Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

A digital signal processing approach for affective sensing of a computer user through pupil diameter monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

Space time coding for polynomial phase modulated signals

Polynomial phase modulated (PPM) signals have been shown to provide improved error rate performance with respect to conventional modulation formats under additive white Gaussian noise and fading channels in single-input single-output (SISO) communication systems. In this dissertation, systems with two and four transmit antennas using PPM signals were presented. In both cases we employed full-rate space-time block codes in order to take advantage of the multipath channel. For two transmit antennas, we used the orthogonal space-time block code (OSTBC) proposed by Alamouti and performed symbol-wise decoding by estimating the phase coefficients of the PPM signal using three different methods: maximum-likelihood (ML), sub-optimal ML (S-ML) and the high-order ambiguity function (HAF). In the case of four transmit antennas, we used the full-rate quasi-OSTBC (QOSTBC) proposed by Jafarkhani. However, in order to ensure the best error rate performance, PPM signals were selected such as to maximize the QOSTBC’s minimum coding gain distance (CGD). Since this method does not always provide a unique solution, an additional criterion known as maximum channel interference coefficient (CIC) was proposed. Through Monte Carlo simulations it was shown that by using QOSTBCs along with the properly selected PPM constellations based on the CGD and CIC criteria, full diversity in flat fading channels and thus, low BER at high signal-to-noise ratios (SNR) can be ensured. Lastly, the performance of symbol-wise decoding for QOSTBCs was evaluated. In this case a quasi zero-forcing method was used to decouple the received signal and it was shown that although this technique reduces the decoding complexity of the system, there is a penalty to be paid in terms of error rate performance at high SNRs.

Endocrine regulation of dynamic communication signals in gymnotiform fish

Communication signals are shaped by the opposing selection pressures imposed by predators and mates. A dynamic signal might serve as an adaptive compromise between an inconspicuous signal that evades predators and an extravagant signal preferred by females. Such a signal has been described in the gymnotiform electric fish, Brachyhypopomus gauderio, which produces a sexually dimorphic electric organ discharge (EOD). The EOD varies on a circadian rhythm and in response to social cues. This signal plasticity is mediated by the slow action of androgens and rapid action of melanocortins. My dissertation research tested the hypotheses that (1) signal plasticity is related to sociality levels in gymnotiform species, and (2) differences in signal plasticity are regulated by differential sensitivity to androgen and melanocortin hormones. To assess the breadth of dynamic signaling within the order Gymnotiformes, I sampled 13 species from the five gymnotiform families. I recorded EODs to observe spontaneous signal oscillations after which I injected melanocortin hormones, saline control, or presented the fish with a conspecific. I showed that through the co-option of the ancient melanocortin pathway, gymnotiforms dynamically regulate EOD amplitude, spectral frequency, both, or neither. To investigate whether observed EOD plasticities are related to species-specific sociality I tested four species; two territorial, highly aggressive species, Gymnotus carapo and Apteronotus leptorhynchus, a highly gregarious species, Eigenmannia cf. virescens , and an intermediate short-lived species with a fluid social system, Brachyhypopomus gauderio. I examined the relationship between the androgens testosterone and 11-ketotestosterone, the melanocortin α-MSH, and their roles in regulating EOD waveform. I implanted all fish with androgen and blank silicone implants, and injected with α-MSH before and at the peak of implant effect. I found that waveforms of the most territorial and aggressive species were insensitive to hormone treatments; maintaining a static, stereotyped signal that preserves encoding of individual identity. Species with a fluid social system were most responsive to hormone treatments, exhibiting signals that reflect immediate condition and reproductive state. In conclusion, variation in gymnotiform signal plasticity is hormonally regulated and seems to reflect species-specific sociality.

Transcriptome Analysis Reveals New Insights into the Modulation of Endometrial Stromal Cell Receptive Phenotype by Embryo-Derived Signals Interleukin-1 and Human Chorionic Gonadotropin: Possible Involvement in Early Embryo Implantation

The presence of the conceptus in uterine cavity necessitates an elaborate network of interactions between the implanting embryo and a receptive endometrial tissue. We believe that embryo-derived signals play an important role in the remodeling and the extension of endometrial receptivity period. Our previous studies provided original evidence that human Chorionic Gonadotropin (hCG) modulates and potentiates endometrial epithelial as well as stromal cell responsiveness to interleukin 1 (IL1), one of the earliest embryonic signals, which may represent a novel pathway by which the embryo favors its own implantation and growth within the maternal endometrial host. The present study was designed to gain a broader understanding of hCG impact on the modulation of endometrial cell receptivity, and in particular, cell responsiveness to IL1 and the acquisition of growth-promoting phenotype capable of receiving, sustaining, and promoting early and crucial steps of embryonic development. Our results showed significant changes in the expression of genes involved in cell proliferation, immune modulation, tissue remodeling, apoptotic and angiogenic processes. This points to a relevant impact of these embryonic signals on the receptivity of the maternal endometrium, its adaptation to the implanting embryo and the creation of an environment that is favorable for the implantation and the growth of this latter within a new and likely hostile host tissue. Interestingly our data further identified a complex interaction between IL1 and hCG, which, despite a synergistic action on several significant endometrial target genes, may encompass a tight control of endogenous IL1 and extends to other IL1 family members.

Paleoenvironments and geochemical signals from the late Barremian to the middle Aptian in a Tethyan marginal basin, northeast Spain: Implications for carbon sequestration in restricted basins

The hallmark of oceanic anoxic event 1a (OAE1a) (early Aptian ~125 Ma) corresponds to worldwide deposition of black shales with total organic carbon (TOC) content > 2% and a δ13C positive excursion up to ~5‰. OAE1a has been related to large igneous province volcanism and dissociation of methane hydrates during the Lower Cretaceous. However, the occurrence of atypical, coeval and diachronous organic-rich deposits associated with OAE1a, which are also characterized by positive spikes of the δ 13C in epicontinental to restricted marine environments of the Tethys Ocean, indicates localized responses decoupled from complex global forcing factors. ^ The present research is a high-resolution, multiproxy approach to assess the paleoenvironmental conditions that led to enhanced carbon sequestration from the late Barremian to the middle Aptian in a restricted, Tethyan marginal basin prior to and during OAE1a. I studied the lower 240 m of the El Pui section, Organyà Basin, Spanish Pyrenees. The basin developed as the result of extensional tectonism linked to the opening of the Atlantic Ocean. At the field scale the section consists of a sequence of alternating beds of cm – m-scale, medium-gray to grayish-black limestones and marlstones with TOC up to ~4%. ^ The results indicate that the lowest 85 m of the section, from latest Barremian -earliest Aptian, characterize a deepening phase of the basin concomitant with sustained riverine flux and intensified primary productivity. These changes induced a shift in the sedimentation pattern and decreased the oxygen levels in the water column through organic matter respiration and limited ventilation of the basin. ^ The upper 155 m comprising the earliest – late-early Aptian document the occurrence of OAE1a and its associated geochemical signatures (TOC up to 3% and a positive shift in δ13C of ~5‰). However, a low enrichment of redox-sensitive trace elements indicates that the basin did not achieve anoxic conditions. The results also suggest that a shallower-phase of the basin, coeval with platform progradation, may have increased ventilation of the basin at the same time that heightened sedimentation rates and additional input of organic matter from terrestrial sources increased the burial and preservation rate of TOC in the sediment.^

A Digital Signal Processing Approach for Affective Sensing of a Computer User through Pupil Diameter Monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

Playing with sound and gesture in digital audio games

This article introduces the genre of a digital audio game and discusses selected play interaction solutions implemented in the Audio Game Hub, a prototype designed and evaluated in the years 2014 and 2015 at the Gamification Lab at Leuphana University Lüneburg.1 The Audio Game Hub constitutes a set of familiar playful activities (aiming at a target, reflex-based reacting to sound signals, labyrinth exploration) and casual games (e.g. Tetris, Memory) adapted to the digital medium and converted into the audio sphere, where the player is guided predominantly or solely by sound. The authors will discuss the design questions raised at early stages of the project, and confront them with the results of user experience testing performed on two groups of sighted and one group of visually impaired gamers.

Phase noise and spur reduction in an array of direct digital synthesizers

Many applications, including communications, test and measurement, and radar, require the generation of signals with a high degree of spectral purity. One method for producing tunable, low-noise source signals is to combine the outputs of multiple direct digital synthesizers (DDSs) arranged in a parallel configuration. In such an approach, if all noise is uncorrelated across channels, the noise will decrease relative to the combined signal power, resulting in a reduction of sideband noise and an increase in SNR. However, in any real array, the broadband noise and spurious components will be correlated to some degree, limiting the gains achieved by parallelization. This thesis examines the potential performance benefits that may arise from using an array of DDSs, with a focus on several types of common DDS errors, including phase noise, phase truncation spurs, quantization noise spurs, and quantizer nonlinearity spurs. Measurements to determine the level of correlation among DDS channels were made on a custom 14-channel DDS testbed. The investigation of the phase noise of a DDS array indicates that the contribution to the phase noise from the DACs can be decreased to a desired level by using a large enough number of channels. In such a system, the phase noise qualities of the source clock and the system cost and complexity will be the main limitations on the phase noise of the DDS array. The study of phase truncation spurs suggests that, at least in our system, the phase truncation spurs are uncorrelated, contrary to the theoretical prediction. We believe this decorrelation is due to the existence of an unidentified mechanism in our DDS array that is unaccounted for in our current operational DDS model. This mechanism, likely due to some timing element in the FPGA, causes some randomness in the relative phases of the truncation spurs from channel to channel each time the DDS array is powered up. This randomness decorrelates the phase truncation spurs, opening the potential for SFDR gain from using a DDS array. The analysis of the correlation of quantization noise spurs in an array of DDSs shows that the total quantization noise power of each DDS channel is uncorrelated for nearly all values of DAC output bits. This suggests that a near N gain in SQNR is possible for an N-channel array of DDSs. This gain will be most apparent for low-bit DACs in which quantization noise is notably higher than the thermal noise contribution. Lastly, the measurements of the correlation of quantizer nonlinearity spurs demonstrate that the second and third harmonics are highly correlated across channels for all frequencies tested. This means that there is no benefit to using an array of DDSs for the problems of in-band quantizer nonlinearities. As a result, alternate methods of harmonic spur management must be employed.

Paleoenvironments and Geochemical Signals from the Late Barremian to the Middle Aptian in a Tethyan Marginal Basin, Northeast Spain: Implications for Carbon Sequestration in Restricted Basins

The hallmark of oceanic anoxic event 1a (OAE1a) (early Aptian ~125 Ma) corresponds to worldwide deposition of black shales with total organic carbon (TOC) content > 2% and a d13C positive excursion up to ~5‰. OAE1a has been related to large igneous province volcanism and dissociation of methane hydrates during the Lower Cretaceous. However, the occurrence of atypical, coeval and diachronous organic-rich deposits associated with OAE1a, which are also characterized by positive spikes of the d13C in epicontinental to restricted marine environments of the Tethys Ocean, indicates localized responses decoupled from complex global forcing factors. The present research is a high-resolution, multiproxy approach to assess the paleoenvironmental conditions that led to enhanced carbon sequestration from the late Barremian to the middle Aptian in a restricted, Tethyan marginal basin prior to and during OAE1a. I studied the lower 240 m of the El Pui section, Organyà Basin, Spanish Pyrenees. The basin developed as the result of extensional tectonism linked to the opening of the Atlantic Ocean. At the field scale the section consists of a sequence of alternating beds of cm – m-scale, medium-gray to grayish-black limestones and marlstones with TOC up to ~4%. The results indicate that the lowest 85 m of the section, from latest Barremian –earliest Aptian, characterize a deepening phase of the basin concomitant with sustained riverine flux and intensified primary productivity. These changes induced a shift in the sedimentation pattern and decreased the oxygen levels in the water column through organic matter respiration and limited ventilation of the basin. The upper 155 m comprising the earliest – late-early Aptian document the occurrence of OAE1a and its associated geochemical signatures (TOC up to 3% and a positive shift in d13C of ~5‰). However, a low enrichment of redox-sensitive trace elements indicates that the basin did not achieve anoxic conditions. The results also suggest that a shallower-phase of the basin, coeval with platform progradation, may have increased ventilation of the basin at the same time that heightened sedimentation rates and additional input of organic matter from terrestrial sources increased the burial and preservation rate of TOC in the sediment.

[In search of] Digital biomarkers for objective pain assessment

Pain is a highly complex phenomenon involving intricate neural systems, whose interactions with other physiological mechanisms are not fully understood. Standard pain assessment methods, relying on verbal communication, often fail to provide reliable and accurate information, which poses a critical challenge in the clinical context. In the era of ubiquitous and inexpensive physiological monitoring, coupled with the advancement of artificial intelligence, these new tools appear as the natural candidates to be tested to address such a challenge. This thesis aims to conduct experimental research to develop digital biomarkers for pain assessment. After providing an overview of the state-of-the-art regarding pain neurophysiology and assessment tools, methods for appropriately conditioning physiological signals and controlling confounding factors are presented. The thesis focuses on three different pain conditions: cancer pain, chronic low back pain, and pain experienced by patients undergoing neurorehabilitation. The approach presented in this thesis has shown promise, but further studies are needed to confirm and strengthen these results. Prior to developing any models, a preliminary signal quality check is essential, along with the inclusion of personal and health information in the models to limit their confounding effects. A multimodal approach is preferred for better performance, although unimodal analysis has revealed interesting aspects of the pain experience. This approach can enrich the routine clinical pain assessment procedure by enabling pain to be monitored when and where it is actually experienced, and without the involvement of explicit communication,. This would improve the characterization of the pain experience, aid in antalgic therapy personalization, and bring timely relief, with the ultimate goal of improving the quality of life of patients suffering from pain.

Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.

Transition From Glass To Digital Slide Microscopy In The Teaching Of Oral Pathology In A Brazilian Dental School.

Several medical and dental schools have described their experience in the transition from conventional to digital microscopy in the teaching of general pathology and histology disciplines; however, this transitional process has scarcely been reported in the teaching of oral pathology. Therefore, the objective of the current study is to report the transition from conventional glass slide to virtual microscopy in oral pathology teaching, a unique experience in Latin America. An Aperio ScanScope® scanner was used to digitalize histological slides used in practical lectures of oral pathology. The challenges and benefits observed by the group of Professors from the Piracicaba Dental School (Brazil) are described and a questionnaire to evaluate the students' compliance to this new methodology was applied. An improvement in the classes was described by the Professors who mainly dealt with questions related to pathological changes instead of technical problems; also, a higher interaction with the students was described. The simplicity of the software used and the high quality of the virtual slides, requiring a smaller time to identify microscopic structures, were considered important for a better teaching process. Virtual microscopy used to teach oral pathology represents a useful educational methodology, with an excellent compliance of the dental students.

Avaliação de técnicas de classificação digital de imagens landsat em diferentes padrões de cobertura da terra em Rondônia

Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.

Modelo de inclusão digital para construção do conhecimento em qualidade de vida e atividade fisica

Universidade Estadual de Campinas. Faculdade de Educação Física