Publications

Many studies have focused on novel noninvasive techniques to monitor respiratory rate such as bioimpedance. We propose an algorithm to detect respiratory phases using wearable bioimpedance to compute time parameters like respiratory rate, inspiratory and expiratory times, and duty cycle. The proposed algorithm was compared with two other algorithms from literature designed to estimate the respiratory rate using physiological signals like bioimpedance. We acquired bioimpedance and airflow from 50 chronic obstructive pulmonary disease (COPD) patients during an inspiratory loading protocol. We compared performance of the algorithms by computing accuracy and mean average percentage error (MAPE) between the bioimpedance parameters and the reference parameters from airflow. We found similar performance for the three algorithms in terms of accuracy (>0.96) and respiratory time and rate errors (<3.42 %). However, the proposed algorithm showed lower MAPE in duty cycle (10.18 %), inspiratory time (10.65 %) and expiratory time (8.61 %). Furthermore, only the proposed algorithm kept the statistical differences in duty cycle between COPD severity levels that were observed using airflow. Accordingly, we suggest bioimpedance to monitor breathing pattern parameters in home situations.Clinical relevance - This study exhibits the suitability of wearable thoracic bioimpedance to detect respiratory phases and to compute accurate breathing pattern parameters. © 2021 IEEE.

JTD Keywords: algorithms, copd, signals, Algorithm, Algorithms, Bioimpedance, Breathing rate, Chronic obstructive lung disease, Electronic device, Human, Humans, Lung, Pulmonary disease, chronic obstructive, Respiratory rate, Wearable electronic devices

In this work, we evaluated a non-linear approach to estimate morphological variations in ECG depolarization, in the context of intermittent hypoxia (IH). Obstructive apnea sequences were provoked for 15 minutes in anesthetized Sprague-Dawley rats, alternating with equal periods of normal breathing, in a recurrent obstructive sleep apnea (OSA) model. Each apnea episode lasted 15 s, while the frequency used for each sequence was randomly selected. Average heartbeats obtained before the start and at the end of each episode, were delineated to extract only the QRS wave. Then, the segmented QRS waves were non-linearly aligned using the dynamic time warping (DWT) algorithm. Morphological QRS changes in both the amplitude and temporal domains were estimated from this alignment procedure. The hypoxic and basal segments were analyzed using ECG (lead I) recordings acquired during the experiment. To assess the effects of IH over time, the changes relative to the basal QRS wave were determined, in the intervals prior to each successive events until the end of the experiment. The results showed a progressive increase in the amplitude and time-domain morphological markers of the QRS wave along the experiment, which were strongly correlated with the changes in traditional QRS markers (r ≈ 0.9). Significant changes were found between pre-apnea and hypoxic measures only for the time-domain analysis (p<0.001), probably due to the short duration of the simulated apnea episodes.Clinical relevance Increased variability in ECG depolarization morphology during recurrent hypoxic episodes would be closely related to the expression of cardiovascular dysfunction in OSA patients.

JTD Keywords: Electrocardiography, Rats, Heart rate variability, Sleep apnea, Protocols, Heuristic algorithms

Can machines be endowed with morality? We argue that morality in the descriptive or epistemic sense can be extended to artificial systems. Following arguments from evolutionary game-theory, we identify two main ingredients required to operationalize this notion of morality in machines. The first, being a group theory of mind, and the second, being an assignment of valence. We make the case for the plausibility of these operations in machines without reference to any form of intentionality or consciousness. The only systems requirements needed to support the above two operations are autonomous goal-directed action and the ability to interact and learn from the environment. Following this we have outlined a theoretical framework based on conceptual spaces and valence assignments to gauge latent morality in autonomous machines and algorithms.

JTD Keywords: Autonomous systems, Ethics of algorithms, Goal-directed action, Philosophy of morality, Qualia, Theory of mind

This book constitutes the proceedings of the 8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019, held in Nara, Japan, in July 2019. The 26 full and 16 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Biomimetics, Computer architecture, Human robot interaction, Human-Computer Interaction (HCI), Humanoid robot, Image processing, Learning algorithms, Mobile robots, Multipurpose robots, Neural networks, Quadruped robots, Reinforcement learning, Robot learning, Robotics, Robots, Sensor, Sensors, Swarm robotics, User interfaces

This book constitutes the proceedings of the 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, held in Paris, France, in July 2018. The 40 full and 18 short papers presented in this volume were carefully reviewed and selected from 60 submissions. The theme of the conference targeted at the intersection of research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial neural network, Bio-actuators, Bio-robotics, Biohybrid systems, Biomimetics, Bipedal robots, Earthoworm-like robots, Robotics, Decision-making, Tactile sensing, Soft robots, Locomotion, Insects, Sensors, Actuators, Robots, Artificial intelligence, Neural networks, Motion planning, Learning algorithms

Heart motion compensation is a challenging problem within medical robotics and it is still considered an open research area due to the lack of robustness. As it can be formulated as an energy minimization problem, an optimization technique is needed. The selection of an adequate method has a significant impact over the global solution. For this reason, a new methodology is presented here for solving heart motion compensation in which the central topic is oriented to increase robustness with the goal of achieving a balance between efficiency and efficacy. Particularly, genetic algorithms are used as optimization technique since they can be adapted to any real application, complex and oriented to work in real-time problems.

JTD Keywords: Genetic Algorithms, Deformation, Stochastic Optimization, Beating Heart Surgery, Robotic Assisted Surgery

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

JTD Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

Purpose: 123I-labelled radioligands are commonly used for single-photon emission computed tomography (SPECT) imaging of the dopaminergic system to study the dopamine transporter binding. The aim of this work was to compare the quantitative capabilities of two different SPECT systems through Monte Carlo (MC) simulation. Methods: The SimSET MC code was employed to generate simulated projections of a numerical phantom for two gamma cameras equipped with a parallel and a fan-beam collimator, respectively. A fully 3D iterative reconstruction algorithm was used to compensate for attenuation, the spatially variant point spread function (PSF) and scatter. A post-reconstruction partial volume effect (PVE) compensation was also developed. Results: For both systems, the correction for all degradations and PVE compensation resulted in recovery factors of the theoretical specific uptake ratio (SUR) close to 100%. For a SUR value of 4, the recovered SUR for the parallel imaging system was 33% for a reconstruction without corrections (OSEM), 45% for a reconstruction with attenuation correction (OSEM-A), 56% for a 3D reconstruction with attenuation and PSF corrections (OSEM-AP), 68% for OSEM-AP with scatter correction (OSEM-APS) and 97% for OSEM-APS plus PVE compensation (OSEM-APSV). For the fan-beam imaging system, the recovered SUR was 41% without corrections, 55% for OSEM-A, 65% for OSEM-AP, 75% for OSEM-APS and 102% for OSEM-APSV. Conclusion: Our findings indicate that the correction for degradations increases the quantification accuracy, with PVE compensation playing a major role in the SUR quantification. The proposed methodology allows us to reach similar SUR values for different SPECT systems, thereby allowing a reliable standardisation in multicentric studies.

JTD Keywords: Brain SPECT, Monte Carlo methods, Receptor imaging, Reconstruction quantification, SPECT instrumentation and algorithms

In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.

JTD Keywords: Adult, Algorithms, Artificial Intelligence, Cognition, Electroencephalography, Female, Humans, Male, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Task Performance and Analysis, User-Computer Interface