Stress Evaluation in Simulated Autonomous and Manual Driving through the Analysis of Skin Potential Response and Electrocardiogram Signals.

The evaluation of car drivers' stress condition is gaining interest as research on Autonomous Driving Systems (ADS) progresses. The analysis of the stress response can be used to assess the acceptability of ADS and to compare the driving styles of different autonomous drive algorithms. In this contribution, we present a system based on the analysis of the Electrodermal Activity Skin Potential Response (SPR) signal, aimed to reveal the driver's stress induced by different driving situations. We reduce motion artifacts by processing two SPR signals, recorded from the hands of the subjects, and outputting a single clean SPR signal. Statistical features of signal blocks are sent to a Supervised Learning Algorithm, which classifies between stress and normal driving (non-stress) conditions. We present the results obtained from an experiment using a professional driving simulator, where a group of people is asked to undergo manual and autonomous driving on a highway, facing some unexpected events meant to generate stress. The results of our experiment show that the subjects generally appear more stressed during manual driving, indicating that the autonomous drive can possibly be well received by the public. During autonomous driving, however, significant peaks of the SPR signal are evident during unexpected events. By examining the electrocardiogram signal, the average heart rate is generally higher in the manual case compared to the autonomous case. This further supports our previous findings, even if it may be due, in part, to the physical activity involved in manual driving.

Car Driver's Sympathetic Reaction Detection Through Electrodermal Activity and Electrocardiogram Measurements.

OBJECTIVE: in this paper we propose a system to detect a subject's sympathetic reaction, which is related to unexpected or challenging events during a car drive. METHODS: we use the Electrocardiogram (ECG) signal and the Skin Potential Response (SPR) signal, which has several advantages with respect to other Electrodermal (EDA) signals. We record one SPR signal for each hand, and use an algorithm that, selecting the smoother signal, is able to remove motion artifacts. We extract statistical features from the ECG and SPR signals in order to classify signal segments and identify the presence or absence of emotional events via a Supervised Learning Algorithm. The experiments were carried out in a company which specializes in driving simulator equipment, using a motorized platform and a driving simulator. Different subjects were tested with this setup, with different challenging events happening on predetermined locations on the track. RESULTS: we obtain an Accuracy as high as 79.10% for signal blocks and as high as 91.27% for events. CONCLUSION: results demonstrate the good performance of the presented system in detecting sympathetic reactions, and the effectiveness of the motion artifact removal procedure. SIGNIFICANCE: our work demonstrates the possibility to classify the emotional state of the driver, using the ECG and EDA signals and a slightly invasive setup. In particular, the proposed use of SPR and of the motion artifact removal procedure are crucial for the effectiveness of the system.

Matched Filtering for Heart Rate Estimation on Compressive Sensing ECG Measurements.

OBJECTIVE: Compressive sensing (CS) has recently been applied as a low-complexity compression framework for long-term monitoring of electrocardiogram (ECG) signals using wireless body sensor networks. Long-term recording of ECG signals can be useful for diagnostic purposes and to monitor the evolution of several widespread diseases. In particular, beat-to-beat intervals provide important clinical information, and these can be derived from the ECG signal by computing the distance between QRS complexes (R-peaks). Numerous methods for R-peak detection are available for uncompressed ECG. However, in the case of compressed sensed data, signal reconstruction can be performed with relatively complex optimization algorithms, which may require significant energy consumption. This paper addresses the problem of heart rate estimation from CS ECG recordings, avoiding the reconstruction of the entire signal. METHODS: We consider a framework, where the ECG signals are represented under the form of CS linear measurements. The QRS locations are estimated in the compressed domain by computing the correlation of the compressed ECG and a known QRS template. RESULTS: Experiments on actual ECG signals show that our novel solution is competitive with methods applied to the reconstructed signals. CONCLUSION: Avoiding the reconstruction procedure, the proposed method proves to be very convenient for real-time low-power applications.

Atrial fibrillation detection on compressed sensed ECG.

OBJECTIVE: Compressive sensing (CS) approaches to electrocardiogram (ECG) analysis provide efficient methods for real time encoding of cardiac activity. In doing so, it is important to assess the downstream effect of the compression on any signal processing and classification algorithms. CS is particularly suitable for low power wearable devices, thanks to its low-complex digital or hardware implementation that directly acquires a compressed version of the signal through random projections. In this work, we evaluate the impact of CS compression on atrial fibrillation (AF) detection accuracy. APPROACH: We compare schemes with data reconstruction based on wavelet and Gaussian models, followed by a P&T-based identification of beat-to-beat (RR) intervals on the MIT-BIH atrial fibrillation database. A state-of-the-art AF detector is applied to the RR time series and the accuracy of the AF detector is then evaluated under different levels of compression. We also consider a new beat detection procedure which operates directly in the compressed domain, avoiding costly signal reconstruction procedures. MAIN RESULTS: We demonstrate that for compression ratios up to 30[Formula: see text] the AF detector applied to RR intervals derived from the compressed signal exhibits results comparable to those achieved when employing a standard QRS detector on the raw uncompressed signals, and exhibits only a 2% accuracy drop at a compression ratio of 60%. We also show that the Gaussian-based reconstruction approach is superior in terms of AF detection accuracy, with a negligible drop in performance at a compression ratio ⩽75%, compared to a wavelet approach, which exhibited a significant drop in accuracy at a compression ratio ⩾65%. SIGNIFICANCE: The results suggest that CS should be considered as a plausible methodology for both efficient real time ECG compression (at moderate compression rates) and for offline analysis (at high compression rates).

Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals.

This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%.

Separation and Analysis of Fetal-ECG Signals From Compressed Sensed Abdominal ECG Recordings.

OBJECTIVE: Analysis of fetal electrocardiogram (f-ECG) waveforms as well as fetal heart-rate (fHR) evaluation provide important information about the condition of the fetus during pregnancy. A continuous monitoring of f-ECG, for example using the technologies already applied for adults ECG tele-monitor-ing (e.g., Wireless Body Sensor Networks (WBSNs)), may increase early detection of fetal arrhythmias. In this study, we propose a novel framework, based on compressive sensing (CS) theory, for the compression and joint detection/classification of mother and fetal heart beats. METHODS: Our scheme is based on the sparse representation of the components derived from independent component analysis (ICA), which we propose to apply directly in the compressed domain. Detection and classification is based on the activated atoms in a specifically designed reconstruction dictionary. RESULTS: Validation of the proposed compression and detection framework has been done on two publicly available datasets, showing promising results (sensitivity S = 92.5 %, P += 92 % , F1 = 92.2 % for the Silesia dataset and S = 78 % , P += 77 %, F1 = 77.5 % for the Challenge dataset A, with average reconstruction quality PRD = 8.5 % and PRD = 7.5 %, respectively). CONCLUSION: The experiments confirm that the proposed framework may be used for compression of abdominal f-ECG and to obtain real-time information of the fHR, providing a suitable solution for real time, very low-power f-ECG monitoring. SIGNIFICANCE: To the authors' knowledge, this is the first time that a framework for the low-power CS compression of fetal abdominal ECG is proposed combined with a beat detector for an fHR estimation.

A visit paid to Jung by Alwine von Keller.

In the winter of 1943-1944, Jung had suffered a coronary thrombosis which almost cost him his life. During his illness, Jung experienced a series of visions, described in his Memories, Dreams, Reflections, which were also to influence significantly the development of his theoretical thinking. On 27(th) September 1944, Alwine von Keller (1878-1965) paid a visit to Jung, while he was still convalescing, in Zurich and documented her meeting with him in a series of notes, recently discovered, which testify to the fact that, at the time of their meeting, Jung was engaged in writing the 'Salt' chapter of Mysterium coniunctionis and investigating the alchemistic symbolism of the 'sea'. This theme seems to testify to a continuity of interests on Jung's part with the seminar he held at Eranos the previous year on the cartographic art of Opicinus de Canistris (1296-c.1352). With its addition of many unpublished details, Alwine von Keller's notes supplement the report which Jung made of his visions experienced during his sickness in MDR. In particular, these attest to the fact that Jung had attributed the terrible experience which he had endured to the problem of the conjunctio, which was confronting him from the theoretical point of view in his writing of Mysterium coniunctionis.

Opicinus de Canistris: some notes from Jung's unpublished Eranos Seminar on the medieval Codex Palatinus Latinus 1993.

Jung held an informal seminar for a limited number of students after the end of the Eranos Conference in August, 1943. All traces of this seminar were lost until the notes taken on it by one of the students, Alwine von Keller, were found in 2006. Jung's talk consisted of a psychological commentary on a series of images in the medieval Codex Palatinus Latinus 1993, attributed to Opicinus de Canistris (1296-c.1352), a fourteenth-century Italian clergyman, mystic, miniaturist, and cartographer. Jung interpreted Opicinus' images as a series of mandalas in which the Shadow, the dark principle, does not manage to be integrated into a balanced system. Opicinus tried to settle this division into opposites, which constitutes the main problem in modern times, while remaining inside the system of Christian doctrine. However, he did not succeed in his attempt to integrate the principle of the Shadow on the doctrinal level because he was not aware of the very same division in his own unconscious. Our article points out the features in the seminar where Jung seemed to show much more originality in his interpretation than other psychoanalytic studies on Opicinus or other analytical-psychological readings of medieval Christian art.

Energy cost and metabolic power in elite soccer: a new match analysis approach.

PURPOSE: Video match analysis is used for the assessment of physical performances of professional soccer players, particularly for the identification of "high intensities" considered as "high running speeds." However, accelerations are also essential elements setting metabolic loads, even when speed is low. We propose a more detailed assessment of soccer players' metabolic demands by video match analysis with the aim of also taking into account accelerations. METHODS: A recent study showed that accelerated running on a flat terrain is equivalent to running uphill at constant speed, the incline being dictated by the acceleration. Because the energy cost of running uphill is known, this makes it possible to estimate the instantaneous energy cost of accelerated running, the corresponding instantaneous metabolic power, and the overall energy expenditure, provided that the speed (and acceleration) is known. Furthermore, the introduction of individual parameters makes it possible to customize performance profiles, especially as it concerns energy expenditure derived from anaerobic sources. Data from 399 "Serie-A" players (mean +/- SD; age = 27 +/- 4 yr, mass = 75.8 +/- 5.0 kg, stature = 1.80 +/- 0.06 m) were collected during the 2007-2008 season. RESULTS: Mean match distance was 10,950 +/- 1044 m, and average energy expenditure was 61.12 +/- 6.57 kJ x kg(-1). Total distance covered at high power (>20 W x kg(-1)) amounted to 26% and corresponding energy expenditure to approximately 42% of the total. "High intensities" expressed as high-power output are two to three times larger than those based only on running speed. CONCLUSIONS: The present approach for the assessment of top-level soccer players match performance through video analysis allowed us to assess instantaneous metabolic power, thus redefining the concept of "high intensity" on the basis of actual metabolic power rather than on speed alone.