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Issue No.01 - January-March (2008 vol.7)
pp: 56-61
Shyamal Patel , Spaulding Rehabilitation Hospital, Harvard Medical School
Todd Hester , Spaulding Rehabilitation Hospital, Harvard Medical School
Richard Hughes , Spaulding Rehabilitation Hospital, Harvard Medical School
Nancy Huggins , Massachusetts General Hospital, Harvard Medical School
Alice Flaherty , Massachusetts General Hospital, Harvard Medical School
David Standaert , University of Alabama at Birmingham
John Growdon , Harvard Medical School
Paolo Bonato , Spaulding Rehabilitation Hospital, Harvard Medical School
The pilot work presented here represents a first step toward implementing advanced strategies to optimize clinical outcomes of deep brain stimulation in Parkinson’s disease using systematic data capture and analysis. The authors reliably predicted clinical outcomes by processing accelerometer data that captured motor responses to changes in deep-brain stimulation parameters. Deep-brain stimulation can help manage Parkinson’s symptoms. This department is part of a special issue on implantable electronics.
deep-brain stimulation, Parkinson’s disease, sensors, accelerometer data, data capture, data analysis
Shyamal Patel, Todd Hester, Richard Hughes, Nancy Huggins, Alice Flaherty, David Standaert, John Growdon, Paolo Bonato, "Processing Wearable Sensor Data to Optimize Deep-Brain Stimulation", IEEE Pervasive Computing, vol.7, no. 1, pp. 56-61, January-March 2008, doi:10.1109/MPRV.2008.15
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