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    Clinical Impact and Evidence

  • Parkinson’s disease affects more than 10 million people worldwide and over one million individuals in the United States. Although pharmacological treatments can alleviate symptoms, no therapy currently halts disease progression. Exercise-based rehabilitation has been shown to improve motor function — yet personalization remains limited in conventional programs.

    Adaptix Neuro builds upon a substantial body of peer-reviewed research demonstrating the benefits of motor-assisted cycling therapy.

    Early Clinical Findings

    In pilot studies conducted by our team:

    • Participants demonstrated 13% improvement in UPDRS motor scores after three sessions
    • Improvements reached 22% after twelve sessions

    These results are particularly significant given the non-invasive, exercise-based nature of the intervention.

    Interaction Variability and Motor Improvement

    Our research identified a key insight:

    Variability in cadence and power output during assisted cycling strongly correlates with motor improvement.

    Specifically:

    • Approximate Entropy (ApEn)
    • Sample Entropy (SampEn)

    were shown to predict therapeutic response.

    This discovery laid the foundation for the adaptive algorithms now embedded within Adaptix Neuro.

  • Objective Measurement and Validation

    Clinical validation includes:

    • Use of UPDRS motor scoring
    • Integration with wearable motion sensors such as Kinesia One
    • Monitoring of physiological signals to ensure safety

    Our Phase I objectives focus on validating real-time adaptive control strategies in lab-based studies with Parkinson’s disease participants, comparing adaptive therapy to static pre-set exercise protocols.

    Beyond Parkinson’s Disease

    While Parkinson’s disease is our initial target population, the broader neurological rehabilitation market includes:

    • Stroke survivors
    • Individuals with multiple sclerosis
    • Patients with motor neuron disorders
    • Aging populations experiencing mobility decline

    The adaptive framework developed by BioMotion allows expansion into these domains without fundamental redesign.

    Toward Scalable, Intelligent Rehabilitation

    Our long-term vision is to enable:

    • Clinic-based deployment under therapist supervision
    • Home-based rehabilitation with remote monitoring
    • Data-driven therapy optimization at scale

    By combining clinical evidence, advanced control systems, and machine learning, BioMotion aims to redefine how neurorehabilitation therapy is delivered — making it more personalized, effective, and accessible.

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