Research-backed corrective exercise programming with integrated workout tracking — evidence-grounded movement selection, compensatory pattern management, and persistent session logging in a single deliverable.
A client transitioning from home-based bodyweight training to a commercial gym environment presented a constellation of compensatory movement patterns: anterior pelvic tilt, thoracic kyphosis, scapular dyskinesis, and dynamic knee valgus. The left shoulder had documented reactivity during loaded extension positions.
The program needed to accomplish three things simultaneously: introduce machine and cable-based resistance training as the safer entry point for this pattern profile, provide research-grounded rationale for every exercise selection so the client understood why each movement mattered, and include a tracking system that captured movement quality — not just reps and weight — because for corrective programming, how a set was performed matters more than whether it was completed.
A mobile-first program viewer with 30 exercises across 3 training days, each carrying evidence boxes explaining the research rationale, machine setup cues, stop-if safety criteria, and compensatory pattern tags. Integrated workout logging captures reps, load, and per-set movement quality (Clean / Grind / Miss) with session history, retroactive entry, and local backup.
View Program →Comprehensive analysis of local gym facilities scored across corrective exercise value, schedule compatibility, equipment depth, and proximity. Evidence-tiered with source verification indicators. Includes class-by-class effectiveness scoring for compensatory exercise goals.
View Research →Every exercise was selected through a structured evidence review of peer-reviewed literature on scapular stabilization, kinetic chain rehabilitation, motor control retraining, knee valgus intervention, and respiratory muscle coordination. The program uses NASM OPT Phase 2 (strength endurance) as its periodization framework, with regional phase differentiation — meaning different body regions operate at different training phases based on their specific compensatory needs.
Guided movement paths let the client focus on effort while the equipment manages direction. Machines limit joints to intended ranges — critical when compensatory patterns could redirect force into reactive tissues.
Every exercise is tagged with the specific patterns it addresses: APT, kyphosis, scapular dysfunction, valgus, breathing. The client sees which compensation each movement targets and why it matters for their profile.
A three-level communication scale (Working / Talking / Done) replaces the binary pain/no-pain framework. “Stop If” criteria on every exercise give explicit permission to modify or stop — because the client who feels empowered to stop is the client who stays safe.
Six movements are explicitly excluded with documented rationale and specific re-entry conditions. Nothing is permanently off the table — the program is building toward these movements, not avoiding them.
The program viewer is a single-file application (178 KB) built in vanilla HTML, CSS, and JavaScript. Program content is authored as semantic HTML with structured data attributes. A bridge layer connects the static exercise cards to a tracking system that manages state via IndexedDB for offline-first persistence.
Session tracking captures three dimensions per set: what happened (reps and load), perceived quality (Clean / Grind / Miss), and contextual notes. Previous session data appears inline as reference when logging new workouts, showing the client exactly what they did last time. Sessions can be edited retroactively and exported as JSON backups.
The architecture includes a synchronization layer designed for cloud persistence via Cloudflare D1, activatable when the client is ready for cross-device access. The local-first approach means the application works fully offline from day one — cloud sync adds convenience without creating dependency.
The evidence base draws from three structured research databases totaling over 9,000 indexed passages across 22 peer-reviewed sources. Each evidence claim in the program viewer carries a three-layer citation: a bidirectional footnote linking text to source and back, a source link with evidence-tier indicator and archive fallback, and where possible, a direct quote-link that navigates to the specific passage in the original publication.
The gym facility research used a separate evidence grading system with each claim tagged to its verification level. Where information could not be verified from published sources, explicit gap markers identify what still requires direct confirmation — because acknowledging uncertainty is more useful than hiding it.