while Na(+) decreased from 143.9 ± 0.3 to 138.7 ± 0.2, Cl(-) from 101.7 ± 0.2 to 99.5 ± 0.1, Ca(2+) from 1.98 ± 0.04 to 1.89 ± 0.02 and Mg(2+) from 0.84 ± 0.01 to 0.80 ± 0.00 mM. All these changes were rapidly reaching stable levels. K(+) increased from 4.02 ± 0.02 to 4.59 ± 0.02 mM (P < 0.0001) also reaching stable levels but with some delay. Na(+), Cl(-), Mg(2+) and Ca(2+) are essentially determined by blood dilution, and their values will remain diminished as long as the hyperglycaemia lasts. Partial suppression of insulin-stimulated Na(+)/K(+) pumping lead to increased K(+) levels. The combination of elevated K(+) and decreased Mg(2+) and Ca(2+) levels may lead to an altered excitability, which is particularly relevant for diabetic patients with heart disease.

The remote sensing of mental stress from the electromagnetic reflection coefficient of human skin in the sub-THz range.

Recent work has demonstrated that the reflection coefficient of human skin in the frequency range from 95 to 110 GHz (W band) mirrors the temporal relaxation of stress induced by physical exercise. In this work, we extend these findings to show that in the event of a subtle trigger to stress, such as mental activity, a similar picture of response emerges. Furthermore, the findings are extended to cover not only the W band (75-110 GHz), but also the frequency band from 110 to 170 GHz (D band). We demonstrate that mental stress, induced by the Stroop effect and recorded by the galvanic skin response (GSR), can be correlated to the reflection coefficient in the aforementioned frequency bands. Intriguingly, a light physical stress caused by repeated hand gripping clearly showed an elevated stress level in the GSR signal, but was largely unnoted in the reflection coefficient in the D band. The implication of this observation requires further validation.

Data processing for noninvasive continuous glucose monitoring with a multisensor device.

BACKGROUND: Impedance spectroscopy has been shown to be a candidate for noninvasive continuous glucose monitoring in humans. However, in addition to glucose, other factors also have effects on impedance characteristics of the skin and underlying tissue. METHOD: Impedance spectra were summarized through a principal component analysis and relevant variables were identified with Akaike's information criterion. In order to model blood glucose, a linear least-squares model was used. A Monte Carlo simulation was applied to examine the effects of personalizing models. RESULTS: The principal component analysis was able to identify two major effects in the impedance spectra: a blood glucose-related process and an equilibration process related to moisturization of the skin and underlying tissue. With a global linear least-squares model, a coefficient of determination (R²) of 0.60 was achieved, whereas the personalized model reached an R² of 0.71. The Monte Carlo simulation proved a significant advantage of personalized models over global models. CONCLUSION: A principal component analysis is useful for extracting glucose-related effects in the impedance spectra of human skin. A linear global model based on Solianis Multisensor data yields a good predictive power for blood glucose estimation. However, a personalized linear model still has greater predictive power.

Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation.

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz-100 MHz, 1 and 2 GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44±16 y; BMI 24.1±1.3 kg/m(2), duration of diabetes 27±12 y; HbA1c 7.3±1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9 mg dL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.

Cutaneous blood perfusion as a perturbing factor for noninvasive glucose monitoring.

It is widely accepted that noninvasive glucose monitoring (NIGM) has the potential to revolutionize diabetes therapy. However, current approaches to NIGM studied to date have not yet demonstrated a level of acceptable functionality to allow real-time use, beyond restricted fields of application. A number of reviews have been devoted to the subject of NIGM with different focuses related to challenges and a description of the respective underlying problems. This review is aimed at addressing a fundamental topic in the application of NIGM that seems to have received less attention, by describing the perturbations that result in a reduced functionality of NIGM in daily use. Here we provide a short general introduction to glucose monitoring and a basic illustration of the electromagnetic spectrum with a description of the respective physical mechanisms underlying the measurement techniques. This allows for a better understanding of how these perturbing factors affect the measured properties. Cutaneous blood perfusion is one of the major perturbing factors to NIGM, along with variations in temperature, migration of water, and the effect of attachment of the sensor to the skin. An understanding of the mechanisms underlying perfusion variation over time and within the measured human skin tissue matrix is required to enable a discrimination between glucose-induced effects within the tissue and various biophysical impacts to be made. It is suggested that a plurality of probing frequencies is required to discriminate glucose-related changes from the perturbations. A system designed to perform the measurements in different regions of the electromagnetic spectrum with dedicated sensors (multisensor approach) has the potential to more efficiently and reliably discriminate glucose-related information from perturbations. This can be achieved by combining signals related to measurements with different physical underlying mechanisms of the interaction between the probing field propagation and the tissue to help account for the different sources of perturbations.

The electromagnetic response of human skin in the millimetre and submillimetre wave range.

Recent studies of the minute morphology of the skin by optical coherence tomography revealed that the sweat ducts in human skin are helically shaped tubes, filled with a conductive aqueous solution. This, together with the fact that the dielectric permittivity of the dermis is higher than that of the epidermis, brings forward the supposition that as electromagnetic entities, the sweat ducts could be regarded as low Q helical antennas. The implications of this statement were further investigated by electromagnetic simulation and experiment of the in vivo reflectivity of the skin of subjects under varying physiological conditions (Feldman et al 2008 Phys. Rev. Lett. 100 128102). The simulation and experimental results are in a good agreement and both demonstrate that sweat ducts in the skin could indeed behave as low Q antennas. Thus, the skin spectral response in the sub-Terahertz region is governed by the level of activity of the perspiration system and shows the minimum of reflectivity at some frequencies in the frequency band of 75-110 GHz. It is also correlated to physiological stress as manifested by the pulse rate and the systolic blood pressure. As such, it has the potential to become the underlying principle for remote sensing of the physiological parameters and the mental state of the examined subject.

Non-invasive glucose monitoring in patients with Type 1 diabetes: a Multisensor system combining sensors for dielectric and optical characterisation of skin.

In vivo variations of blood glucose (BG) are affecting the biophysical characteristics (e.g. dielectric and optical) of skin and underlying tissue (SAUT) at various frequencies. However, the skin impedance spectra for instance can also be affected by other factors, perturbing the glucose related information, factors such as temperature, skin moisture and sweat, blood perfusion as well as body movements affecting the sensor-skin contact. In order to be able to correct for such perturbing factors, a Multisensor system was developed including sensors to measure the identified factors. To evaluate the quality of glucose monitoring, the Multisensor was applied in 10 patients with Type 1 diabetes. Glucose was administered orally to induce hyperglycaemic excursions at two different study visits. For analysis of the sensor signals, a global multiple linear regression model was derived. The respective coefficients of the variables were determined from the sensor signals of this first study visit (R(2)=0.74, MARD=18.0%--mean absolute relative difference). The identical set of modelling coefficients of the first study visit was re-applied to the test data of the second study visit to evaluate the predictive power of the model (R(2)=0.68, MARD=27.3%). It appears as if the Multisensor together with the global linear regression model applied, allows for tracking glucose changes non-invasively in patients with diabetes without requiring new model coefficients for each visit. Confirmation of these findings in a larger study group and under less experimentally controlled conditions is required for understanding whether a global parameterisation routine is feasible.

The role of GLUT1 in the sugar-induced dielectric response of human erythrocytes.

We propose a key role for the glucose transporter 1 (GLUT1) in mediating the observed changes in the dielectric properties of human erythrocyte membranes as determined by dielectric spectroscopy. Cytochalasin B, a GLUT1 transport inhibitor, abolished the membrane capacitance changes in glucose-exposed red cells. Surprisingly, D-fructose, known to be transported primarily by GLUT5, exerted similar membrane capacitance changes at increasing D-fructose concentrations. In order to evaluate whether the glucose-mediated membrane capacitance changes originated directly from intracellularly bound adenosine triphosphate (ATP) or other components of the glycolysis process, we studied the dielectric responses of swollen erythrocytes with a decreased ATP content and of nucleotide-filled ghosts. Resealed ghosts containing physiological concentrations of ATP yielded the same glucose-dependent capacitance changes as biconcave intact red blood cells, further supporting the finding that ATP is the effector of the glucose-mediated dielectric response where the ATP concentration is also the mediating factor in swollen red blood cells. The results suggest that ATP binding to GLUT1 elicits a membrane capacitance change that increases with the applied concentration gradient of D-glucose. A simplified model of the membrane capacitance alteration with glucose uptake is proposed.

Human skin as arrays of helical antennas in the millimeter and submillimeter wave range.

Recent studies of the minute morphology of the skin by optical coherence tomography showed that the sweat ducts in human skin are helically shaped tubes, filled with a conductive aqueous solution. A computer simulation study of these structures in millimeter and submillimeter wave bands show that the human skin functions as an array of low-Q helical antennas. Experimental evidence is presented that the spectral response in the sub-Terahertz region is governed by the level of activity of the perspiration system. It is also correlated to physiological stress as manifested by the pulse rate and the systolic blood pressure.