Processing Wearable Sensor Data to Optimize Deep-Brain Stimulation

Author

Patel, Shyamal ; Hester, Todd ; Hughes, Richard ; Huggins, Nancy ; Flaherty, Alice ; Standaert, David ; Growdon, John ; Bonato, Paolo

Author_Institution

Harvard Med. Sch., Boston

Volume

7

Issue

1

fYear

2008

Firstpage

56

Lastpage

61

Abstract

Our study suggests that a sensor-based technique might be an important adjunct to existing clinical measures to improve the management of patients undergoing Parkinson´s control therapy via deep-brain stimulation. In the future, clinicians could gather accelerometer data for approximately one week before and after outpatient visits for deep-brain stimulation adjustments. An expert system could then merge clinical observations and results of the accelerometer data analyses to recommend optimal settings. Physicians would decide how to apply these recommendations as one option for the clinical management of motor symptoms, including adjustments in medication intake as well as changes in settings for deep-brain stimulation.

Keywords

accelerometers; data analysis; diseases; medical expert systems; neurophysiology; patient treatment; Parkinson control therapy; accelerometer data analyses; clinical observation; deep-brain stimulation; expert system; wearable sensor data analysis; Accelerometers; Data analysis; Electrodes; Frequency; Medical treatment; Parkinson´s disease; Space vector pulse width modulation; Testing; Thigh; Wearable sensors; Parkinson’s disease; accelerometer data; data analysis; data capture; deep-brain stimulation; sensors;

fLanguage

English

Journal_Title

Pervasive Computing, IEEE

Publisher

ieee

ISSN

1536-1268

Type

jour

DOI

10.1109/MPRV.2008.15

Filename

4431857