Wearable Smart System for Physical Activity Support

Wearable smart systems that measure and process a human vital sings have become important tool in eHealth, rehabilitation and recreation. This research was about to develop a system that aims to support recreational physical activity by delivering communication and computational services. The system architecture facilitates implementation of advanced data processing methods in the form of computational services and easily include additional services according to the user needs. An eHealth application was developed to demonstrate the system capabilities. The application makes use of expert’s knowledge together with measurement data in order to generate the optimal training plan. The system performs such tasks as: modelling of the sportsmen’s cardiovascular system, estimation of the sportsmen’s parameters, adaptation of the model to the sportsmen.

[1]  Piotr Rygielski,et al.  TRANSLATIONS OF SERVICE LEVEL AGREEMENT IN SYSTEMS BASED ON SERVICE-ORIENTED ARCHITECTURES , 2010, Cybern. Syst..

[2]  Niall Twomey,et al.  Comparison of accelerometer-based energy expenditure estimation algorithms , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.

[3]  Robert X. Gao,et al.  Multisensor Data Fusion for Physical Activity Assessment , 2012, IEEE Transactions on Biomedical Engineering.

[4]  Luca Chittaro,et al.  MOPET: A context-aware and user-adaptive wearable system for fitness training , 2008, Artif. Intell. Medicine.

[5]  Piotr Rygielski,et al.  Translations of Service Level Agreement in Systems Based on Service Oriented Architecture , 2010, KES.

[6]  Svetha Venkatesh,et al.  Hierarchical recognition of intentional human gestures for sports video annotation , 2002, Object recognition supported by user interaction for service robots.

[7]  Piotr Rygielski,et al.  Context Change Detection for Resource Allocation in Service-Oriented Systems , 2011, KES.

[8]  Michael Michailov Evolvement and Experimentation of a New Interval Method For Strength Endurance Development , 2006 .

[9]  Andrey V. Savkin,et al.  Nonlinear Modeling and Control of Human Heart Rate Response During Exercise With Various Work Load Intensities , 2008, IEEE Transactions on Biomedical Engineering.

[10]  Kenji Mase,et al.  Activity and Location Recognition Using Wearable Sensors , 2002, IEEE Pervasive Comput..

[11]  Grzegorz Kolaczek,et al.  Smart Work Workbench; Integrated Tool for IT Services Planning, Management, Execution and Evaluation , 2011, ICCCI.

[12]  Piotr Rygielski,et al.  Dynamic Resources Allocation for Delivery of Personalized Services , 2010, I3E.

[13]  Wojciech Cellary,et al.  Software Services for e-World - 10th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2010, Buenos Aires, Argentina, November 3-5, 2010. Proceedings , 2010, I3E.

[14]  Krzysztof Juszczyszyn,et al.  Service Composition in Knowledge-based SOA Systems , 2012, New Generation Computing.

[15]  Shyamal Patel,et al.  Mercury: a wearable sensor network platform for high-fidelity motion analysis , 2009, SenSys '09.

[16]  Tapio Seppänen,et al.  Recognizing human motion with multiple acceleration sensors , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[17]  Piotr Rygielski,et al.  USER ASSIGNMENT AND MOVEMENT PREDICTION IN WIRELESS NETWORKS , 2012, Cybern. Syst..

[18]  Piotr Rygielski,et al.  Migration-aware Optimization of Virtualized Computational Resources Allocation in Complex Systems , 2011, 2011 21st International Conference on Systems Engineering.

[19]  Friedrich Foerster,et al.  Detection of posture and motion by accelerometry : a validation study in ambulatory monitoring , 1999 .

[20]  Pawel Swiatek,et al.  ADAPTIVE DECISION SUPPORT SYSTEM FOR AUTOMATIC PHYSICAL EFFORT PLAN GENERATION—DATA-DRIVEN APPROACH , 2013, Cybern. Syst..

[21]  Cristiano Maria Verrelli,et al.  Nonlinear Control Techniques for the Heart Rate Regulation in Treadmill Exercises , 2012, IEEE Transactions on Biomedical Engineering.

[22]  Krzysztof Brzostowski,et al.  System Analysis Techniques in eHealth Systems: A Case Study , 2012, ACIIDS.

[23]  Krzysztof Juszczyszyn,et al.  Supporting Content, Context and User Awareness in Future Internet Applications , 2012, Future Internet Assembly.

[24]  Luis M. Camarinha-Matos,et al.  Technological Innovation for Sustainability - Second IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2011, Costa de Caparica, Portugal, February 21-23, 2011. Proceedings , 2011, DoCEIS.

[25]  A K Bourke,et al.  Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. , 2007, Gait & posture.

[26]  Sharon Ann Plowman,et al.  Exercise Physiology for Health, Fitness, and Performance , 1996 .

[27]  K. Aminian,et al.  Physical activity monitoring based on accelerometry: validation and comparison with video observation , 1999, Medical & Biological Engineering & Computing.

[28]  Andrey V. Savkin,et al.  Heart Rate Regulation During Exercise with Various Loads: Identification and Nonlinear H∞ Control , 2008 .

[29]  Ki H. Chon,et al.  Physiological Parameter Monitoring from Optical Recordings With a Mobile Phone , 2012, IEEE Transactions on Biomedical Engineering.

[30]  Krzysztof Juszczyszyn,et al.  A Model for Automated Service Composition System in SOA Environment , 2011, DoCEIS.

[31]  C. Cobelli,et al.  Physical Activity into the Meal Glucose—Insulin Model of Type 1 Diabetes: In Silico Studies , 2009, Journal of diabetes science and technology.

[32]  L Nyberg,et al.  Comparison of real-life accidental falls in older people with experimental falls in middle-aged test subjects. , 2012, Gait & posture.

[33]  Maarit Kangas,et al.  Comparison of low-complexity fall detection algorithms for body attached accelerometers. , 2008, Gait & posture.

[34]  Adam Janiak,et al.  New perspectives in VLSI design automation: deterministic packing by Sequence Pair , 2010, Ann. Oper. Res..

[35]  Pawel Swiatek,et al.  Complex Services Availability in Service Oriented Systems , 2011, 2011 21st International Conference on Systems Engineering.

[36]  Maciej Zieba,et al.  The Proposal of Service Oriented Data Mining System for Solving Real-Life Classification and Regression Problems , 2011, DoCEIS.

[37]  Grzegorz Kolaczek,et al.  Multiagent Security Evaluation Framework for Service Oriented Architecture Systems , 2009, KES.

[38]  Jordi Mongay Batalla,et al.  Provision of end-to-end QoS in heterogeneous multi-domain networks , 2008, Ann. des Télécommunications.

[39]  Marek Natkaniec,et al.  An Analysis of Star Topology IEEE 802.11e Networks in the Presence of Hidden Nodes , 2008, 2008 International Conference on Information Networking.

[40]  Pawel Swiatek,et al.  MODELING AND OPTIMIZATION OF COMPLEX SERVICES IN SERVICE-BASED SYSTEMS , 2009, Cybern. Syst..

[41]  Adrian Burns,et al.  An adaptive gyroscope-based algorithm for temporal gait analysis , 2010, Medical & Biological Engineering & Computing.

[42]  David R. Kincaid,et al.  Numerical mathematics and computing , 1980 .

[43]  Piotr Rygielski,et al.  Graph-fold: an efficient method for complex service execution plan optimization , 2010 .

[44]  Jakub M. Tomczak On-Line Change Detection for Resource Allocation in Service-Oriented Systems , 2012, DoCEIS.