OHSU Utilizes Sensors to Track Upper Extremity Motion Patterns during Surgical Simulation Training

The path to becoming a surgeon requires intensive training and extensive schooling. Typically, one must spend four years in undergraduate study, four years in medical school leading to a Doctor of Medicine degree, and then three to eight years of surgical residency at a hospital. Even with up to 16 years of education, work hour constraints limit the exposure of residents to the operating room. The fine motor control and dexterity required to successfully perform arthroscopic procedures has made surgical simulation a popular option for “real-life” experience to give residents more hands-on opportunities outside of an operating room. Surgical simulation is not only an alternate teaching method, but it also provides a standardized environment for performance assessment and feedback. Global rating scales like the Arthroscopic Surgical Skill Evaluation Tool (ASSET) have been developed to evaluate surgical performance, but these evaluations are subjective. Currently, there are no objective methods to evaluate a resident’s surgical performance in arthroscopy. Wearable sensors that track motion in real time can provide objective performance measures for numerous procedures and could therefore be a useful evaluation tool.

Validation of Upper Body Kinematics

A previous study led by Dr. Melissa Morrow at the Mayo Clinic validated the use of Opal wearable sensors against a video motion capture system in quantifying upper body kinematics. Six surgical faculty members performed a simulated surgical training task that mimics minimally invasive surgery while having 3-D kinematics recorded by an optical motion capture system and six Opal wearable sensors placed on the head, sternum, and arms. Comparing the absolute range of motion measured by the two systems showed excellent range agreement for the neck, trunk, and elbow flexion/extension measures [1]. Dr. Morrow’s current research with Dr. Stephen Cain of the University of Michigan entails utilizing Opal wearable sensors to quantify upper body kinematics of manual wheelchair users in the free-living environment. The goal of this work is to advance understanding of the kinematic mechanisms of shoulder overuse injury that is frequently experienced by manual wheelchair users [2].

Tracking Movement during Surgical Simulations

In the Oregon Health & Science University residency program, there are 50 hours of surgical simulation training during the third-year sports medicine rotation as well as a 40-hour arthroscopic “boot camp.” Dr. Michael Rose and his colleagues used Opal wearable sensors to assess the performance of orthopedic residents while performing a diagnostic knee arthroscopy. The 14 participants were divided into three groups based on experience: five were novices (third-year residents), another five were intermediates (fourth-year residents), and the remaining four were experts (surgeons specializing in orthopedic sports surgery). While the participants probed the areas of interest within the cadaver’s knee, arm movement data was collected with two Opal wearable sensors per arm, another placed on the sternum, and the sixth Opal placed on the low back.

Experienced Surgeons Require Less Movement

Figures A and B represent the average range of motion for the shoulder and the elbow. The left hand held a camera for visualization within the knee while the right hand probed the tissue of interest. The results show that expert surgeons required significantly less movement in the shoulder and elbow of the probe hand to execute the arthroscopic procedure compared to the novice or intermediate residents. This means that the surgeon’s level of experience could be determined based on the total motion required to execute a diagnostic knee arthroscopy [3]. As the American Academy of Orthopaedic Surgeons has mandated the development of surgical skills training as part of resident education, upper body joint kinematic data could be used in the future for proficiency-based progression. This in turn could allow talented residents to progress through their program more quickly, while others can receive the appropriate aid needed for success.

Quantifying 3-D Kinematics

APDM Wearable Technologies offers sensor-based solutions for quantifying human movement. APDM’s research-grade sensors and sophisticated algorithms are designed to streamline biomechanical research through automated movement analysis. Motion Studio provides access to raw movement data, Mobility Lab generates spatiotemporal outcome measures for gait and balance, and Moveo Explorer produces full-body kinematic data including joint angles and range of motion. For more information, please contact info@apdm.com.

REFERENCES

  1. Morrow et. al., “Validation of Inertial Measurement Units for Upper Body Kinematics.” Journal of Applied Biomechanics. 2017
  2. NIH R01 HD084423 (PI: Morrow)
  3. Rose et. al., “Wearable Inertial Sensors Allow for Quantitative Assessment of Shoulder and Elbow Kinematics in a Cadaveric Knee Arthroscopy Model.” Journal of Arthroscopic & Related Surgery. 2017
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