Date of Thesis

Spring 2026

Description

Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion vibrotactile feedback hub using Lab Streaming Layer (LSL) for synchronization. Four healthy amateur cyclists (4M, 22.3 ± 1.3 years) performed stationary cycling trials. Real-time feedback was delivered to the anterior thigh when the vastus medialis (VM) or semitendinosus (ST) reached a 10% contraction threshold within a targeted knee flexion window (8° more flexed than baseline). The system successfully delivered synchronized feedback across all participants with minimal error (~2% data loss). For the VM, participants exhibited a non-significant trend toward increased knee flexion at onset, 75.2 ± 24.1° in the feedback condition vs. 71.8 ± 17.7° at baseline (p< 0.1), suggesting a shift toward earlier activation in the pedal stroke. Conversely, ST onset showed a slight decrease in flexion angle, 92.6 ± 9.8° in the feedback condition vs. 94.9 ± 9.5° at baseline (p< 0.1), potentially due to the shorter perceptual window for feedback during the upstroke phase. Cadence remained stable across all conditions, ensuring that observed shifts were not a byproduct of altered pedaling speed. Both feedback trials were not statistically different from the baseline This study establishes the technical feasibility of a novel EMG-based vibrotactile feedback framework. While asymptomatic individuals may exhibit limited plasticity due to highly optimized motor patterns, the system reliably detected and responded to real-time physiological triggers. This technology provides a tangible, evidence-based tool for physical therapists to retrain neuromuscular coordination, offering a promising new direction for the treatment and prevention of musculoskeletal injuries in cycling.

Keywords

Biomechanics, Electromyography, Cycling, Knee Injury, Feedback, Rehabilitation

Access Type

Honors Thesis

Degree Type

Bachelor of Science in Biomedical Engineering

Major

Biomedical Engineering

Minor, Emphasis, or Concentration

Mathematics

First Advisor

Margo Donlin

Second Advisor

Benjamin Wheatley

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