JL Pulse

The Coaching Problem I Identified

Coaches can see technique and record times, but those observations do not fully explain how an athlete is responding internally to workload, fatigue, speed, and recovery. Important signals are spread across devices, subjective check-ins, training notes, and the coach’s own judgment.

I defined JL Pulse as the sensing layer that brings those signals into the same coaching conversation—without replacing the coach or overwhelming the athlete with raw data.

• Connect internal workload to visible movement
• Recognize meaningful changes across repetitions
• Preserve athlete and coach context
• Turn sensor output into an actionable training decision

The Product System I Designed

I separated the JL performance ecosystem into three clear responsibilities. This prevents one product from trying to do everything and gives every signal a defined destination.

JL Pulse senses the athlete—capturing movement and physiological response during training.

JL Vision interprets movement—analyzing biomechanics, technique, movement quality, and performance patterns.

MovementOS connects the athlete story—combining sensor information, assessments, coaching observations, and history into a longitudinal performance profile.

• Sensing layer
• Movement-intelligence layer
• Coaching and athlete record
• Shared performance language

Decisions Grounded in Coaching

My design criteria came from nearly three decades of athlete development. A useful performance product has to work between repetitions, support individual baselines, and communicate clearly enough for athletes and families to understand.

That led me to prioritize interpretation and workflow over a dashboard filled with isolated metrics.

• Monitor intensity across repetitions
• Compare movement with physiological response
• Track readiness and recovery over time
• Flag changes associated with fatigue
• Support individualized session adjustments
• Keep the coach responsible for the final decision

Hardware and Platform Evaluation

I evaluated Movesense HR+ as a credible foundation for the JL Pulse prototype direction because it combines a nine-axis IMU, ECG, heart rate, heart-rate variability, temperature measurement, Bluetooth connectivity, onboard processing, and local logging in an open programmable platform.

Its APIs, customizable firmware, extension interface, and OEM path make it suitable for validating workflows before investing in custom JL Pulse hardware.

• Nine-axis motion sensing
• ECG, heart rate, and HRV
• Temperature monitoring
• Bluetooth data transfer
• On-sensor processing and logging
• Open APIs and firmware extensibility

Constraints and Development Roadmap

Movesense HR+ does not include integrated EMG or a built-in haptic actuator. I treat those as explicit product constraints—not capabilities to imply before they exist.

The development path is to validate sensing and coaching workflows first, then evaluate connected EMG, external feedback components, custom enclosures, and eventually purpose-built hardware where the use case justifies it.

• Validate athlete and coach workflows
• Test signal quality during training
• Define useful thresholds and alerts
• Investigate connected EMG
• Prototype athlete-specific haptic feedback
• Integrate JL Vision and MovementOS data

What This Work Demonstrates

JL Pulse brings together the two sides of my career: deep coaching experience and enterprise technology thinking. I can identify a real performance problem, translate it into a product system, evaluate enabling technology, define honest constraints, and communicate the result to coaches, athletes, technical partners, and decision-makers.

The dedicated JL Influence experience shows the product direction in action. This case study explains the judgment and work behind it.

Sense the athlete. Understand the movement. Respond with purpose.