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  • 1.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Snäll, Jonatan
    KTH, School of Technology and Health (STH).
    Aslamy, Benjamin
    KTH, School of Technology and Health (STH).
    Abtahi, Shirin
    KTH, School of Technology and Health (STH).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Boras, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institute, Sweden.
    Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 1, p. 93-109Article in journal (Refereed)
    Abstract [en]

    Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

  • 2.
    Atefi, Seyed Reza
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Thorlin, Thorleif
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Stroke Damage Detection Using Classification Trees on Electrical Bioimpedance Cerebral Spectroscopy Measurements2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 8, p. 10074-10086Article in journal (Refereed)
    Abstract [en]

    After cancer and cardio-vascular disease, stroke is the third greatest cause of death worldwide. Given the limitations of the current imaging technologies used for stroke diagnosis, the need for portable non-invasive and less expensive diagnostic tools is crucial. Previous studies have suggested that electrical bioimpedance (EBI) measurements from the head might contain useful clinical information related to changes produced in the cerebral tissue after the onset of stroke. In this study, we recorded 720 EBI Spectroscopy (EBIS) measurements from two different head regions of 18 hemispheres of nine subjects. Three of these subjects had suffered a unilateral haemorrhagic stroke. A number of features based on structural and intrinsic frequency-dependent properties of the cerebral tissue were extracted. These features were then fed into a classification tree. The results show that a full classification of damaged and undamaged cerebral tissue was achieved after three hierarchical classification steps. Lastly, the performance of the classification tree was assessed using Leave-One-Out Cross Validation (LOO-CV). Despite the fact that the results of this study are limited to a small database, and the observations obtained must be verified further with a larger cohort of patients, these findings confirm that EBI measurements contain useful information for assessing on the health of brain tissue after stroke and supports the hypothesis that classification features based on Cole parameters, spectral information and the geometry of EBIS measurements are useful to differentiate between healthy and stroke damaged brain tissue.

  • 3.
    Bagula, Antoine
    et al.
    University of Cape Town.
    Inggs, Gordon
    University of Cape Town.
    Scott, Simon
    University of Cape Town.
    Zennaro, Marco
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Telecommunication Systems Laboratory, TSLab.
    On the Relevance of Using Open Wireless Sensor Networks in Environment Monitoring2009In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 9, no 6, p. 4845-4868Article in journal (Refereed)
    Abstract [en]

    This paper revisits the problem of the readiness for field deployments of wireless sensor networks by assessing the relevance of using Open Hardware and Software motes for environment monitoring. We propose a new prototype wireless sensor network that fine-tunes SquidBee motes to improve the life-time and sensing performance of an environment monitoring system that measures temperature, humidity and luminosity. Building upon two outdoor sensing scenarios, we evaluate the performance of the newly proposed energy-aware prototype solution in terms of link quality when expressed by the Received Signal Strength, Packet Loss and the battery lifetime. The experimental results reveal the relevance of using the Open Hardware and Software motes when setting up outdoor wireless sensor networks.

  • 4.
    Cheng, Xiaogang
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS). Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210003, Jiangsu, Peoples R China.;Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden.
    Yang, Bin
    Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden.;Xian Univ Architecture & Technol, Sch Environm & Municipal Engn, Xian 710055, Shaanxi, Peoples R China..
    Liu, Guoqing
    Nanjing Tech Univ, Sch Phys & Math Sci, Nanjing 211800, Jiangsu, Peoples R China..
    Olofsson, Thomas
    Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden..
    Li, Haibo
    KTH, School of Electrical Engineering and Computer Science (EECS). Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210003, Jiangsu, Peoples R China..
    A Total Bounded Variation Approach to Low Visibility Estimation on Expressways2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 2, article id 392Article in journal (Refereed)
    Abstract [en]

    Low visibility on expressways caused by heavy fog and haze is a main reason for traffic accidents. Real-time estimation of atmospheric visibility is an effective way to reduce traffic accident rates. With the development of computer technology, estimating atmospheric visibility via computer vision becomes a research focus. However, the estimation accuracy should be enhanced since fog and haze are complex and time-varying. In this paper, a total bounded variation (TBV) approach to estimate low visibility (less than 300 m) is introduced. Surveillance images of fog and haze are processed as blurred images (pse udo-blurred images), while the surveillance images at selected road points on sunny days are handled as clear images, when considering fog and haze as noise superimposed on the clear images. By combining image spectrum and TBV, the features of foggy and hazy images can be extracted. The extraction results are compared with features of images on sunny days. Firstly, the low visibility surveillance images can be filtered out according to spectrum features of foggy and hazy images. For foggy and hazy images with visibility less than 300 m, the high-frequency coefficient ratio of Fourier (discrete cosine) transform is less than 20%, while the low-frequency coefficient ratio is between 100% and 120%. Secondly, the relationship between TBV and real visibility is established based on machine learning and piecewise stationary time series analysis. The established piecewise function can be used for visibility estimation. Finally, the visibility estimation approach proposed is validated based on real surveillance video data. The validation results are compared with the results of image contrast model. Besides, the big video data are collected from the Tongqi expressway, Jiangsu, China. A total of 1,782,000 frames were used and the relative errors of the approach proposed are less than 10%.

  • 5.
    Gomez-Espinosa, Alfonso
    et al.
    Tecnol Monterrey, Escuela Ingn & Ciencias, Ave Epigmenio Gonzalez 500, Fracc San Pablo 76130, Queretaro, Mexico..
    Sundin, Roberto Castro
    KTH.
    Loidi Eguren, Ion
    Univ Mondragon, Escuela Politecn Super, Pais Vasco 20500, Spain..
    Cuan-Urquizo, Enrique
    Tecnol Monterrey, Escuela Ingn & Ciencias, Ave Epigmenio Gonzalez 500, Fracc San Pablo 76130, Queretaro, Mexico..
    Trevino-Quintanilla, Cecilia D.
    Tecnol Monterrey, Escuela Ingn & Ciencias, Ave Epigmenio Gonzalez 500, Fracc San Pablo 76130, Queretaro, Mexico..
    Neural Network Direct Control with Online Learning for Shape Memory Alloy Manipulators2019In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 11, article id 2576Article in journal (Refereed)
    Abstract [en]

    New actuators and materials are constantly incorporated into industrial processes, and additional challenges are posed by their complex behavior. Nonlinear hysteresis is commonly found in shape memory alloys, and the inclusion of a suitable hysteresis model in the control system allows the controller to achieve a better performance, although a major drawback is that each system responds in a unique way. In this work, a neural network direct control, with online learning, is developed for position control of shape memory alloy manipulators. Neural network weight coefficients are updated online by using the actuator position data while the controller is applied to the system, without previous training of the neural network weights, nor the inclusion of a hysteresis model. A real-time, low computational cost control system was implemented; experimental evaluation was performed on a 1-DOF manipulator system actuated by a shape memory alloy wire. Test results verified the effectiveness of the proposed control scheme to control the system angular position, compensating for the hysteretic behavior of the shape memory alloy actuator. Using a learning algorithm with a sine wave as reference signal, a maximum static error of 0.83 degrees was achieved when validated against several set-points within the possible range.

  • 6.
    Karlsson, Mikael
    et al.
    RISE Res Inst Sweden AB, Box 1070, SE-16425 Kista, Sweden.;Pamitus AB, Timotejvagen 1, SE-35253 Vaxjo, Sweden..
    Strandqvist, Carl
    Swedish Natl Forens Ctr, SE-58194 Linkoping, Sweden..
    Jussi, Johnny Israelsson
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics. RISE Res Inst Sweden AB, Box 1070, SE-16425 Kista, Sweden..
    Oberg, Olof
    RISE Res Inst Sweden AB, Box 1070, SE-16425 Kista, Sweden..
    Petermann, Ingemar
    RISE Res Inst Sweden AB, Box 1070, SE-16425 Kista, Sweden..
    Elmlund, Louise
    Swedish Natl Forens Ctr, SE-58194 Linkoping, Sweden..
    Dunne, Simon
    Swedish Natl Forens Ctr, SE-58194 Linkoping, Sweden..
    Fu, Ying
    KTH, School of Engineering Sciences (SCI), Applied Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Royal Inst Technol, Sci Life Lab, Dept Appl Phys, SE-17121 Solna, Sweden..
    Wang, Qin
    RISE Res Inst Sweden AB, Box 1070, SE-16425 Kista, Sweden..
    Chemical Sensors Generated on Wafer-Scale Epitaxial Graphene for Application to Front-Line Drug Detection2019In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 10, article id 2214Article in journal (Refereed)
    Abstract [en]

    Generation of large areas of graphene possessing high quality and uniformity will be a critical factor if graphene-based devices/sensors are to be commercialized. In this work, epitaxial graphene on a 2" SiC wafer was used to fabricate sensors for the detection of illicit drugs (amphetamine or cocaine). The main target application is on-site forensic detection where there is a high demand for reliable and cost-efficient tools. The sensors were designed and processed with specially configured metal electrodes on the graphene surface by utilizing a series of anchors where the metal contacts are directly connected on the SiC substrate. This has been shown to improve adhesion of the electrodes and decrease the contact resistance. A microfluidic system was constructed to pump solutions over the defined graphene surface that could then act as a sensor area and react with the target drugs. Several prototypic systems were tested where non-covalent interactions were used to localize the sensing components (antibodies) within the measurement cell. The serendipitous discovery of a wavelength-dependent photoactivity for amphetamine and a range of its chemical analogs, however, limited the general application of these prototypic systems. The experimental results reveal that the drug molecules interact with the graphene in a molecule dependent manner based upon a balance of -stacking interaction of the phenyl ring with graphene (p-doping) and the donation of the amine nitrogens lone pair electrons into the *-system of graphene (n-doping).

  • 7.
    Lu, Ke
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Yang, Liyun
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Seoane, F.
    Abtahi, Farhad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Forsman, Mikael
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. Institute of Environmental Medicine, Karolinska Institutet, Solnavägen 1, 171 77 Solna, Sweden.
    Lindecrantz, K.
    Fusion of heart rate, respiration and motion measurements from a wearable sensor system to enhance energy expenditure estimation2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 9, article id 3092Article in journal (Refereed)
    Abstract [en]

    This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21–65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R2 = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R2 = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R2 = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications. 

  • 8. Ludovici, Alessandro
    et al.
    Di Marco, Piergiuseppe
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Calveras, Anna
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Analytical Model of Large Data Transactions in CoAP Networks2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 8, p. 15610-15638Article in journal (Refereed)
    Abstract [en]

    We propose a novel analytical model to study fragmentation methods in wireless sensor networks adopting the Constrained Application Protocol (CoAP) and the IEEE 802.15.4 standard for medium access control (MAC). The blockwise transfer technique proposed in CoAP and the 6LoWPAN fragmentation are included in the analysis. The two techniques are compared in terms of reliability and delay, depending on the traffic, the number of nodes and the parameters of the IEEE 802.15.4 MAC. The results are validated trough Monte Carlo simulations. To the best of our knowledge this is the first study that evaluates and compares analytically the performance of CoAP blockwise transfer and 6LoWPAN fragmentation. A major contribution is the possibility to understand the behavior of both techniques with different network conditions. Our results show that 6LoWPAN fragmentation is preferable for delay-constrained applications. For highly congested networks, the blockwise transfer slightly outperforms 6LoWPAN fragmentation in terms of reliability.

  • 9.
    Löfhede, Johan
    et al.
    University of Borås.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical sensors, signals and systems (MSSS).
    Thordstein, Magnus
    Göteborg Universitet .
    Textile Electrodes for EEG Recording: A Pilot Study2012In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 12, no 12, p. 16907-16919Article in journal (Refereed)
    Abstract [en]

    The overall aim of our research is to develop a monitoring system for neonatal intensive care units. Long-term EEG monitoring in newborns require that the electrodes don’t harm the sensitive skin of the baby, an especially relevant feature for premature babies. Our approach to EEG monitoring is based on several electrodes distributed over the head of the baby, and since the weight of the head always will be on some of them, any type of hard electrode will inevitably cause a pressure-point that can irritate the skin. Therefore, we propose the use of soft conductive textiles as EEG electrodes, primarily for neonates, but also for other kinds of unobtrusive long-term monitoring. In this paper we have tested two types of textile electrodes on five healthy adults and compared them to standard high quality electrodes. The acquired signals were compared with respect to morphology, frequency distribution, spectral coherence, correlation and power line interference sensitivity, and the signals were found to be similar in most respects. The good measurement performance exhibited by the textile electrodes indicates that they are feasible candidates for EEG recording, opening the door for long-term EEG monitoring applications.

  • 10. Mohino-Herranz, Inma
    et al.
    Gil-Pita, Roberto
    Ferreira, Javier
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Boras, Boras, Sweden.
    Rosa-Zurera, Manuel
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Boras, Boras, Sweden.
    Assessment of Mental, Emotional and Physical Stress through Analysis of Physiological Signals Using Smartphones2015In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 10, p. 25607-25627Article in journal (Refereed)
    Abstract [en]

    Determining the stress level of a subject in real time could be of special interest in certain professional activities to allow the monitoring of soldiers, pilots, emergency personnel and other professionals responsible for human lives. Assessment of current mental fitness for executing a task at hand might avoid unnecessary risks. To obtain this knowledge, two physiological measurements were recorded in this work using customized non-invasive wearable instrumentation that measures electrocardiogram (ECG) and thoracic electrical bioimpedance (TEB) signals. The relevant information from each measurement is extracted via evaluation of a reduced set of selected features. These features are primarily obtained from filtered and processed versions of the raw time measurements with calculations of certain statistical and descriptive parameters. Selection of the reduced set of features was performed using genetic algorithms, thus constraining the computational cost of the real-time implementation. Different classification approaches have been studied, but neural networks were chosen for this investigation because they represent a good tradeoff between the intelligence of the solution and computational complexity. Three different application scenarios were considered. In the first scenario, the proposed system is capable of distinguishing among different types of activity with a 21.2% probability error, for activities coded as neutral, emotional, mental and physical. In the second scenario, the proposed solution distinguishes among the three different emotional states of neutral, sadness and disgust, with a probability error of 4.8%. In the third scenario, the system is able to distinguish between low mental load and mental overload with a probability error of 32.3%. The computational cost was calculated, and the solution was implemented in commercially available Android-based smartphones. The results indicate that execution of such a monitoring solution is negligible compared to the nominal computational load of current smartphones.

  • 11.
    Pastuhoff, Markus
    et al.
    KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
    Tillmark, Nils
    KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
    Alfredsson, P. Henrik
    KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
    Measuring surface pressure on rotating compressor blades using pressure sensitive paint2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 3, article id 344Article in journal (Refereed)
    Abstract [en]

    Pressure sensitive paint (PSP) was used to measure pressure on the blades of a radial compressor with a 51 mm inlet diameter rotating at speeds up to 50 krpm using the so called lifetime method. A diode laser with a scanning-mirror system was used to illuminate the paint and the luminescent lifetime was registered using a photo multiplier. With the described technique the surface-pressure fields were acquired for eight points in the compressor map, useful for general understanding of the flow field and for CFD validation. The PSP was of so called fast type, which makes it possible to observe pressure variations with frequencies up to several kHz. Through frequency spectrum analysis we were able to detect the pulsating flow frequency when the compressor was driven to surge.

  • 12.
    Seoane, Fernando
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ferreira, Javier
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Alvarez, Lorena
    Buendia, Ruben
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ayllon, David
    Llerena, Cosme
    Gil-Pita, Roberto
    Sensorized Garments and Textrode-Enabled Measurement Instrumentation for Ambulatory Assessment of the Autonomic Nervous System Response in the ATREC Project2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 7, p. 8997-9015Article in journal (Refereed)
    Abstract [en]

    Advances in textile materials, technology and miniaturization of electronics for measurement instrumentation has boosted the development of wearable measurement systems. In several projects sensorized garments and non-invasive instrumentation have been integrated to assess on emotional, cognitive responses as well as physical arousal and status of mental stress through the study of the autonomous nervous system. Assessing the mental state of workers under stressful conditions is critical to identify which workers are in the proper state of mind and which are not ready to undertake a mission, which might consequently risk their own life and the lives of others. The project Assessment in Real Time of the Stress in Combatants (ATREC) aims to enable real time assessment of mental stress of the Spanish Armed Forces during military activities using a wearable measurement system containing sensorized garments and textile-enabled non-invasive instrumentation. This work describes the multiparametric sensorized garments and measurement instrumentation implemented in the first phase of the project required to evaluate physiological indicators and recording candidates that can be useful for detection of mental stress. For such purpose different sensorized garments have been constructed: a textrode chest-strap system with six repositionable textrodes, a sensorized glove and an upper-arm strap. The implemented textile-enabled instrumentation contains one skin galvanometer, two temperature sensors for skin and environmental temperature and an impedance pneumographer containing a 1-channel ECG amplifier to record cardiogenic biopotentials. With such combinations of garments and non-invasive measurement devices, a multiparametric wearable measurement system has been implemented able to record the following physiological parameters: heart and respiration rate, skin galvanic response, environmental and peripheral temperature. To ensure the proper functioning of the implemented garments and devices the full series of 12 sets have been functionally tested recording cardiogenic biopotential, thoracic impedance, galvanic skin response and temperature values. The experimental results indicate that the implemented wearable measurement systems operate according to the specifications and are ready to be used for mental stress experiments, which will be executed in the coming phases of the project with dozens of healthy volunteers.

  • 13.
    Seoane, Fernando
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Mohino-Herranz, Inmaculada
    Ferreira, Javier
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Alvarez, Lorena
    Buendia, Ruben
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ayllon, David
    Llerena, Cosme
    Gil-Pita, Roberto
    Wearable Biomedical Measurement Systems for Assessment of Mental Stress of Combatants in Real Time2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 4, p. 7120-7141Article in journal (Refereed)
    Abstract [en]

    The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants' operational capabilities. Within this framework the ATREC project funded by the Coincidente program aims at analyzing diverse biometrics to assess by real time monitoring the stress levels of combatants. This project combines multidisciplinary disciplines and fields, including wearable instrumentation, textile technology, signal processing, pattern recognition and psychological analysis of the obtained information. In this work the ATREC project is described, including the different execution phases, the wearable biomedical measurement systems, the experimental setup, the biomedical signal analysis and speech processing performed. The preliminary results obtained from the data analysis collected during the first phase of the project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax. These results suggest that cardiac and respiration activity offer better biomarkers for assessment of stress than speech, galvanic skin response or skin temperature when recorded with wearable biomedical measurement systems.

  • 14. Si, Zhongwei
    et al.
    Ma, Junyang
    Thobaben, Ragnar
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Coded Cooperation for Multiway Relaying in Wireless Sensor Networks2015In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 7, p. 15265-15284Article in journal (Refereed)
    Abstract [en]

    Wireless sensor networks have been considered as an enabling technology for constructing smart cities. One important feature of wireless sensor networks is that the sensor nodes collaborate in some manner for communications. In this manuscript, we focus on the model of multiway relaying with full data exchange where each user wants to transmit and receive data to and from all other users in the network. We derive the capacity region for this specific model and propose a coding strategy through coset encoding. To obtain good performance with practical codes, we choose spatially-coupled LDPC (SC-LDPC) codes for the coded cooperation. In particular, for the message broadcasting from the relay, we construct multi-edge-type (MET) SC-LDPC codes by repeatedly applying coset encoding. Due to the capacity-achieving property of the SC-LDPC codes, we prove that the capacity region can theoretically be achieved by the proposed MET SC-LDPC codes. Numerical results with finite node degrees are provided, which show that the achievable rates approach the boundary of the capacity region in both binary erasure channels and additive white Gaussian channels.

  • 15. Smith, A. D.
    et al.
    Li, Qi
    Vyas, Agin
    Haque, Mohammad Mazharul
    Wang, Kejian
    Velasco, Andres
    Zhang, Xiaoyan
    Thurakkal, Shameel
    Quellmalz, Arne
    Niklaus, Frank
    Gylfason, Kristinn
    Lundgren, Per
    Enoksson, Peter
    Carbon-Based Electrode Materials for Microsupercapacitors in Self-Powering Sensor Networks: Present and Future Development2019In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 19, article id 4231Article in journal (Refereed)
    Abstract [en]

    There is an urgent need to fulfill future energy demands for micro and nanoelectronics. This work outlines a number of important design features for carbon-based microsupercapacitors, which enhance both their performance and integration potential and are critical for complimentary metal oxide semiconductor (CMOS) compatibility. Based on these design features, we present CMOS-compatible, graphene-based microsupercapacitors that can be integrated at the back end of the line of the integrated circuit fabrication. Electrode materials and their interfaces play a crucial role for the device characteristics. As such, different carbon-based materials are discussed and the importance of careful design of current collector/electrode interfaces is emphasized. Electrode adhesion is an important factor to improve device performance and uniformity. Additionally, doping of the electrodes can greatly improve the energy density of the devices. As microsupercapacitors are engineered for targeted applications, device scaling is critically important, and we present the first steps toward general scaling trends. Last, we outline a potential future integration scheme for a complete microsystem on a chip, containing sensors, logic, power generation, power management, and power storage. Such a system would be self-powering.

  • 16. Stöggl, Thomas
    et al.
    Holst, Anders
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Swedish Institute of Computer Science, Sweden .
    Jonasson, Arndt
    Andersson, Erik
    Wunsch, Tobias
    Norström, Christer
    Holmberg, Hans-Christer
    Automatic Classification of the Sub-Techniques (Gears) Used in Cross-Country Ski Skating Employing a Mobile Phone2014In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 11, p. 20589-20601Article in journal (Refereed)
    Abstract [en]

    The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 +/- 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% +/- 8.9% of the time, a value that rose to 90.3% +/- 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear.

  • 17.
    Vega-Barbas, Mario
    et al.
    Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    Diaz-Olivares, Jose A.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Lu, Ke
    Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden..
    Forsman, Mikael
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    Seoane, Fernando
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Halsovagen 7, S-14157 Huddinge, Sweden.;Univ Boras, Swedish Sch Text, Allegatan 1, S-50190 Boras, Sweden.;Karolinska Univ Hosp, Dept & T Biomed Engn, S-17176 Solna, Sweden..
    Abtahi, Farhad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing2019In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 5, article id 1225Article in journal (Refereed)
    Abstract [en]

    Preventive healthcare has attracted much attention recently. Improving people's lifestyles and promoting a healthy diet and wellbeing are important, but the importance of work-related diseases should not be undermined. Musculoskeletal disorders (MSDs) are among the most common work-related health problems. Ergonomists already assess MSD risk factors and suggest changes in workplaces. However, existing methods are mainly based on visual observations, which have a relatively low reliability and cover only part of the workday. These suggestions concern the overall workplace and the organization of work, but rarely includes individuals' work techniques. In this work, we propose a precise and pervasive ergonomic platform for continuous risk assessment. The system collects data from wearable sensors, which are synchronized and processed by a mobile computing layer, from which exposure statistics and risk assessments may be drawn, and finally, are stored at the server layer for further analyses at both individual and group levels. The platform also enables continuous feedback to the worker to support behavioral changes. The deployed cloud platform in Amazon Web Services instances showed sufficient system flexibility to affordably fulfill requirements of small to medium enterprises, while it is expandable for larger corporations. The system usability scale of 76.6 indicates an acceptable grade of usability.

  • 18.
    Vega-Barbas, Mario
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Pau, Ivan
    Universidad Politecnica de Madrid.
    Martín-Ruiz, Maria Luisa
    Universidad Politecnica de Madrid.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Adaptive Software Architecture Based on Confident HCI for the Deployment of Sensitive Services in Smart Homes2015In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 4, p. 7294-7322Article in journal (Refereed)
    Abstract [en]

    Smart spaces foster the development of natural and appropriate forms of human-computer interaction by taking advantage of home customization. The interaction potential of the Smart Home, which is a special type of smart space, is of particular interest in fields in which the acceptance of new technologies is limited and restrictive. The integration of smart home design patterns with sensitive solutions can increase user acceptance. In this paper, we present the main challenges that have been identified in the literature for the successful deployment of sensitive services (e.g., telemedicine and assistive services) in smart spaces and a software architecture that models the functionalities of a Smart Home platform that are required to maintain and support such sensitive services. This architecture emphasizes user interaction as a key concept to facilitate the acceptance of sensitive services by end-users and utilizes activity theory to support its innovative design. The application of activity theory to the architecture eases the handling of novel concepts, such as understanding of the system by patients at home or the affordability of assistive services. Finally, we provide a proof-of-concept implementation of the architecture and compare the results with other architectures from the literature.

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