Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone.

The application of Poincaré plot analysis to characterize inter-beat interval dynamics has been successfully proposed in the scientific literature for the assessment of humans' physiological states and related aberrations. In this study, we proposed novel descriptors to trace the evolution of Poincaré plot shape over the lags. Their reliability in ultra-short cardiovascular series analysis was validated on synthetic inter-beat series generated through a physiologically plausible integral pulse frequency modulation model. Furthermore, we used the proposed approach for the investigation of the direct relationship between autonomic nervous system (ANS) dynamics and hedonic olfactory elicitation, in a group of 30 healthy subjects. Participants with a similar olfactory threshold were selected, and were asked to score 5-s stimuli in terms of arousal and valence levels according to the Russell's circumflex model of affect. Their ANS response was investigated in 35-s windows after the elicitation. Experimental results showed a gender-specific, high discriminant power of the proposed approach, discerning between pleasant and unpleasant odorants with an accuracy of 83.33% and 73.33% for men and for women, respectively. Graphical Abstract Olfaction plays a crucial role in our life and is strictly related to the Autonomic Nervous System (ANS) activity, which can be monitored studying Heart Rate Variability. We used the Lagged Poincare Plot approach to recognize gender-specific ANS response in 35-second windows after the elicitation through pleasant/unpleasant odorants.

A Multiclass Arousal Recognition using HRV Nonlinear Analysis and Affective Images.

This paper reports on a multiclass arousal recognition system based on autonomic nervous system linear and nonlinear dynamics during affective visual elicitation. We propose a new hybrid method based on Lagged Poincaré Plot (LPP) and symbolic analysis, hereinafter called LPPsymb. This tool uses symbolic analysis to evaluate the irregularity of the trends of Lagged Poincaré Plot (LPP) quantifiers over the lags, and is here applied to investigate complex Heart Rate Variability (HRV) changes during emotion stimuli. In the experimental protocol 22 healthy subjects were elicited through a passive visualization of affective images gathered from the international affective picture system. LPPsymb and standard HRV analysis (defined in time and frequency domains) were applied to HRV series of one minute length. Then, an ad-hoc pattern recognition algorithm based on quadratic discriminant classifier was implemented and validated through a leave-onesubject-out procedure. The best performance of the proposed classification algorithm for recognizing the four classes of arousal was obtained using nine features comprising heartbeat complex dynamics, achieving an accuracy of 71.59%.

A novel Heart Rate Variability analysis using Lagged Poincaré plot: A study on hedonic visual elicitation.

This paper reports on a novel method for the analysis of Heart Rate Variability (HRV) through Lagged Poincaré Plot (LPP) theory. Specifically a hybrid method, LPPsymb, including LPP quantifiers and related symbolic dynamics was proposed. LPP has been applied to investigate the autonomic response to pleasant and unpleasant pictures extracted from the International Affective Picture System (IAPS). IAPS pictures are standardized in terms of level of arousal, i.e. the intensity of the evoked emotion, and valence, i.e. the level of pleasantness/unpleasantness, according to the Circumplex model of Affects (CMA). Twenty-two healthy subjects were enrolled in the experiment, which comprised four sessions with increasing arousal level. Within each session valence increased from positive to negative. An ad-hoc pattern recognition algorithm using a Leave-One-Subject-Out (LOSO) procedure based on a Quadratic Discriminant Classifier (QDC) was implemented. Our pattern recognition system was able to classify pleasant and unpleasant sessions with an accuracy of 71.59%. Therefore, we can suggest the use of the LPPsymb for emotion recognition.

Combining electroencephalographic activity and instantaneous heart rate for assessing brain-heart dynamics during visual emotional elicitation in healthy subjects.

Emotion perception, occurring in brain areas such as the prefrontal cortex and amygdala, involves autonomic responses affecting cardiovascular dynamics. However, how such brain-heart dynamics is further modulated by emotional valence (pleasantness/unpleasantness), also considering different arousing levels (the intensity of the emotional stimuli), is still unknown. To this extent, we combined electroencephalographic (EEG) dynamics and instantaneous heart rate estimates to study emotional processing in healthy subjects. Twenty-two healthy volunteers were elicited through affective pictures gathered from the International Affective Picture System. The experimental protocol foresaw 110 pictures, each of which lasted 10 s, associated to 25 different combinations of arousal and valence levels, including neutral elicitations. EEG data were processed using short-time Fourier transforms to obtain time-varying maps of cortical activation, whereas the associated instantaneous cardiovascular dynamics was estimated in the time and frequency domains through inhomogeneous point-process models. Brain-heart linear and nonlinear coupling was estimated through the maximal information coefficient (MIC). Considering EEG oscillations in theθband (4-8 Hz), MIC highlighted significant arousal-dependent changes between positive and negative stimuli, especially occurring at intermediate arousing levels through the prefrontal cortex interplay. Moreover, high arousing elicitations seem to mitigate changes in brain-heart dynamics in response to pleasant/unpleasant visual elicitation.

Brain-heart linear and nonlinear dynamics during visual emotional elicitation in healthy subjects.

This study investigates brain-heart dynamics during visual emotional elicitation in healthy subjects through linear and nonlinear coupling measures of EEG spectrogram and instantaneous heart rate estimates. To this extent, affective pictures including different combinations of arousal and valence levels, gathered from the International Affective Picture System, were administered to twenty-two healthy subjects. Time-varying maps of cortical activation were obtained through EEG spectral analysis, whereas the associated instantaneous heartbeat dynamics was estimated using inhomogeneous point-process linear models. Brain-Heart linear and nonlinear coupling was estimated through the Maximal Information Coefficient (MIC), considering EEG time-varying spectra and point-process estimates defined in the time and frequency domains. As a proof of concept, we here show preliminary results considering EEG oscillations in the θ band (4-8 Hz). This band, indeed, is known in the literature to be involved in emotional processes. MIC highlighted significant arousal-dependent changes, mediated by the prefrontal cortex interplay especially occurring at intermediate arousing levels. Furthermore, lower and higher arousing elicitations were associated to not significant brain-heart coupling changes in response to pleasant/unpleasant elicitations.

Point-process nonlinear autonomic assessment of depressive states in bipolar patients.

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems". OBJECTIVES: The goal of this work is to apply a computational methodology able to characterize mood states in bipolar patients through instantaneous analysis of heartbeat dynamics. METHODS: A Point-Process-based Nonlinear Autoregressive Integrative (NARI) model is applied to analyze data collected from five bipolar patients (two males and three females, age 42.4 ± 10.5 range 32 -56) undergoing a dedicated affective elicitation protocol using images from the International Affective Picture System (IAPS) and Thematic Apperception Test (TAT). The study was designed within the European project PSYCHE (Personalised monitoring SYstems for Care in mental HEalth). RESULTS: RESULTS demonstrate that the inclusion of instantaneous higher order spectral (HOS) features estimated from the NARI nonlinear assessment significantly improves the accuracy in successfully recognizing specific mood states such as euthymia and depression with respect to results using only linear indices. In particular, a specificity of 74.44% using the instantaneous linear features set, and 99.56% using also the nonlinear feature set were achieved. Moreover, IAPS emotional elicitation resulted in a more discriminant procedure with respect to the TAT elicitation protocol. CONCLUSIONS: A significant pattern of instantaneous heartbeat features was found in depressive and euthymic states despite the inter-subject variability. The presented point-process Heart Rate Variability (HRV) nonlinear methodology provides a promising application in the field of mood assessment in bipolar patients.

Quantitative EEG analysis in minimally conscious state patients during postural changes.

Mobilization and postural changes of patients with cognitive impairment are standard clinical practices useful for both psychic and physical rehabilitation process. During this process, several physiological signals, such as Electroen-cephalogram (EEG), Electrocardiogram (ECG), Photopletysmography (PPG), Respiration activity (RESP), Electrodermal activity (EDA), are monitored and processed. In this paper we investigated how quantitative EEG (qEEG) changes with postural modifications in minimally conscious state patients. This study is quite novel and no similar experimental data can be found in the current literature, therefore, although results are very encouraging, a quantitative analysis of the cortical area activated in such postural changes still needs to be deeply investigated. More specifically, this paper shows EEG power spectra and brain symmetry index modifications during a verticalization procedure, from 0 to 60 degrees, of three patients in Minimally Consciousness State (MCS) with focused region of impairment. Experimental results show a significant increase of the power in ß band (12 - 30 Hz), commonly associated to human alertness process, thus suggesting that mobilization and postural changes can have beneficial effects in MCS patients.

On the deconvolution analysis of electrodermal activity in bipolar patients.

People affected by bipolar disorders experience alternating states of depression with episodes of mania or hypomania. This mental can lead to a poor handling of daily routines, can worsen personal relationships, and often can be life-threatening. This preliminary study aims at investigating how the autonomic nervous system, in terms of electrodermal activity, responds to specific controlled emotional stimuli in bipolar patients. More specifically, we present here a method to deploy the analysis of ElectroDermal Activity (EDA) to discriminate clinical mood states. EDA was analyzed by using a deconvolution method to separate tonic from phasic components. The three subjects recruited and the experimental protocol used here is part of the European project PSYCHE. Preliminary results show that the bipolar mood states can be related to electrodermal tonic activity.

SoC CMOS UWB Pulse Radar Sensor for Contactless Respiratory Rate Monitoring.

An ultra wideband (UWB) system-on-chip radar sensor for respiratory rate monitoring has been realized in 90 nm CMOS technology and characterized experimentally. The radar testchip has been applied to the contactless detection of the respiration activity of adult and baby. The field operational tests demonstrate that the UWB radar sensor detects the respiratory rate of person under test (adult and baby) associated with sub-centimeter chest movements, allowing the continuous-time non-invasive monitoring of hospital patients and other people at risk of obstructive apneas such as babies in cot beds, or other respiratory diseases.

EEG complexity drug-induced changes in disorders of consciousness: a preliminary report.

The goal of this work is to investigate EEG (ElectroEncephaloGram) dynamics after drug intake in patients being in states of Disorders Of Consciousness (DOC) after brain injury. Four patients were involved in the study. All the patients exhibit cerebral lesions located in the same anatomical region. Two nonlinear indexes, such as Lempel-Ziv Complexity (LZC) and Approximate Entropy (ApEn), along with power spectra, were calculated for EEG signals gathered from electrodes placed on both injured and non-injured regions. Experimental results show that after drug administration the two nonlinear indexes calculated from EEG taken from injured regions increase (p < 0.001) while power spectra decrease or remain unchanged. These results do not pretend to draw conclusions about consciousness level either suggest promising therapeutical treatments, but represent only an experimental evidence about the change in the EEG complexity after drug administration.

Wearable system-on-a-chip UWB radar for contact-less cardiopulmonary monitoring: present status.

The present status of the project aimed at the realization of an innovative wearable system-on-chip UWB radar for the cardiopulmonary monitoring is presented. The overall system consists of a wearable wireless interface including a fully integrated UWB radar for the detection of the heart beat and breath rates, and a IEEE 802.15.4 ZigBee low-power radio interface. The principle of operation of the UWB radar for the monitoring of the heart wall is summarized. With respect to the prior art, this paper reports the results of the experimental characterization of the intra-body channel loss, which has been carried out successfully in order to validate the theoretical model employed for the radar system analysis. Moreover, the main building blocks of the radar have been manufactured in 90 nm CMOS technology by ST-Microelectronics and the relevant performance are resulted in excellent agreement with those expected by post-layout simulations.

Wearable microwave radiometers for remote fire detection: System-on-Chip (SoC) design and proof of the concept.

The paper reports the present status of the project aimed at the realization of a wearable low-cost low-power System-on-Chip (SoC) 13-GHz passive microwave radiometer in CMOS 90 nm technology. This sensor has been thought to be inserted into the firemen jacket in order to help them in the detection of a hidden fire behind a door or a wall, especially where the IR technology fail. With respect of the prior art, the SoC is further developed and a proof of the concept is provided by means of a discrete-component prototype.

Wearable system-on-a-chip radiometer for remote temperature sensing and its application to the safeguard of emergency operators.

The remote sensing and the detection of events that may represent a danger for human beings have become more and more important thanks to the latest advances of the technology. A microwave radiometer is a sensor capable to detect a fire or an abnormal increase of the internal temperature of the human body (hyperthermia), or an onset of a cancer, or even meteorological phenomena (forest fires, pollution release, ice formation on road pavement). In this paper, the overview of a wearable low-cost low-power system-on-a-chip (SoaC) 13 GHz passive microwave radiometer in CMOS 90 nm technology is presented. In particular, we focused on its application to the fire detection for civil safeguard. In detail, this sensor has been thought to be inserted into the fireman jacket in order to help the fireman in the detection of a hidden fire behind a door or a wall. The simulation results obtained by Ptolemy system simulation have confirmed the feasibility of such a SoaC microwave radiometer in a low-cost standard silicon technology for temperature remote sensing and, in particular, for its application to the safeguard of emergency operators.

Performance analysis and early validation of a bi-modal ultrasound transducer.

In this paper we report on results from experiments performed on a bi-modal piezoelectric transducer used both as an active ultrasound transceiver and a passive acoustic sensor. The transducer, which has a low Q factor in order to exhibit a sufficiently broad bandwidth, will be integrated into a wearable system. In particular, it is placed, along with ECG fabric electrodes, within a textile belt wrapped around the chest. The transducer behaves as an acoustic sensor at low frequency and as an ultrasound transducer at high frequency. The low-frequency acoustic signals were compared with the analogue signals acquired simultaneously by commercial biomedical sensors. These signals provide information about the respiratory activity and heart apex pulse. A comparative analysis was performed both in the time and frequency domain and results were discussed. Moreover, the same transducer used at high frequencies is able to generate ultrasound signals which can bounce off the target organ, the heart, and receive the back-propagated echoes. The experimental validation was done by means of a comparison between the spatial interval inferred from time delay of the return echoes detected by the transducer and the actual distance from the target. This information, in addition to ECG signals, can provide helpful cues for the cardiac status of the subject, both in terms of prevention and diagnosis.