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Статті в журналах з теми "Biosignal monitoring"
Klinger, Volkhard. "An IoT-Based Platform for Rehabilitation Monitoring and Biosignal Identification." International Journal of Privacy and Health Information Management 6, no. 1 (January 2018): 1–19. http://dx.doi.org/10.4018/ijphim.2018010101.
Повний текст джерелаStuart, Tucker, Jessica Hanna, and Philipp Gutruf. "Wearable devices for continuous monitoring of biosignals: Challenges and opportunities." APL Bioengineering 6, no. 2 (June 1, 2022): 021502. http://dx.doi.org/10.1063/5.0086935.
Повний текст джерелаCogan, Diana, Javad Birjandtalab, Mehrdad Nourani, Jay Harvey, and Venkatesh Nagaraddi. "Multi-Biosignal Analysis for Epileptic Seizure Monitoring." International Journal of Neural Systems 27, no. 01 (November 8, 2016): 1650031. http://dx.doi.org/10.1142/s0129065716500313.
Повний текст джерелаAthavale, Yashodhan, and Sridhar Krishnan. "Biosignal monitoring using wearables: Observations and opportunities." Biomedical Signal Processing and Control 38 (September 2017): 22–33. http://dx.doi.org/10.1016/j.bspc.2017.03.011.
Повний текст джерелаBlachowicz, Tomasz, Guido Ehrmann, and Andrea Ehrmann. "Textile-Based Sensors for Biosignal Detection and Monitoring." Sensors 21, no. 18 (September 9, 2021): 6042. http://dx.doi.org/10.3390/s21186042.
Повний текст джерелаKlinger, Volkhard. "SMoBAICS." International Journal of Privacy and Health Information Management 5, no. 2 (July 2017): 34–57. http://dx.doi.org/10.4018/ijphim.2017070103.
Повний текст джерелаShanmathi, N., and M. Jagannath. "Multimodal Biosignal Acquisition System for Remote Health Monitoring." Research Journal of Pharmacy and Technology 11, no. 12 (2018): 5265. http://dx.doi.org/10.5958/0974-360x.2018.00959.9.
Повний текст джерелаMercado-Aguirre, Isabela M., Edgardo L. Mercado-Medina, Zulay D. Chavarro-Hernandez, Juan A. Dominguez-Jimenez, and Sonia H. Contreras-Ortiz. "A wearable system for biosignal monitoring in weightlifting." Sports Engineering 20, no. 1 (July 11, 2016): 73–80. http://dx.doi.org/10.1007/s12283-016-0212-z.
Повний текст джерелаWu, Xianzhang, Zhangpeng Li, Honggang Wang, Jingxia Huang, Jinqing Wang, and Shengrong Yang. "Stretchable and self-healable electrical sensors with fingertip-like perception capability for surface texture discerning and biosignal monitoring." Journal of Materials Chemistry C 7, no. 29 (2019): 9008–17. http://dx.doi.org/10.1039/c9tc02575h.
Повний текст джерелаMurakami, D., and M. Makikawa. "Ambulatory Behavior Map, Physical Activity and Biosignal Monitoring System." Methods of Information in Medicine 36, no. 04/05 (October 1997): 360–63. http://dx.doi.org/10.1055/s-0038-1636848.
Повний текст джерелаДисертації з теми "Biosignal monitoring"
Snäll, Jonatan. "Software development of Biosignal Pi : An affordable open source platform for monitoring ECG and respiration." Thesis, KTH, Skolan för teknik och hälsa (STH), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154211.
Повний текст джерелаFör att hantera den ökande kostnaden för hälso- och sjukvård kommer en större del av övervakning samt vård att ske i patientens hem. Det kommer därför att vara önskvärt att utveckla mindre system som är lättare att hantera än de större traditionella apparaterna för att samla in vanliga biosignaler som exempelvis ett EKG. Detta projekt är en fortsättning på ett tidigare projekt vars syfte var att framställa en ”sköld” som kan kopplas ihop med en Raspberry Pi via dess GPIO pinnar. Det föregående projektet var lyckat och en sköld innehållande en ADAS1000 som kan samla in bl.a. ett EKG samt andningen framställdes. Syftet med detta projekt var att utveckla en applikation som kan köras på en Raspberry Pi och på så sätt visa den data som samlas in från skölden på en skärm. Det skulle även vara möjligt att spara insamlad data för senare användning. Projektet resulterade i en applikation som uppfyllde dessa krav.
Gomes, Ricardo Rafael Baptista. "Long-term biosignals visualization and processing." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/7979.
Повний текст джерелаLong-term biosignals acquisitions are an important source of information about the patients’state and its evolution. However, long-term biosignals monitoring involves managing extremely large datasets, which makes signal visualization and processing a complex task. To overcome these problems, a new data structure to manage long-term biosignals was developed. Based on this new data structure, dedicated tools for long-term biosignals visualization and processing were implemented. A multilevel visualization tool for any type of biosignals, based on subsampling is presented, focused on four representative signal parameters (mean, maximum, minimum and standard deviation error). The visualization tool enables an overview of the entire signal and a more detailed visualization in specific parts which we want to highlight, allowing an user friendly interaction that leads to an easier signal exploring. The ”map” and ”reduce” concept is also exposed for long-term biosignal processing. A processing tool (ECG peak detection) was adapted for long-term biosignals. In order to test the developed algorithm, long-term biosignals acquisitions (approximately 8 hours each) were carried out. The visualization tool has proven to be faster than the standard methods, allowing a fast navigation over the different visualization levels of biosignals. Regarding the developed processing algorithm, it detected the peaks of long-term ECG signals with fewer time consuming than the nonparalell processing algorithm. The non-specific characteristics of the new data structure, visualization tool and the speed improvement in signal processing introduced by these algorithms makes them powerful tools for long-term biosignals visualization and processing.
Eguchi, Kana. "Easy-to-Use Biosignal Monitoring: Wearable Device for Muscle Activity Measurement during Sleep in Daily Life." Doctoral thesis, Kyoto University, 2020. http://hdl.handle.net/2433/253414.
Повний текст джерела0048
新制・課程博士
博士(情報学)
甲第22578号
情博第715号
新制||情||123(附属図書館)
京都大学大学院情報学研究科社会情報学専攻
(主査)教授 黒田 知宏, 教授 守屋 和幸, 教授 吉川 正俊
学位規則第4条第1項該当
Doctor of Informatics
Kyoto University
DFAM
Radüntz, Thea. "Biophysiological Mental-State Monitoring during Human-Computer Interaction." Doctoral thesis, Humboldt-Universität zu Berlin, 2021. http://dx.doi.org/10.18452/23026.
Повний текст джерелаThe long-term negative consequences of inappropriate mental workload on employee health constitute a serious problem for a digitalized society. Continuous, objective assessment of mental workload can provide an essential contribution to the identification of such improper load. Recent improvements in sensor technology and algorithmic methods for biosignal processing are the basis for the quantitative determination of mental workload. Neuronal workload measurement has the advantage that workload registration is located directly there where human information processing takes place, namely the brain. Preliminary studies for the development of a method for neuronal workload registration by use of the electroencephalogram (EEG) have already been carried out [Rad16, Rad17]. For the field use of these findings, the mental workload assess- ment on the basis of the EEG must be evaluated and its reliability examined with respect to several conditions in realistic environments. A further essential require-ment is that the method can be combined with the innovative technologies of gel free EEG registration and wireless signal transmission. Hence, the presented papers include two investigations. Main subject of the first investigation are experimental studies on the usability of commercially-oriented EEG systems for mobile field use and system selection for the future work. Main subject of the second investigation is the evaluation of the continuous method for neuronal mental workload registration in the field. Thereby, a challenging application was used, namely the arrival management of aircraft. The simulation of the air traffic control environment allows the realisation of realistic conditions with different levels of task load. Furthermore, the work is well contextualized in a domain which is very sensible to human-factors research.
Parmakis, Gerry. "Artificial pattern recognition with indeterminate input : a methodological review, and an original design for an adaptive system having prospective application in the real-time monitoring of biosignals such as ECG." Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310728.
Повний текст джерелаSarmento, Ana Sofia Nascimento. "Improving skin conductivity to small ions for enhanced biosignal monitoring." Master's thesis, 2018. https://hdl.handle.net/10216/114359.
Повний текст джерелаSarmento, Ana Sofia Nascimento. "Improving skin conductivity to small ions for enhanced biosignal monitoring." Dissertação, 2018. https://hdl.handle.net/10216/114359.
Повний текст джерелаSarmento, Ana Sofia Nascimento. "Improving skin conductivity to small ions for enhanced biosignal monitoring." Dissertação, 2002. https://repositorio-aberto.up.pt/handle/10216/114359.
Повний текст джерелаSaleh, Abdulelah. "Inkjet Printing of a Two-Dimensional Conductor for Cutaneous Biosignal Monitoring." Thesis, 2019. http://hdl.handle.net/10754/652930.
Повний текст джерелаMoura, André Magalhães. "Construction of a biosignal measurement device and its dashboard for swimming training." Master's thesis, 2021. http://hdl.handle.net/10400.6/12025.
Повний текст джерелаO âmbito deste trabalho incide no desenvolvimento/criação de um dispositivo de medição de biosinais (acelerometria, eletromiografia e eletrocardiografia) para que através de uma conexão via Bluetooth seja feita a captura destes valores num nadador. Abrange ainda o desenvolvimento de um dashboard que permite ao treinador acompanhar e melhorar os treinos de um atleta.
Книги з теми "Biosignal monitoring"
Amine, Naït-Ali, ed. Advanced biosignal processing. Berlin: Springer, 2009.
Знайти повний текст джерелаUrban, Gerald A., Roland Fried, Sven Bode, Gerald Czygan, and Martin Daumer. Biosignale und Monitoring. De Gruyter, Inc., 2021.
Знайти повний текст джерелаGuttmann, Joseph, Roland Fried, Sven Bode, Gerald Czygan, and Martin Daumer. Biosignale und Monitoring. de Gruyter GmbH, Walter, 2030.
Знайти повний текст джерелаUrban, Gerald A., Thomas Penzel, and Jens Haueisen. Biosignale und Monitoring. de Gruyter GmbH, Walter, 2030.
Знайти повний текст джерелаЧастини книг з теми "Biosignal monitoring"
Sengupta, Joydeep, Nupur Baviskar, and Surbhi Shukla. "Biosignal Acquisition System for Stress Monitoring." In Mobile Communication and Power Engineering, 451–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35864-7_69.
Повний текст джерелаRitika Saxena, Sushabhan Choudhary, Rajesh Singh, and Anshuman Prakash. "Biosignal Acquisition of Stress Monitoring Through Wearable Device." In Proceeding of International Conference on Intelligent Communication, Control and Devices, 803–9. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1708-7_93.
Повний текст джерелаStan, A., R. Lupu, M. Ciorap, and R. Ciorap. "Biosignal Monitoring and Processing for Management of Hypertension." In XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010, 537–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13039-7_135.
Повний текст джерелаLovell, Nigel H., and Stephen J. Redmond. "Biosignal Processing to Meet the Emerging Needs of Telehealth Monitoring Environments." In Lecture Notes in Electrical Engineering, 263–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05167-8_15.
Повний текст джерелаSilva, Hugo, Susana Palma, and Hugo Gamboa. "AAL+: Continuous Institutional and Home Care Through Wireless Biosignal Monitoring Systems." In Handbook of Digital Homecare, 115–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/8754_2011_25.
Повний текст джерелаPannerselvam, Ithayarani. "A Multimodal Biosignal Compression Technique for Monitoring Health in Wearable Devices." In Artificial Intelligence and Cybersecurity, 155–74. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003097518-10.
Повний текст джерелаValenza, Gaetano, and Enzo Pasquale Scilingo. "Exploiting Physiological Sensors and Biosignal Processing to Enhance Monitoring Care in Mental Health." In Handbook of Large-Scale Distributed Computing in Smart Healthcare, 515–50. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58280-1_19.
Повний текст джерелаLópez-de-Ipiña, K., J. Solé-Casals, U. Martinez de Lizarduy, P. M. Calvo, J. Iradi, M. Faundez-Zanuy, and A. Bergareche. "Non-invasive Biosignal Analysis Oriented to Early Diagnosis and Monitoring of Cognitive Impairments." In Converging Clinical and Engineering Research on Neurorehabilitation II, 867–72. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46669-9_141.
Повний текст джерелаGolz, Martin, and David Sommer. "Automatic Knowledge Extraction: Fusion of Human Expert Ratings and Biosignal Features for Fatigue Monitoring Applications." In Signal Processing Techniques for Knowledge Extraction and Information Fusion, 299–316. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74367-7_16.
Повний текст джерелаKim, Young-Hyuk, Il-Kown Lim, Jae-Pil Lee, Jae-Gwang Lee, and Jae-Kwang Lee. "Study on Low-Power Transmission Protocols for ZigBee Wireless Network-Based Remote Biosignal Monitoring Systems." In Lecture Notes in Electrical Engineering, 709–16. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5857-5_76.
Повний текст джерелаТези доповідей конференцій з теми "Biosignal monitoring"
Perego, Paolo, Giuseppe Andreoni, Rinaldo Zanini, and Roberto Bellù. "Wearable Biosignal Monitoring System for Newborns." In 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies". ICST, 2014. http://dx.doi.org/10.4108/icst.mobihealth.2014.257403.
Повний текст джерелаSakaue, Yusuke, and Masaaki Makikawa. "Development of Wireless Biosignal Monitoring Device." In 6th International Special Topic Conference on Information Technology Applications in Biomedicine, 2007. IEEE, 2007. http://dx.doi.org/10.1109/itab.2007.4407409.
Повний текст джерелаDappuri, Bhasker, M. Tamilselvi, E. Baburaj, and S. Omkumar. "Biosignal electrode based patient health monitoring system." In INDUSTRIAL, MECHANICAL AND ELECTRICAL ENGINEERING. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0109775.
Повний текст джерелаOwyeung, Rachel, Wenxin Zeng, and Sameer Sonkusale. "Eutectogel Electrodes for Long-Term Biosignal Monitoring." In 2022 IEEE Sensors. IEEE, 2022. http://dx.doi.org/10.1109/sensors52175.2022.9967321.
Повний текст джерелаJung, Hachul, Dahye Kwon, Seunga Lee, Jinwoo Ahn, A.-Hee Kim, Young-Jin Kim, and Jinhee Moon. "Carbon Based Electrode for Wearable Biosignal Monitoring Patch." In 2018 International Flexible Electronics Technology Conference (IFETC). IEEE, 2018. http://dx.doi.org/10.1109/ifetc.2018.8583893.
Повний текст джерелаGupta, Yashi, Suman Kumar, and Vijay Mago. "Pregnancy Health Monitoring System based on Biosignal Analysis." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8769074.
Повний текст джерелаSingh, Rajiv Ranjan, Sailesh Conjeti, and Rahul Banerjee. "Biosignal based on-road stress monitoring for automotive drivers." In 2012 National Conference on Communications (NCC). IEEE, 2012. http://dx.doi.org/10.1109/ncc.2012.6176845.
Повний текст джерелаLozano, Jorge, and Boris Stoeber. "Microspike Array Electrode with Flexible Backing for Biosignal Monitoring." In 2019 IEEE SENSORS. IEEE, 2019. http://dx.doi.org/10.1109/sensors43011.2019.8956869.
Повний текст джерелаChen, Pei-Jarn, Jui-Yu Weng, and Yi-Kai Chiou. "Implement an IOT Platform of Biosignal Monitoring for Nurse Station." In 2020 IEEE 2nd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS). IEEE, 2020. http://dx.doi.org/10.1109/ecbios50299.2020.9203686.
Повний текст джерелаSaisho, Osamu, Keiichiro Kashiwagi, Yui Saito, and Tomoyuki Fujino. "Adaptive biosignal data gathering for distributed and continual remote monitoring." In UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3410530.3414413.
Повний текст джерела