Internet of Medical Things

Faculty: Tom Bailey, Yixin Chen, Marin Kollef, Chenyang Lu, Susan Stark

Team members: Xin Hu, Jay Amrish Vaidya, Michael Wang 

Past team members and collaborators: Stephen Bosch, Chris Brooks, Ben Bush, Roger Chamberlain, Octav Chipara, Rahav Dor, Greg Hackmann, Bo Li, Yi Mao, Catalin Roman, Zhicheng Yang

Department of Computer Science and Engineering, School of Engineering, Washington University
Department of Medicine,
School of Medicine, Washington University
BJC HealthCare
Institute of Clinical and Translational Sciences, Washington University

Clinical Warning System

Early detection and intervention are essential for preventing clinical deterioration in patients.  We are developing a two-tiered clinical warning system designed to identify the signs of clinical deterioration and provide early warning of serious clinical events at general hospital units.  The first tier of the system automatically identifies patients at risk of clinical deterioration from existing electronic medical record databases.  The second tier performs real-time clinical event detection based on vital sign data collected from on-body wireless sensors attached to those high-risk patients.  Wireless sensor networks play an important role in clinical warning by collecting real-time vital signs for clinical decision support.  We have developed and deployed a large-scale wireless clinical monitoring system that encompasses portable wireless pulse oximeters, a wireless relay network spanning multiple hospital floors, and integration with electronic medical record databases.  Our system has been deployed over a 14-month clinical trial in six hospital wards of Barnes-Jewish Hospital in St. Louis, Missouri.  Our experiences show the feasibility of achieving reliable vital sign collection using a wireless sensor network integrated with hospital IT infrastructure and procedures.  We also identify and overcome technical and non-technical elements that pose challenges in a real-world hospital environment and provide guidelines for successful and efficient deployment of similar systems.  The convergence of wireless sensors, mobile computing, data mining and electronic medical record in clinical warning systems will lead to enhanced quality of care for patients in hospitals as well as outpatients in their everyday lives.

Wireless Clinical Monitoring Systems at Washington University

Fall Studies of Community-Dwelling Older Adults

Despite over a decade of research and development in fall detection systems, accurate and reliable systems in use are few. The existing fall detection approaches leave three major challenges unsolved: (1) insufficient fall data for model training process, (2) unreliable labeling of ground truth, and (3) resorting to artificial falls to model falls. We are addressing these challenges through an inter-disciplinary clinical study with community-dwelling older adults. The data collected from the real world reveal significant differences between artificial falls and actual falls, and also to illuminate the limitations of existing algorithms. We are developing new fall studies and technologies based on the challenges, experience, and lessons we learned from earlier studies.

News Coverage

Wireless Sensors Relay Medical Insight to Patients and CaregiversIEEE Signal Processing Magazine, 29(3): 8-12, May 2012.

Washington University Researchers Seek to Bring Mobility to ICU Patients, RFID Journal, August 2011.

Mesh Network Monitors Patients in Virtual ICU, British Journal of Healthcare Computing, August 2011.

Hospital Tests Wireless Patient Monitoring, UPI, August 2011.

Clinical Warning System Could Change Healthcare,, August 2011.

St. Louis Hospital Tests Wireless System That Monitors Vital Signs,
iHealthBeat, Augist 2011.

Wireless Network in Hospital Monitors Vital Signs, Washington University News Release, August 2011.


X. Hu, R. Dor, S. Bosch, A. Khoong, J. Li, S. Stark and C. Lu, Challenges in Studying Falls of Community-dwelling Older Adults in the Real World, IEEE International Conference on Smart Computing (SMARTCOMP'17), May 2017. (Invited Paper)

D. Picker, M. Dans, K. Heard, T. Bailey, Y. Chen, C. Lu and M.H Kollef, A Randomized Trial of Palliative Care Discussions Linked to an Automated Early Warning System Alert, Critical Care Medicine, 45(2): 234-240, February 2017.

M.H. Kollef, K. Heard, Y. Chen, C. Lu, N. Martin and T. Bailey, Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts, American Journal of Medical Quality, 32(1): 12-18, January/February 2017.

S.T. Micek, M. Samant, T. Bailey, Y. Chen, C. Lu, K. Heard and M.H. Kollef, Real-Time Automated Clinical Deterioration Alerts Predict Thirty-Day Hospital Readmission, Journal of Hospital Medicine, 11(11): 768772, November 2016.

Y. Wang, W. Chen, K. Heard, M. Kollef, T. Bailey, Z. Cui, Y. He, C. Lu and Y. Chen, Mortality Prediction in ICUs Using a Novel Time-Slicing Cox Regression Method, American Medical Informatics Association Annual Symposium (AMIA-15), November 2015. Distinguished Paper Award

M.H. Kollef, Y. Chen, K. Heard, G.N. LaRossa, C. Lu, N.R. Martin, N. Martin, S.T. Micek and T. Bailey, A Randomized Trial of Real-Time Automated Clinical Deterioration Alerts Sent to a Rapid Response Team, Journal of Hospital Medicine, 9(7): 424429, July 2014.

T. Bailey, Y. Chen, Y. Mao, C. Lu, G. Hackmann, S.T. Micek, K. Heard, K. Faulkner, M.H. Kollef, A Trial of a Real-Time Alert for Clinical Deterioration in Patients Hospitalized on General Medical Wards, Journal of Hospital Medicine, 8(5): 236242, May 2013.

R. Dor, G. Hackmann, Z. Yang, C. Lu, Y. Chen, M. Kollef and T.C. Bailey, Experiences with an End-To-End Wireless Clinical Monitoring System, Conference on Wireless Health (WH'12), October 2012.

Y. Mao, W. Chen, Y. Chen, C. Lu, M. Kollef and T.C. Bailey, An Integrated Data Mining Approach to Real-time Clinical Monitoring and Deterioration Warning, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), August 2012.

Y. Mao, Y. Chen, G. Hackmann, M. Chen, C. Lu, M. Kollef and T.C. Bailey, Early Deterioration Warning for Hospitalized Patients by Mining Clinical Data, International Journal of Knowledge Discovery in Bioinformatics, 2(3):1-20, 2012. (Extended version of the BioDM'11 paper.)

Y. Mao, Y. Chen, G. Hackmann, M. Chen, C. Lu, M. Kollef and T.C. Bailey, Medical Data Mining for Early Deterioration Warning in General Hospital Wards, ICDM Workshop on Biological Data Mining and its Applications in Healthcare (BioDM'11), December 2011.

G. Hackmann, M. Chen, O. Chipara, C. Lu, Y. Chen, M. Kollef and T.C. Bailey, Toward a Two-Tier Clinical Warning System for Hospitalized Patients, American Medical Informatics Association Annual Symposium (
AMIA'11), October 2011.

O. Chipara, C. Lu, T.C. Bailey and G.-C. Roman, Reliable Clinical Monitoring using Wireless Sensor Networks: Experience in a Step-down Hospital Unit, ACM Conference on Embedded Networked Sensor Systems (SenSys'10), November 2010.

J. Ko, C. Lu, M.B. Srivastava, J.A. Stankovic, A. Terzis and M. Welsh, Wireless Sensor Networks for Healthcare, Proceedings of IEEE, 98(11): 1947 - 1960, November 2010.

O. Chipara, G.Hackmann, C. Lu, W. Smart and G.-C. Roman, Practical Modeling and Prediction of Radio Coverage in Indoor Sensor Networks, ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'10), April 2010.

O. Chipara, C. Brooks, S. Bhattacharya, C. Lu, R.D. Chamberlain, G.-C. Roman, and T.C. Bailey, Reliable Real-time Clinical Monitoring Using Sensor Network Technology, American Medical Informatics Association (AMIA) Annual Symposium, November 2009.


Wireless Clinical Monitoring at Scale, Distinguished Lecture, DGIST Global Innovation Festival (DGIF), November 2013.

Wireless Clinical Monitoring at Scale, Samsung Advanced Institute of Technology, November 2013.

Toward Wireless Clinical Warning in Hospitals and Beyond, Illinois Institute of Technology, September 2013.

Toward a Two-Tier Clinical Warning System for Hospitalized Patients, American Medical Informatics Association Annual Symposium (
AMIA'11), October 2011.

Reliable Clinical Monitoring using Wireless Sensor Networks: Experience in a Step-down Hospital Unit, ACM Conference on Embedded Networked Sensor Systems (SenSys'10), November 2010.

Toward Wireless Clinical Monitoring in General Hospital Units, PRECISE Seminar, University of Pennsylvania, October 2010.


The project described was supported by Award Number UL1RR024992 from the National Center For Research Resources and BJH Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.