GLNT to use $1.5M NIH award to expand Parkinson’s monitoring technology to mobile apps

Great Lakes NeuroTechnologies (GLNT) announced today they will be using a $1.5M award from NIH to expand their Parkinson’s monitoring technology to mobile applications. Repositioning GLNT’s Kinesia™ product line with mobile apps strategically aligns with growing trends in domestic and international healthcare landscapes regarding accessibility, costs, reimbursement, and regulatory policies. Parkinson’s disease impacts quality of life for millions of people around the world. Tremor, slowed movements, episodes of freezing, gait abnormalities, and therapy side effects that result in abnormal movements can have a major impact on individual quality of life and ability to complete activities of daily living. Monitoring symptoms with patient-worn sensors and connecting clinicians and patients through telemedicine can expand access to care for underserved populations and improve opportunities for adjusting therapy such as medication timing or deep brain stimulation.

GLNT’s FDA cleared to market Kinesia [ http://www.glneurotech.com/kinesia/ ] technology assesses and visualizes Parkinson’s symptoms for in-clinic and telemedicine applications. The current form factor includes patient worn sensors and tablet PC running an embedded application with broadband connectivity. Individuals with Parkinson’s wear mobile sensors, data is sent wirelessly from the patient sensors to the tablet, and the tablet sends data via 3G broadband to a cloud application for processing and clinician reports. While this distribution model has successfully driven the technology into the clinical trials market , the price point required to support the tablet and broadband costs is not sustainable for wide spread acceptance into traditional patient care. Leveraging mobile technology already in the pockets of many individuals can significantly reduce those costs, providing scalability for the patient care market and connecting underserved populations without access to care to clinicians with the expertise to improve their quality of life.

“Great Lakes NeuroTech has a unique industry position to capitalize on emerging healthcare trends and improve quality of care for individuals with Parkinson’s disease”, said Joseph P. Giuffrida, PhD, President and Principal Investigator. “Transitioning Kinesia technology to apps leverages our existing product and cloud infrastructure as well as our strong intellectual property covering the technology, symptom assessment algorithms and accuracy, and adjusting drug delivery or deep brain stimulation therapy based on measure symptoms. Furthermore, recent shifts in healthcare paradigms such as a growing number of FDA approved apps, expanded telemedicine reimbursement, and accountable care cost policies create an environment where apps can play a major role in healthcare delivery for the Parkinson’s community.”

The company is targeting release of the app based technology by the end of 2014 for both the U.S. and European markets. Dr. Giuffrida thanked the National Institute of Health, specifically the National Institute of Neurological Disorders and Stroke for their continued support of this (5R44NS065554) and other funding through the SBIR program.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Predicting mood episodes with sleep data: A breakthrough for mental health care