3:20 - 3:25 pmSaturday, September 17
Upper Lobby
OneRing: automated Parkinson's disease stage classification through random forest learning ensembles - an intelligent wearable ring for monitoring motor symptom progression
Upper Lobby
OneRing: automated Parkinson's disease stage classification through random forest learning ensembles - an intelligent wearable ring for monitoring motor symptom progression
Founder and CEO
This interdisciplinary study develops a wearable ring to automatically classify the stage and severity of Parkinson’s disease through novel machine-learning based signal-processing. The algorithms presented... Read more

Description

This interdisciplinary study develops a wearable ring to automatically classify the stage and severity of Parkinson’s disease through novel machine-learning based signal-processing. The algorithms presented in this study are trained to analyze passively collected movement data; automatically generating a quantified patient report that is critical to tracking disease progression, and optimizing its treatment. Current diagnostic procedures of Parkinson’s – which affects millions worldwide – lack quantification, hence inhibiting a physician’s ability to accurately prescribe medication. The developed ring utilizes power spectral analysis and deviation calculations as feature generation mechanisms to extract the principle components from movement data collected over an entire day. Random Forest (RF) classification then algorithmically identifies unique Parkinson’s motor symptoms and uses the machine-learning ensemble to classify disease severity with 71% accuracy. The RF module, using stochastically trained decision-trees built from a labeled dataset of 30,000 examples, models movement patterns including Bradykinesia, Dyskinesia, and tremor to produce meaningful patient reports. Each report includes thousands of automated classifications resembling Hoehn and Yahr grading – therefore completely revolutionizing how physicians interact with their patients to prescribe medications. Overall, OneRing provides an entirely novel tool for monitoring Parkinson’s, therefore potentially facilitating faster relief from motor symptoms for thousands of patients worldwide.

Utkarsh Tandon is the Founder and CEO of OneRing, an intelligent tool for monitoring Parkinson’s Disease. His creation – a wearable ring, captures movement data from a patient in order to algorithmically identify Parkinson’s movement patterns and classify its severity on a daily basis.

After volunteering at a local Parkinson’s institute over his summer break, Utkarsh decided to build his own company at the age of 15 in order to improve the daily life of a Parkinson’s patient. Since then he has been working on the signal processing and machine learning algorithms to generate smart patient reports that can easily be read by a physician in order to better prescribe PD medications.

Overall, Utkarsh has a strong passion in building products to help the people around him, especially in medical applications. He looks to bring OneRing to Parkinson’s patients all around the world in hopes of suppressing the condition’s rapid progression.

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