SageMotion designs and manufactures wearable haptic feedback systems for real-time movement assessment and training

Leadership

We started SageMotion in 2019 and created the world’s first wearable haptic feedback system with full customization and open algorithm code. We love helping biomechanics researchers perform novel motion training research that impacts humanity by improving movement in medical and sports applications.

We are an energetic team of biomechanists, programmers, engineers, sales & support specialists and staff with extensive experience in the development, testing, and implementation of wearable sensing and feedback hardware and software for movement assessment and training research.

Below is a short Q&A about why we care about haptic feedback, customization, open algorithm code, and python programming.

Why Haptic Biofeedback?

Haptic biofeedback is a powerful way to train human motion by stimulating mechanoreceptors in the skin. Haptic, tactile feedback cues naturally guide new human movements and can be applied across multiple locations on the body to simultaneously train one or more movement parameters. Haptic feedback is wearable, eliminating the need for tethered laboratory equipment like mounted cameras, and unlike visual and auditory feedback, haptic feedback does not interfere with human visual/audio information input streams necessary for most overground locomotion. Wearable haptics has already been shown to significantly improve movement in a variety of impacting research applications [Review Paper 1] [Review Paper 2].

Why Open Data and Open Algorithm Code?

Open data allows access to all raw and processed data to provide the deepest insights into human movements, and open algorithm code means you no longer have to wonder how movement angles are calculated and feedback cues are initiated. Open algorithm code also means you no longer have to choose whether you will collect raw data or movement angles, because you can do both simultaneously for all trials. Because all algorithm code is open, you can read and deeply understand all physics-based and machine learning movement computation algorithms and how to implement effective haptic feedback training strategies.

Why Customization?

Customization empowers you to perform novel research for your specific movement training application. SageMotion haptic feedback and sensing nodes can be placed in any configuration across any locations on the body to measure and train the wide array of human movements. Customization also means you only use the necessary number of nodes for any given research application instead of being forced to wear a full body suit or complicated set of unnecessary sensors. Through customization you can easily configure which movements are measured and trained and when and how haptic feedback cues are delivered for training.

Why Python?

Python is the most widely used and highly recommended programming language in the world for developing advanced algorithms, and there is a huge community with a vast support system and libraries which makes learning and implementing python highly effective. Python is both simple to learn and a potent framework for developing physics-based and machine learning algorithm code. All open algorithm code in the SageMotion System is in python allowing access to the vast machine learning and movement-related libraries, so you can even easily create and implement your own movement training code!