SPW-1: A Low-Maintenance Wearable Activity Tracker for Residential Monitoring and Healthcare Applications

In this paper, we present SPW-1; a low-profile versatile wearable activity tracker that employs two ultra-low-power accelerometers and relies on Bluetooth Low Energy (BLE) for wireless communication. Aiming for a low maintenance system, SPW-1 is able to offer a battery lifetime of multiple months. Measurements on its wireless performance in a real residential environment with thick brick walls, demonstrate that SPW-1 can fully cover a room and - in most cases - the adjacent room, as well. SPW-1 is a research platform that is aimed to be used both as a data collecting tool for health-oriented studies outside the laboratory, but also for research on wearable technologies and body-centric communications. As a result, SPW-1 incorporates versatile features, such as external sensor support, various powering options, and accelerometer configuration options that can support a wide range applications from kinematics to long-term activity recognition.

[1]  Ping Jiang,et al.  Verity: an ambient assisted living platform , 2012, IEEE Transactions on Consumer Electronics.

[2]  Robert J. Piechocki,et al.  Fix it, don't bin it! - CRC error correction in Bluetooth Low Energy , 2015, 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT).

[3]  Jean-Yves Fourniols,et al.  Smart wearable systems: Current status and future challenges , 2012, Artif. Intell. Medicine.

[4]  G. Mcnicoll.  World Population Ageing 1950-2050. , 2002 .

[5]  Yuting Zhang,et al.  Continuous functional activity monitoring based on wearable tri-axial accelerometer and gyroscope , 2011, 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.

[6]  Matti Siekkinen,et al.  How low energy is bluetooth low energy? Comparative measurements with ZigBee/802.15.4 , 2012, 2012 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[7]  Refet Firat Yazicioglu,et al.  A Low-power and Compact-sized Wearable Bio-impedance Monitor with Wireless Connectivity , 2013 .

[8]  Daniel P. Siewiorek,et al.  Activity recognition and monitoring using multiple sensors on different body positions , 2006, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06).

[9]  Robert J. Piechocki,et al.  A residential maintenance-free long-term activity monitoring system for healthcare applications , 2016, EURASIP Journal on Wireless Communications and Networking.

[10]  Xiang Chen,et al.  A Framework for Daily Activity Monitoring and Fall Detection Based on Surface Electromyography and Accelerometer Signals , 2013, IEEE Journal of Biomedical and Health Informatics.

[11]  Piotr Ponikowski,et al.  Silver paper: The future of health promotion and preventive actions, basic research, and clinical aspects of age-related disease , 2009, Endokrynologia Polska.

[12]  Pai H. Chou,et al.  EcoIMU: A Dual Triaxial-Accelerometer Inertial Measurement Unit for Wearable Applications , 2010, 2010 International Conference on Body Sensor Networks.

[13]  Vedran Bilas,et al.  Low-Power Wearable Respiratory Sound Sensing , 2014, Sensors.

[14]  Helen Pearson,et al.  Children of the 90s: Coming of age , 2012, Nature.

[15]  Ingrid Moerman,et al.  A Comprehensive Survey of Wireless Body Area Networks , 2012, Journal of Medical Systems.

[16]  Luc Vandendorpe,et al.  Adaptive coding and modulation using imperfect CSI in cognitive BIC-OFDM systems , 2016, EURASIP J. Wirel. Commun. Netw..

[17]  Yao-Chiang Kan,et al.  A Wearable Inertial Sensor Node for Body Motion Analysis , 2012, IEEE Sensors Journal.

[18]  Lars Kai Hansen,et al.  How efficient is estimation with missing data? , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[19]  Xenofon Fafoutis,et al.  Investigation into off-body links for wrist mounted antennas in bluetooth systems , 2015, 2015 Loughborough Antennas & Propagation Conference (LAPC).

[20]  Majid Mirmehdi,et al.  A multi-modal sensor infrastructure for healthcare in a residential environment , 2015, 2015 IEEE International Conference on Communication Workshop (ICCW).

[21]  Tim Dallas,et al.  Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer , 2014, IEEE Transactions on Biomedical Engineering.

[22]  Xenofon Fafoutis,et al.  Sustainable medium access control: Implementation and evaluation of ODMAC , 2013, 2013 IEEE International Conference on Communications Workshops (ICC).

[23]  Thea J. M. Kooiman,et al.  Reliability and validity of ten consumer activity trackers , 2015, BMC Sports Science, Medicine and Rehabilitation.

[24]  A. Mcgregor,et al.  Body-Worn Sensor Design: What Do Patients and Clinicians Want? , 2011, Annals of Biomedical Engineering.

[25]  Martina Ziefle,et al.  Acceptance of pervasive healthcare systems: A comparison of different implementation concepts , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.