Personalizing object handover with an electronic health record
Pages 1144 - 1149
Abstract
Comfortable object handover involves searching for a person, identifying them, and then actually handing them an object. It is a goal of many robotics applications, particularly in healthcare. But people can have a wide variety of physical, perceptual, or cognitive limitations. To address these variable patient conditions with an autonomous robot, a robot must adapt to these individual differences. In this work, we first interviewed nurses regarding common issues faced by healthcare providers. Then we designed a system that interfaces with an individual's electronic health record, and adapts its search and handover capabilities to improve the quality of object handover.
VI. References
[1]
C. King et al., “Dusty: an assistive mobile manipulator that retrieves dropped objects for people with motor impairments”, Disability and Rehabilitation: Assistive Technology, vol. 7, p. 168–179, 2012.
[2]
D. Fischinger et al., “Hobbit - The Mutual Care Robot”, in Int Conf on Intelligent Robots and Systems, Tokyo, 2013.
[3]
F. Cavallo et al., “Development of a Socially Believable Multi-Robot Solution from Town to Home”, Journal of Cognitive Computation, vol. 6, no. 4, pp. 954–967, 2014.
[4]
A. Kristoffersson et al., “Towards Measuring Quality of Interaction in Mobile Robotic”, Journal of Behavioral Robotics, vol. 4, no. 1, pp. 34–48. 2013.
[5]
M. Cakmak et al., “Human preferences for robot-human hand-over configurations”, in Int Conf on Intelligent Robots and Systems, San Francisco. CA. 2011.
[6]
K. Dautenhahn et al., “How may I serve you?: a robot companion approaching a seated person in a helping context”, in Proc of 1 st ACM Conf on Human-Robot Interaction, Salt Lake City, UT, 2006.
[7]
M. Davis et al., “Towards Context-Aware Face Recognition”, in Int Conf on Multimedia. New York. NY. 2005.
[8]
E. Martinson, W. Lawson and G. Trafton, “Identifying People with Soft-Biometrics at Fleet Week”, in Human Robot Interaction, Tokyo, Japan, 2013.
[9]
D. Chaffin et al., “Stature, age, and gender effects on reach motion nostures”. Human Factors. vol. 42. pp. 408–420. 2000.
[10]
J. Soucie et al., “Range of motion measurements: reference values and a database for comparison studies”, Haemophilia 2010, e-pub November 11. 2010.
[11]
A. Reeves and R. Swenson, “Disorders of the Nervous System: A Primer”. Dartmouth Medical School. 2008.
[12]
A. Berardelli et al., “Pathophysiology of bradykinesia in Parkinson's disease”, Brain, pp. 2131–2146, 2001.
[13]
“OpenEMR 4.2.0 Users Guide”, 14 Dec 2014. [Online]. Available: http://www.open-emr.org/wiki/index.php/OpenEMR_4.2.0_Users_Guide. [Accessed 30 Jan 2015].
[14]
E. Martinson, “Detecting Occluded People for Robotic Guidance”, in Robots and Human Interactive Communication (RO-MAN), Edinburgh, UK, 2014.
[15]
J. Yoon, “Frontal face classifier using AdaBoost with MCT features”, in Int Conf on Control Automation and Vision, Singapore, 2011.
[16]
B. Suay and A. Sisbot, “A Position Generation Algorithm Utilizing A Biomechanical Model For Robot-Human Object Handover”, in Int Conf on Robotics and Automation, Seattle, WA, 2015.
[17]
D. Chaffin, G. Andersson and B. Martin, Occupational Biomechanics, Hoboken, NJ: John Wiley & Sons, Inc, 2006.
[18]
D. Berenson, S. Srinivasa and J. Kuffner, “Task Space Regions: A Framework for Pose-Constrained Manipulation Planning”, Int. Journal of Robot Res, vol. 30, no. 12, pp. 1415–1460, 2011.
[19]
E. Hall, The Hidden Dimension, Garden City, NY: Doubleday, 1966.
Index Terms
- Personalizing object handover with an electronic health record
Index terms have been assigned to the content through auto-classification.
Recommendations
EEMI-An Electronic Health Record for Pediatricians: Adoption Barriers, Services and Use in Mexico
The use of paper health records and handwritten prescriptions are prone to preset errors of misunderstanding instructions or interpretations that derive in affecting patients' health. Electronic Health Records EHR systems are useful tools that among ...
Using electronic health record systems in diabetes care: emerging practices
IHI '10: Proceedings of the 1st ACM International Health Informatics SymposiumWhile there has been considerable attention devoted to the deployment of electronic health record (EHR) systems, there has been far less attention given to their appropriation for use in clinical encounters --- particularly in the context of complex, ...
Benefits and Challenges of Electronic Health Record System on Stakeholders: A Qualitative Study of Outpatient Physicians
Electronic health record system (EHRS) is an important healthcare innovation associated with many controversies about the benefits and challenges to different stakeholders. The aim of this study was to investigate the utility of EHRS by outpatient ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
1025 pages
Copyright © 2016.
Publisher
IEEE Press
Publication History
Published: 01 August 2016
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 16 Nov 2024
Other Metrics
Citations
View Options
View options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in