The PROTXX precision healthcare platform integrates wearable sensor and machine learning innovations to replace bulky and expensive clinical equipment and time-consuming testing procedures for a variety of neurodegenerative medical conditions in which patients suffer from impairments to multiple physiological systems. PROTXX solves the difficult problem of identifying and quantifying these multiple different impairments, disrupting diagnosis and treatment with easy-to-use, low-cost, in-clinic and remote patient assessments.

Current clinical neurology, rehabilitation medicine, and sports medicine applications of the PROTXX platform include stroke, concussions, elderly frailty, Parkinson’s disease, multiple sclerosis, peripheral neuropathies, and neurosurgeries. These medical conditions together impact 100’s of millions of patients worldwide, and each one on its own generates annual healthcare costs between 30 billion and 70 billion dollars in the U.S. alone.

How Does it Work

A Physiological Vibration Acceleration (phybrata) sensor is placed behind the patient or the athlete’s ear. This sensor detects the vibrational motion associated with postural stability. The Protxx Platform analyses the sensors’ readings and enables sensitive detection and remote monitoring of neurological, sensory, and musculoskeletal impairments.

A one-minute phybrata test can quantify normal and pathological physiological performance in patients with conditions such as concussion, stroke, peripheral neuropathy, multiple sclerosis, and Parkinson’s disease. The technology is currently being used by clinical neurology and rehabilitation providers, sports medicine clinics, primary care physicians in family and elderly care, and physical/occupational therapists.

Comprehensive Results

The PROTXX mobile app allows PTS tests to be administered by non-expert operators in less than one minute to a single test subject or simultaneously to multiple test subjects. PROTXX cloud-based data storage, analytics, and reporting services utilize the PTS signals to support classification of complex medical conditions based on quantitative assessments of underlying impairments.

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