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Assistant Professor
West Virginia University
I do not have any relevant financial / non-financial relationships with any proprietary interests.
BIOGRAPHICAL SKETCH
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NAME: Cain, Stephen Matthew
eRA COMMONS USER NAME (credential, e.g., agency login): smcain
POSITION TITLE: Assistant Professor
EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.)
INSTITUTION AND LOCATION DEGREE
(if applicable)
Completion Date
MM/YYYY
FIELD OF STUDY
The Pennsylvania State University BS 12/2002 Mechanical Engineering
The University of Michigan MS 04/2005 Mechanical Engineering
The University of Michigan MS 04/2012 Biomedical Engineering
The University of Michigan PhD 05/2013 Biomedical Engineering
The University of Michigan Postdoctoral 02/2015 Kinesiology
A. Personal Statement
My research is focused on using principles from inertial navigation, engineering dynamics, biomechanics, and kinesiology to develop algorithms and data collection protocols that utilize data from body-worn inertial sensors and other wearable technologies to quantify human movement and physiology in non-laboratory environments. Through the measurement of human movement in the real world, my research enables new research discoveries and the development of personalized interventions to help improve human health and performance.
Through my work on previous and current projects, which include collaborators at other research institutions, I am aware of the importance of frequent communication among project members and the need to establish realistic research goals, timelines, and budgets so that the necessary resources are available to achieve the research goals. I have helped train seven undergraduates, six graduate students, and one postdoc to use IMUs and to develop their own algorithms independently. In addition, I developed and presented an IMU tutorial at the annual conference of the American Society of Biomechanics. Therefore, I am confident that I can lead the development of the IMU-based algorithms required for quantifying the biomechanics of eye drop instillation, both in the clinic and in the real world. I am very excited about continuing my collaboration with Drs. Newman-Casey, Sample, and Burke, which has already resulted in a prototype eye drop adherence monitor. The collaborative work proposed here will result in knowledge that will help us make significant progress in our goal to develop a novel Eye Drop Adherence Monitoring System, which will enable the collection of the data necessary to develop personalized interventions to improve glaucoma medication adherence.
Ongoing and recently completed projects that I would like to highlight include:
American Cancer Society
Lipps (PI), Role: co-investigator
09/01/2020 – 08/31/2024
Quantifying outcomes after prepectoral implant-based breast reconstruction
NIH R01 HD084423
Morrow (PI), Role: co-investigator
06/01/2016 – 05/31/2021
Natural history of shoulder pathology in wheelchair users
US Army Contracting Command-APG, Natick Contracting Division, Natick, MA, contract W911QY-15-C-0053
Perkins and Stirling (PIs), Role: co-investigator
09/01/2015 – 01/31/2021
An automated measurement system for warfighter performance quantification in naturalistic settings
Citations:
1. Payne N, Gangwani R, Barton K, Sample AP, Cain SM, Burke DT, Newman-Casey PA, Shorter KA. Medication Adherence and Liquid Level Tracking System for Healthcare Provider Feedback. Sensors (Basel). 2020 Apr 24;20(8):2435. PMCID: PMC7219493
2. Schneider KJ, Hollenhorst CN, Valicevic AN, Niziol LM, Heisler M, Musch DC, Cain SM, Newman-Casey PA. Impact of the Support, Educate, Empower Personalized Glaucoma Coaching Program Pilot Study on Eye Drop Instillation Technique and Self-Efficacy. Ophthalmol Glaucoma. 2021 Jan-Feb;4(1):42-50. doi: 10.1016/j.ogla.2020.08.003. Epub 2020 Aug 8. PubMed PMID: 32781286; PubMed Central PMCID: PMC7854833.
3. Hallbeck MS, Law KE, Lowndes BR, Linden AR, Morrow M, Blocker RC, Cain SM, Degnim AC, Hieken TJ, Jakub JW, Racz JM, Farley DR, Nelson H, Boughey JC. Workload Differentiates Breast Surgical Procedures: NSM Associated with Higher Workload Demand than SSM. Ann Surg Oncol. 2020 May;27(5):1318-1326. doi: 10.1245/s10434-019-08159-0. Epub 2020 Jan 8. PubMed PMID: 31916090; PubMed Central PMCID: PMC7138769.
4. Cain SM, McGinnis RS, Davidson SP, Vitali RV, Perkins NC, McLean SG. Quantifying performance and effects of load carriage during a challenging balancing task using an array of wireless inertial sensors. Gait Posture. 2016 Jan;43:65-9. doi: 10.1016/j.gaitpost.2015.10.022. Epub 2015 Nov 2. PubMed PMID: 26669954.
B. Positions, Scientific Appointments, and Honors
Positions and Scientific Appointments
2021 – Present Assistant Professor, Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, WV
2017 – 2021 Assistant Research Scientist, Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI
2015-2017 Research Investigator, Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI
2014 – Present Member, International Society of Biomechanics
2011 – Present Member, American Society of Mechanical Engineers
2005 – Present Member, American Society of Biomechanics
Honors
2003 National Science Foundation Graduate Research Fellowship
C. Contributions to Science
1. Development and testing of algorithms for quantifying athletic performance using inertial sensors. The ability to quantify athletic performance in real-world environments has many applications, including providing immediate feedback to the athlete so he or she can modify his or her technique and evaluating performance degradation due to fatigue or load carriage. This work has been driven by a research project sponsored by the U.S. Army Natick Soldier Research, Development, and Engineering Center (NSRDEC). Working with members of Noel Perkins’s and Leia Stirling’s labs at the University of Michigan, we have been tasked with developing the methods to quantify warfighter performance during an extremely wide range of tasks, including: walking, running, sprinting, jumping, crawling, lifting, and crawling over/through obstacles. In general, athletic performance is well defined for constrained tasks (e.g. completing a specific obstacle or performing a specific movement), but our work demonstrates that different tasks require different algorithms to take advantage of the specific opportunities for correcting drift in sensor-based estimates of kinematics.
a. Potter MV, Ojeda LV, Perkins NC, Cain SM. Effect of IMU Design on IMU-Derived Stride Metrics for Running. Sensors (Basel). 2019 Jun 7;19(11). doi: 10.3390/s19112601. PubMed PMID: 31181688; PubMed Central PMCID: PMC6603669.
b. Vitali RV, Cain SM, Ojeda LV, Potter MV, Zaferiou AM, Davidson SP, Coyne ME, Hancock CL, Mendoza A, Stirling LA, Perkins NC. Body-worn IMU array reveals effects of load on performance in an outdoor obstacle course. PLoS One. 2019;14(3):e0214008. doi: 10.1371/journal.pone.0214008.
c. Ojeda LV, Zaferiou AM, Cain SM, Vitali RV, Davidson SP, Stirling LA, Perkins NC. Estimating Stair Running Performance Using Inertial Sensors. Sensors (Basel). 2017 Nov 17;17(11). doi: 10.3390/s17112647.
d. Cain SM, McGinnis RS, Davidson SP, Vitali RV, Perkins NC, McLean SG. Quantifying performance and effects of load carriage during a challenging balancing task using an array of wireless inertial sensors. Gait Posture. 2016 Jan;43:65-9. doi: 10.1016/j.gaitpost.2015.10.022. Epub 2015 Nov 2. PubMed PMID: 26669954.
2. Development and testing of algorithms for quantifying human movement during day-long collections in free-living environments using inertial sensors. Quantifying human movement during extended data collections in unknown free-living environments using IMUs poses a significantly different research challenge than quantifying athletic performance. Unlike athletic movements of interest, movements in free-living environments are largely unknown. Currently, my work in this area is focused on developing algorithms to estimate the shoulder rotations of wheelchair users and healthy matched controls in the real world. I became involved in this work in September 2016, and it is supported by an NIH R01 (PI: Melissa Morrow at Mayo Clinic). In this project, I am working to develop a novel approach to correct drift in the estimates of IMU orientations and to estimate orientations of the IMUs relative to anatomical body axes. These algorithms will enable accurate estimates of shoulder rotations for long-duration data collections and in environments with unknown magnetic fields.
a. Goodwin BM, Cain SM, Van Straaten MG, Fortune E, Jahanian O, Morrow MMB. Humeral elevation workspace during daily life of adults with spinal cord injury who use a manual wheelchair compared to age and sex matched able-bodied controls. PLoS One. 2021;16(4):e0248978. doi: 10.1371/journal.pone.0248978. eCollection 2021. PubMed PMID: 33891602; PubMed Central PMCID: PMC8064589.
b. Goodwin BM, Jahanian O, Cain SM, Van Straaten MG, Fortune E, Morrow MM. Duration of Static and Dynamic Periods of the Upper Arm During Daily Life of Manual Wheelchair Users and Matched Able-Bodied Participants: A Preliminary Report. Front Sports Act Living. 2021;3:603020. doi: 10.3389/fspor.2021.603020. eCollection 2021. PubMed PMID: 33842878; PubMed Central PMCID: PMC8034231.
c. Baroudi L, Newman MW, Jackson EA, Barton K, Shorter KA, Cain SM. Estimating Walking Speed in the Wild. Front Sports Act Living. 2020;2:583848. doi: 10.3389/fspor.2020.583848. eCollection 2020. PubMed PMID: 33345151; PubMed Central PMCID: PMC7739717.
d. Cain SM, MMB Morrow. Challenges and recommendations for quantifying shoulder motion using wearable inertial sensors. XXVII Congress of the International Society of Biomechanics, July 31-August 3, 2019, Calgary, Canada.
3. Quantifying pitching and throwing mechanics with wearable sensors. Most recently I have applied my knowledge of using wearable sensors to quantify human movement to investigate the biomechanics of throwing and pitching in real-world environments. This research has two goals: 1) understanding the factors that affect performance and 2) quantifying the factors that quantify stress on a thrower’s body, with a particular interest in the ulnar collateral ligament.
a. Agresta C, MT Freehill, J Zendler, J Hafer, G Giblin, S Cain. “Sensor Location Matters When Estimating Player Workload for Baseball Pitching.” Strength and Conditioning Journal (in review).
b. Rose M, McCollum KA, Freehill MT, Cain S. Quantifying Throw Counts and Intensities Throughout a Season in Youth Baseball Players: A Pilot Study. J Biomech Eng. 2020 Nov 6;. doi: 10.1115/1.4049025. [Epub ahead of print] PubMed PMID: 33156351.
c. Cain SM. “A Comparison of Filtering Techniques applied to Baseball Pitching Data.” 44th Annual Meeting of the American Society of Biomechanics, August 4-7, 2020, Atlanta, GA.
d. Cain SM, C Agresta. “Capturing day-to-day variability in pitching mechanics with an array of wearable inertial sensors.” XXVII Congress of the International Society of Biomechanics / 43rd Annual Meeting of the American Society of Biomechanics, July 31-August 3, 2019, Calgary, Canada.
Complete List of Published Work in MyBibliography: https://www.ncbi.nlm.nih.gov/myncbi/stephen.cain.1/bibliography/public/
