CirQ - Empowered Life

A line of connected compression base layers to monitor muscle actuation, load balance, and muscle fragmentation. Post activity analytics enable users to better understand joint strain, inflamation, and potential injury vulnerabilities leading to prevent new or reoccurring injuries.

Using AI analysis of users’ performance, the connected App will alert users to injury susceptibility and suggest changes to conditioning regimens to optimize training and create more durable athletes.

Sport Injuries

In 2013, Major League Baseball spent $665 million on injured players and their replacements; NBA teams lost $358 million; and in the NFL, where the average salary is about $2 million, starters missed a record 1,600 games.

Embedded Deformation Soft-Sensors

RehA monitors which muscles are actuating and to what degree in order to avoid over-training or underperforming.

Collected data is visually displayed within the app providing the user with a post work-out summary of joint load, and suggests optimized, personalized recovery strategies.

By analyzing muscular balance, weak points can be identified, and targeted for improvement in future training.

Load balance is a critical component to understanding, preventing, and predicting injuries. Muscular imbalances involve a set of stronger muscles compensating for underdeveloped counter-muscles, causing undue strain on the joints.

RehA employs machine learning algorithms to identify muscle fragmentation within a specific movement.

Many sports, like tennis, require athletes to repetitively perform a very specific movement. Understanding which muscles contribute to a specific movement can improve form and allow athletes to train more efficiently.

RehA Compression Base-layer Features

Monitors exertion of major muscle groups focused around commonly injured joints: shoulders, elbows, wrists, hips, knees, and ankles.
Real-time tracking of muscle activity, joint load, duration and intensity of activity.
Biometric data syncs to users’ device via Bluetooth; data is automatically run through localized machine learning models, and performance reports and insights can be shared with medical professionals, remote trainers, coaches, etc.
Unobtrusive, waterproof, machine washable sensors are seamlessly embedded into fabric for freedom of movement and performance.