Wearable assistant for Parkinson's disease patients with the freezing of gait symptom.
In this paper, we present a wearable assistant for Parkinson's disease (PD) patients with the freezing of gait (FOG) symptom. This wearable system uses on-body acceleration sensors to measure the patients' movements. It automatically detects FOG by analyzing frequency components inherent in these movements. When FOG is detected, the assistant provides a rhythmic auditory signal that stimulates the patient to resume walking. Ten PD patients tested the system while performing several walking tasks in the laboratory. More than 8 h of data were recorded. Eight patients experienced FOG during the study, and 237 FOG events were identified by professional physiotherapists in a post hoc video analysis. Our wearable assistant was able to provide online assistive feedback for PD patients when they experienced FOG. The system detected FOG events online with a sensitivity of 73.1% and a specificity of 81.6%. The majority of patients indicated that the context-aware automatic cueing was beneficial to them. Finally, we characterize the system performance with respect to the walking style, the sensor placement, and the dominant algorithm parameters.
Bächlin
Marc
M
Wearable Computing Laboratory, Swiss Federal Institute of Technology Zürich, Zürich CH-8092, Switzerland. baechlin@ife.ee.ethz.ch
Plotnik
Meir
M
Roggen
Daniel
D
Maidan
Inbal
I
Hausdorff
Jeffrey M
JM
Giladi
Nir
N
Tröster
Gerhard
G
D000054:Acceleration; D000368:Aged; D000465:Algorithms; D003020:Clothing; D056228:Feedback, Sensory; D005260:Female; D020233:Gait Disorders, Neurologic / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D010300:Parkinson Disease / Q000503:physiopathology*; D012656:Self-Help Devices; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted