Nonlinear stochastic system identification techniques, including Volterra kernels and Wiener static nonlinearities, provide broad frameworks of assumptions to model data. By designing Lorentz force linear actuator systems with high-bandwidth characteristics, we were able to study the nonlinear dynamic properties of biological systems with stochastic system identification techniques. Using these methods, it is possible to characterize human behaviors, study tissue behaviors due to disease, or assess the efficacy of commercial products.
Recently, we have been applying these techniques to study complex soft robotic systems. We have also utilized extended Kalman filters to characterize the complex nonlinear behavior of exothermic polymers.
Selected Publications:
- A. Mazumdar†, Y. Chen†, B. G. van Bloemen Waanders, C. F. Brooks, M. Kuehl, and M. B. Nemer, “Wireless Temperature Sensing Using Permanent Magnets for Nonlinear Feedback Control of Exothermic Polymers,” IEEE Sensors Journal, vol.18, no. 19, pp. 7970-7979, 2018. [†These Authors Contributed Equally to this Work] [https://doi.org/10.1109/JSEN.2018.2863249]
- Y. Chen and I. W. Hunter, “Nonlinear Stochastic System Identification of Skin Using Volterra Kernels,” Annals of Biomedical Engineering, vol. 41, no. 4, pp. 847-862, 2013. [http://dx.doi.org/10.1007/s10439-012-0726-x]
- E. J. Sandford, Y. Chen, I. W. Hunter, G. Hillebrand, and L. A. Jones, “Capturing skin properties from dynamic mechanical analyses,” Skin Research and Technology, vol. 19, pp. e339-e348, 2013. [http://dx.doi.org/10.1111/j.1600-0846.2012.00649.x]
- Y. Chen and I. W. Hunter, “Stochastic System Identification of Skin Properties: Linear and Wiener Static Nonlinear Methods,” Annals of Biomedical Engineering, vol. 40, no. 10, pp. 2277-2291, 2012. [http://dx.doi.org/10.1007/s10439-012-0580-x]
- (*) N. Kohls, B. Dias, Y. Mensah, B. P. Ruddy, and Y. C. Mazumdar, “Compliant Electromagnetic Actuator Architecture for Soft Robotics, ” Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020. [In Press]
- Y. Chen and I. W. Hunter, “In Vivo Characterization of Skin using a Wiener Nonlinear Stochastic System Identification Method,” 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6010-6013, 2009. [http://dx.doi.org/10.1109/IEMBS.2009.5334028]
- I. W. Hunter and Y. Chen and L. A. Jones and N. C. Hogan, “Identification techniques and device for testing the efficacy of beauty care products and cosmetics,” U. S. Patent 9,265,461[http://www.freepatentsonline.com/9265461.html] [https://www.google.com/patents/US9265461]. U. S. Patent Application 20110054355 A1 [http://www.google.com/patents/US20110054355].
- I. W. Hunter and Y. Chen, “Nonlinear system identification techniques and device for discovering dynamic and static tissue properties,” U. S. Patent 8,758,271 B2, June 14, 2014. WO Patent Application 2,011,028,719. [http://www.google.com/patents/US20110054354].
- Y. Chen, “Nonlinear stochastic system identification techniques for biological tissues”, S. M. Thesis, Massachusetts Institute of Technology, 2010. [https://dspace.mit.edu/handle/1721.1/62122].