2. Gao W, Emaminejad S, Nyein HY, Challa S, Chen K, Peck A, et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature. 2016; 529(7587):509–514.
Article
6. Xu S, Zhang Y, Jia L, Mathewson KE, Jang KI, Kim J, et al. Soft microfluidic assemblies of sensors, circuits, and radios for the skin. Science. 2014; 344(6179):70–74.
Article
7. Martin T, Jovanov E, Raskovic D. Issues in wearable computing for medical monitoring applications: a case study of a wearable ECG monitoring device. In : Proceedings of the 4th International Symposium on Wearable Computers; 2000 Oct 16-17; Atlanta, GA. p. 43–49.
8. Jovanov E, Gelabert P, Wheelock B, Adhami R, Smith P. Real time portable heart monitoring using low power DSP. In : Proceedings of International Conference on Signal Processing Applications and Technology (ICSPAT); 2000 Oct 16-19; Dallas, TX. p. 16–19.
12. Anliker U, Ward JA, Lukowicz P, Troster G, Dolveck F, Baer M, et al. AMON: a wearable multiparameter medical monitoring and alert system. IEEE Trans Inf Technol Biomed. 2004; 8(4):415–427.
Article
14. To G, Mahfouz MR. Modular wireless inertial trackers for biomedical applications. In : Proceedings of 2013 IEEE Topical Conference on Power Amplifiers for Wireless and Radio Applications (PAWR); 2013 Jan 20-23; Austin, TX. p. 172–174.
15. Veltink PH, Boom HB. 3D movement analysis using accelerometry theoretical concepts. In : Pedotti A, Ferrarin M, Quintern J, Reiner R, editors. Neuroprosthetics: from basic research to clinical applications. Berlin: Springer;1996. p. 317–326.
16. Foerster F, Smeja M, Fahrenberg J. Detection of posture and motion by accelerometry: a validation study in ambulatory monitoring. Comput Human Behav. 1999; 15(5):571–583.
Article
17. Mathie MJ, Coster AC, Lovell NH, Celler BG. Detection of daily physical activities using a triaxial accelerometer. Med Biol Eng Comput. 2003; 41(3):296–301.
Article
18. Uswatte G, Miltner WH, Foo B, Varma M, Moran S, Taub E. Objective measurement of functional upper-extremity movement using accelerometer recordings transformed with a threshold filter. Stroke. 2000; 31(3):662–667.
Article
19. Miyazaki S. Long-term unrestrained measurement of stride length and walking velocity utilizing a piezoelectric gyroscope. IEEE Trans Biomed Eng. 1997; 44(8):753–759.
Article
20. Mayagoitia RE, Nene AV, Veltink PH. Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. J Biomech. 2002; 35(4):537–542.
Article
21. Takeda R, Tadano S, Todoh M, Morikawa M, Nakayasu M, Yoshinari S. Gait analysis using gravitational acceleration measured by wearable sensors. J Biomech. 2009; 42(3):223–233.
Article
22. Roetenberg D. Inertial and magnetic sensing of human motion [dissertation]. Enschede: University of Twente;2006.
23. Altun K, Barshan B, Tuncel O. Comparative study on classifying human activities with miniature inertial and magnetic sensors. Pattern Recognit. 2010; 43(10):3605–3620.
Article
24. Kaewkannate K, Kim S. A comparison of wearable fitness devices. BMC Public Health. 2016; 16:433.
Article
29. Bertolotti GM, Cristiani AM, Colagiorgio P, Romano F, Bassani E, Caramia N, et al. A wearable and modular inertial unit for measuring limb movements and balance control abilities. IEEE Sens J. 2016; 16(3):790–797.
Article
30. Slaughter S, Hilbert C, Jouett N, McEwen M. Quantifying and learning human movement characteristics for fall prevention in the elderly using Inertial Measurement Units and Neural Networks. In : Proceedings of the 2nd International Conference of Education, Research and Innovation (ICERI); 2009 Nov 16-18; Madrid, Spain. p. 978–984.
31. Aziz O, Park EJ, Mori G, Robinovitch SN. Distinguishing near-falls from daily activities with wearable accelerometers and gyroscopes using Support Vector Machines. Conf Proc IEEE Eng Med Biol Soc. 2012; 2012:5837–5840.
Article
32. Frank K, Diaz EM, Robertson P, Sanchez FJ. Bayesian recognition of safety relevant motion activities with inertial sensors and barometer. In : Proceedings of 2014 IEEE/ION Position, Location and Navigation Symposium (PLANS); 2004 May 5-8; Monterey, CA. p. 174–184.
33. Yun X, Bachmann ER, Moore H, Calusdian J. Self-contained position tracking of human movement using small inertial/magnetic sensor modules. In : Proceedings of 2007 IEEE International Conference on Robotics and Automation; 2007 Apr 10-14; Rome, Italy. p. 2526–2533.
34. Epelde G, Carrasco E, Rajasekharan S, Jimenez JM, Vivanco K, Gomez-Fraga I, et al. Universal remote delivery of rehabilitation: validation with seniors' joint rehabilitation therapy. Cybern Syst. 2014; 45(2):109–122.
Article
35. Reiss A, Stricker D. Aerobic activity monitoring: towards a long-term approach. Univers Access Inf Soc. 2014; 13(1):101–114.
Article
36. Schall MC Jr, Fethke NB, Chen H, Oyama S, Douphrate DI. Accuracy and repeatability of an inertial measurement unit system for field-based occupational studies. Ergonomics. 2016; 59(4):591–602.
Article
37. Schulze M, Calliess T, Gietzelt M, Wolf KH, Liu TH, Seehaus F, et al. Development and clinical validation of an unobtrusive ambulatory knee function monitoring system with inertial 9DoF sensors. Conf Proc IEEE Eng Med Biol Soc. 2012; 2012:1968–1971.
Article
38. Dadashi F, Millet GP, Aminian K. Estimation of front-crawl energy expenditure using wearable inertial measurement units. IEEE Sens J. 2014; 14(4):1020–1027.
Article
44. Spinelle L, Gerboles M, Villani MG, Aleixandre M, Bonavitacola F. Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide. Sens Actuators B Chem. 2015; 215:249–257.
Article
45. Chen M, Ma Y, Song J, Lai CF, Hu B. Smart clothing: connecting human with clouds and big data for sustainable health monitoring. Mob Netw Appl. 2016; 21(5):825–845.
Article
46. Wan J, Zhang D, Sun Y, Lin K, Zou C, Cai H. VCMIA: a novel architecture for integrating vehicular cyber-physical systems and mobile cloud computing. Mob Netw Appl. 2014; 19(2):153–160.
Article
47. Peng L, Youn CH, Tang W, Qiao C. A novel approach to optical switching for intradatacenter networking. J Lightwave Technol. 2012; 30(2):252–266.
Article
48. Sanfilippo F, Pettersen KY. A sensor fusion wearable health-monitoring system with haptic feedback. In : Proceedings of 2015 11th International Conference on Innovations in Information Technology (IIT); 2015 Nov 1-3; Dubai, UAE. p. 262–266.
49. Arduino: an open-source electronics prototyping platform [Internet]. [place unknown]: Arduino;c2017. cited at 2017 Jan 25. Available from:
http://arduino.cc/.