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Product
Human-machine interaction.
Selfit’s robotic system combines real-time motion tracking with interactive exercise delivery through a natural, intuitive touch.
It dynamically adjusts to both physical and cognitive levels - creating sessions that are accurate, motivating, and remarkably human.
Smarter care, made personal.
Train with purpose. Move with confidence.
Selfit automates repetitive therapy tasks and assessments - reducing clinician workload, saving time, and improving consistency of care.
It enables continuous monitoring, tailored programs, and adaptive progression - making scalable, high-quality therapy more accessible.
Selfit blends immersive AR with engaging, evidence-based exercises that feel natural but deliver measurable impact - helping to regain strength, independence, and momentum.
It works if you work it.
Health that stays in sync.
Built for connected care, Selfit integrates with digital ecosystems - enabling providers to track progress, engage remotely, and align clinicians, caregivers, and families on one shared platform.
Science
Caring for what matters most.
From early prevention to long-term recovery, Selfit targets the most prevalent brain and heart-related conditions - supporting cognitive and physical function across aging, rehabilitation, and chronic care.
Built on brain science, designed for real life.
Rooted in principles of neural plasticity and motor learning, Selfit promotes brain-driven recovery and helps delay functional decline.
Designed for clinical scalability, Selfit fits seamlessly into hospitals, rehab centers, senior care facilities, and community health programs.
Data
As featured in:
Data in motion.
Selfit captures real-time movement data and turns it into actionable insights.
Advanced machine learning detects subtle patterns, predicts risks, and triggers timely interventions - helping clinicians optimize care and outcomes across conditions.
Contact
Get in touch
Just ping us and we’ll keep on the conversation:
1 - Carolee J. Winstein, Dorsa Beroukhim Kay (2015) Translating the science into practice: shaping rehabilitation practice to enhance recovery after brain damage.
2 - Emma Maureen Gibbons, Alecia Nicole Thomson, Marcos de Noronha & Samer Joseph (2016) Are virtual reality technologies effective in improving lower limb outcomes for patients following stroke – a systematic review with meta-analysis, Topics in Stroke Rehabilitation.
3- Study finds hub linking movement and motivation in the brain, MIT
4- Centers for Disease Control and Prevention, Cholesterol
5 - Centers for Disease Control and Prevention, Heart Disease
6- Centers for Disease Control and Prevention, Stroke
7- Tyson, S. and Connell, L. "The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions: a systematic review." Clin Rehabil 2009 23(11): 1018-1033
8- The Complexity of Standing Postural Sway Associates with Future Falls in Community-Dwelling Older Adults
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