Human-Device Interaction
Human-Device Interaction Lab Photo
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Summary
The human-device interaction group advances regulatory science through the study of human interaction with existing and emerging medical device technologies. Our overarching goal is to improve therapeutic, diagnostic, and rehabilitative outcomes for patients. In addition to applications to neurology, physical medicine, orthopedics, and surgery, the lab is equipped to address cognitive and other human factors that influence device usability across therapeutic areas.
Available instrumentation includes an extensive array of leading edge equipment for monitoring and modeling medical devices and human users, including 3D-printing capabilities, motion and ground force capture technologies, computational modeling and simulation tools, and muscle monitoring (electromyogram), brain monitoring (electroencephalogram), and eye-tracking systems.
Optical markers are used to track and quantify movements in space.
A virtual environment for studying prosthetic function.

A hand function test based on activities of daily living.
Current project areas include:
- Test method development for next-generation upper limb prosthetics
- Sex-specific modeling and analysis of ACL injury susceptibility
- Assessment of patient views on risks and benefits of innovative prosthetic technologies
- Human factors evaluation of 3D-printed patient-matched surgical instrumentation
- Real-world data collection for larger, smarter, distributed clinical trials
- Population variability of EEG biomarkers with potential diagnostic utility
We are continually seeking collaborations with other medical device stakeholders, including clinicians, academic researchers, technology developers, and our colleagues at the FDA and the National Institutes of Health.
For Center and Agency programs and initiatives related to work in this group, please see the following resources:
- Public Workshop on Brain-Computer Interface Devices for Patients with Paralysis and Amputation (including presentations by OSEL scientists)
- Medical Device Innovation Consortium: Patient-Centered Benefit-Risk Assessment
- CDRH Medical Device Development Tool DRAFT Guidance
- FDA Voice Blog Post: Listening to Patients’ Views on New Treatments for Obesity
Current funding sources
Personnel
FDA Staff:
Kimberly Kontson, Ph.D.
LT James Coburn
David Soltysik, Ph.D.
Heather Benz, Ph.D.
Research Fellows:
Conor Bloomer
Chris Gaskins
Janell Joyner
David Nahmias
Sophie Wang
Visiting Scientist:
Eugene Civillico, Ph.D.
FDA collaborators
Ian Marcus
External collaborators
Advanced Arm Dynamics
Defense Advanced Research Projects Agency (DARPA)
Temple University Electrical & Computer Engineering
Medical Device Innovation Consortium (MDIC)
University of Maryland Mechanical Engineering
University of Alberta
University of Houston Electrical & Computer Engineering
University of Maryland Neuroscience and Cognitive Science
Veterans Administration
Walter Reed National Military Medical Center
Resource facilities
Hardware
- Gait and force measurement
- 2 Kistler force measurement platforms integrated into a portable walkway
- Vicon Bonita 3D motion capture system
- ATI Industrial Automation Mini-45 6-degree of freedom force transducer systems
- EMG
- Delsys tethered 8-channel EMG system
- Trigno 16-channel wireless EMG/accelerometer system
- Eye tracking
- Mobile Eye-XG
- EEG
- 64 channel BE Plus LTM mobile system
- 64-channel EGI system
- NetStation software
- “button box” for registering subject input and choices
- Empatica E4 Wristband for EDR, temperature, PPG, and acceleration monitoring
Software
- ANSYS
- LabView
- MATLAB
- ePrime
- Solidworks
Relevant Standards & Guidances
- Human Factors and Medical Devices
- Human Factors Premarket Evaluation
- Agency Expectations for Human Factors Data in Premarket Submissions (2012 Draft Guidance)
- AAMI Handbook of Human Factors in Medical Device Design (complements HE75:2009, the FDA-recognized AAMI standard on Human Factors Engineering)
- Innovative Devices
Selected peer-review publications
- Kontson et al., Targeted box and blocks test: Normative data and comparison to standard tests. PLoS One. 2017
- Kontson et al., An integrated movement analysis framework to study upper limb function: A pilot study. IEEE Trans Neural Sys Rehab Engr. 2017
- Benz et al., System to induce and measure embodiment of an artificial hand with programmable convergent visual and tactile stimuli. IEEE Eng Med Biol Soc. 2016
- Donaldson et al., Prediction of contact mechanics in metal-on-metal Total Hip Replacement for parametrically comprehensive designs and loads J Biomechanics 2015.
- Donaldson et al., Total hip arthroplasty head-neck contact mechanics: a stochastic investigation of key parameters. J Biomechanics 2014.
- Wang S, Hsu CJ, Trent L, Ryan T, Kearns NT, Civillico EF, Kontson KL. Evaluation of Performance-Based Outcome Measures for the Upper Limb: A Comprehensive Narrative Review. PM and R. 2018;10(9):951-62.e3.