Paper Info
Title
Distributed intelligent sensor network for the rehabilitation of Parkinson's patients.
Abstract
The coordination between locomotion and respiration of Parkinson's disease (PD) patients is reduced or even absent. The degree of this disturbance is assumed to be associated with the disease severity [S. Schiermeier, D. Schäfer, T. Schäfer, W. Greulich, and M. E. Schläfke, "Breathing and locomotion in patients with Parkinson's disease," Eur. J. Physiol., vol. 443, No. 1, pp. 67-71, Jul. 2001]. To enable a long-term and online analysis of the locomotion-respiration coordination for scientific purpose, we have developed a distributed wireless communicating network. We aim to integrate biofeedback protocols with the real-time analysis of the locomotion-respiration coordination in the system to aid rehabilitation of PD patients. The network of sensor nodes is composed of intelligent network operating devices (iNODEs). The miniaturized iNODE contains a continuous data acquisition system based on microcontroller, local data storage, capability of on-sensor digital signal processing in real time, and wireless communication based on IEEE 802.15.4. Force sensing resistors and respiratory inductive plethysmography are applied for motion and respiration sensing, respectively. A number of experiments have been undertaken in clinic and laboratory to test the system. It shall facilitate identification of therapeutic effects on PD, allowing to measure the patients' health status, and to aid in the rehabilitation of PD patients.
Year
DOI
Venue
2011
10.1109/TITB.2010.2095463
IEEE Transactions on Information Technology in Biomedicine
Keywords
Field
DocType
microcontrollers,pd patient,wireless communicating network,diseases,t. scha,intelligent sensors,coordination,real-time analysis,intelligent network operating device,step detection,parkinson’s disease (pd),inode,local data storage,pneumodynamics,plethysmography,body sensor network (bsn),wireless communication,patient rehabilitation,distributed intelligent sensor network,parkinson's disease,locomotion,respiration,continuous data acquisition system,wireless sensor networks,force sensing resistor,locomotion-respiration coordination,biofeedback protocol,disease severity,online analysis,microcontroller,intelligent sensor network,protocols,artificial intelligence,real time systems,data acquisition,intelligent sensor,information technology,signal processing,telemetry
Rehabilitation,Signal processing,Digital signal processing,inode,Intelligent sensor,Computer science,Intelligent Network,Wireless sensor network,Biofeedback,Embedded system
Journal
Volume
Issue
ISSN
15
2
1558-0032
Citations 
PageRank 
References 
10
0.61
3
Authors
7
Name
Order
Citations
PageRank
Hong Ying1100.61
Mario T. Schlosser22157153.71
Andreas Schnitzer3100.61
Thorsten Schäfer4100.61
Marianne E Schläfke5100.61
Steffen Leonhardt631978.74
Michael Schiek7144.21