Motion Capture Suite

 

Our state-of-the-art motion capture facility is designed for research in human performance and biomechanics. This facility enables users to conduct human-centered studies and test prototype technologies using multimodal physiological monitoring devices. It is equipped with an 11-camera VICON Vantage system and a Lock+ 64-channel ADC, which allows for the capture of high-resolution motion data for gait analysis and rehabilitation studies. Additional hardware includes integrated AMTI force plates that provide detailed force measurements, a Delsys Trigno Wireless system for real-time monitoring of muscle activity using 16 Avanti EMG sensors, and BioSignalPlux wearable devices for measuring electrodermal activity related to physical stress and respiration. The facility also features configurable exercise equipment for kinesiology and sports medicine studies, including doors and stairs. The facility has been serving researchers from a wide variety of academic departments on campus, as well as corporate partners, to conduct innovative research studies.

For more information on how to get involved, contact:

Catherine Bouthillier
cbouthillier@wpi.edu
(M) 860-428-6840
(O) 508-831-4653

Preview walkthrough

Equipment:

  • 11 Camera VICON Vantage motion capture system with Lock+ 64-channel ADC 
  • VICON Vue for color video overlay 
  • Gait analysis track with two integrated AMTI OPT400600 force plates 
  • Delsys Trigno Wireless system with 16 Avanti EMG sensors containing integrated IMU, Bluetooth compatibility, and SDK/ API support 
  • Configurable exercise equipment and obstacles to include doors and stairs 
  • Ability to connect to external ultrasounds and accelerometers 

Selected Research Publications Utilizing the Facility:

  1. Meier, Tess B., Alexander Spencer, John P. Chiodini, Bhawna Shiwani, Serge H. Roy, Gianluca DeLuca, Joshua C. Kline, and Paola Contessa. "A Wearable Sensor-based System For Gait Analysis That Is Robust To Gait Variations: 173." Medicine & Science in Sports & Exercise 53, no. 8S (2021): 53.
  2. K. Yang, T. B. Meier, H. Zhou, G. S. Fischer and C. J. Nycz, "A sEMG Proportional Control for the Gripper of Patient Side Manipulator in da Vinci Surgical System," 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Glasgow, Scotland, United Kingdom, 2022, pp. 4843-4848, doi: 10.1109/EMBC48229.2022.9871664.
  3. N. Goldfarb, H. Zhou, C. Bales and G. S. Fischer, "Control of a lower limb exoskeleton using Learning from Demonstration and an iterative Linear Quadratic Regulator Controller: A simulation study," 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Mexico, 2021, pp. 4687-4693, doi: 10.1109/EMBC46164.2021.9630810.

  4. N. Goldfarb, C. Bales and G. S. Fischer, "Toward Generalization of Bipedal Gait Cycle During Stair Climbing Using Learning From Demonstration," in IEEE Transactions on Medical Robotics and Bionics, vol. 3, no. 2, pp. 446-454, May 2021, doi: 10.1109/TMRB.2021.3070019.