David Mandeville


David Mandeville

College Of Education And Human Development

Department of Counseling, Health and Kinesiology


Assistant Professor

STEM 142D
(210) 784-2582
dmandeville@tamusa.edu
View CV

David Stewart Mandeville, Ph.D.

Biomechanics & Human Physiology | Email: dmandeville@tamusa.edu | Phone: 210.784.2582

Professional Biography

Dr. David Stewart Mandeville is an accomplished human physiologist and biomechanist specializing in clinical biomechanics, wearable sensor technologies, and lower extremity gait stability. He earned his Ph.D. in Human Physiology and M.S. in Exercise Science from the University of Oregon, following a B.A. in Exercise Science and Athletic Training from Fort Lewis College.

With extensive academic and research experience spanning nearly two decades, Dr. Mandeville has served as Primary Investigator on federally and institutionally funded projects, including an NIH Extramural Associates Research Development Award (EARDA). His research integrates 3D motion capture, wearable inertial measurement unit (IMU) sensors, and predictive machine learning algorithms to assess fall risks in older adults and evaluate the biomechanical effects of knee osteoarthritis, total knee replacement, and musculoskeletal deformities. His work is widely published in high-impact journals such as Gait & Posture, Clinical Biomechanics, and the Journal of College Science Teaching.

In the classroom, Dr. Mandeville is an innovator in evidence-based, problem-based learning (PBL) and Quality Matters (QM) certified course design. He has developed pioneering metacognitive assessment scales and mentored numerous graduate and undergraduate students in clinical biomechanics and research design.

Areas of Expertise & Research Interests

  • Clinical Biomechanics & Gait Stability: 3D optical motion capture, lower extremity kinematics/kinetics, knee osteoarthritis, and post-arthroplasty rehabilitation.
  • Wearable Sensor Technology & Fall Prevention: IMU signal processing, cadence feature extraction, and fuzzy inference/machine learning algorithms for elderly fall risk assessment.
  • Scholarship of Teaching & Learning (SoTL): Problem-based learning (PBL), metacognitive development (MINDS scale), student-centered STEM pedagogy, and Quality Matters online instruction.

 

Course Teachings

SubjectNumberSectionDescriptionTermSyllabi
EDKN 4344 001 Health & Aging Fall 2026 Syllabus
EDKN 5310 01 Advanced Human Anatomy Fall 2026 Syllabus